#BUT they got a new location thats a little further away BUT has more space

[paranoidgemsbok]

tending to my podbins and imagining the cute table display i would have at a reptile expo :)

[prof-peach]

Followup to the shroomified Torterra ask!

I did as you said and kept my buddies away from the Torterra, but they still look freaked out. Solosis tried to do something funky with the psychic energy when it came within sight of our house, either stoking aggression or straight up making a hallucination for the Torterra to attack, but as far as I can tell none of their efforts had any effect. Leafeon won't go further than the Pecha trees outside the front door since that.

I remember you asking about region - I live in Sinnoh, near the edge of Eterna Forest and the Floaroma flower fields. As you can imagine, I see a lot of grass types, but not so many at the forest's edge in the last couple of days. Flower field mons seem normal, though. Are they all avoiding the Torterra?

Went ahead and contacted the rangers too, and while they aren't telling me much, it kind of sounds like they're having trouble finding it. How does a shroom turtle that big hide anywhere?? And more constructively, is there anything I can do to ward it away from our home? I don't want poor Leafeon getting even more stressed out.

Fascinating that your solosis tried to evoke a reaction and got nothing. Not a great sign for the host pokemon, i'd put my money on that thing being a deceased mon who's being piloted by the invasive mushrooms. Wouldn't be the first pokemon to have this happen to. I'd kill to study that thing, it's a rare occurrence to see something so big still moving if thats the case. Fingers crossed local experts are too busy and they call us up, though sinnoh is a little out of our usual jurisdiction.

They're surprisingly evasive when they want to be. Settle right into the dirt and basically disappear. It seemed to sneak up on you with a surprising lack of noise, i'm not shocked the rangers aren't able to locate it right away, their camouflage is pretty adept. If they continue to struggle in finding it, I don't doubt a specialist will be brought in to track and investigate it.

As for warding it off, well, if its not conscious of its actions, it'll be very difficult to keep it away should it want to move in your general direction. It has not shown hostility, but may be moving about to find a new host or otherwise infect other things with its spores. I suppose you can see if a cleanse tag warding line would work. thread a load on wire or string, hang them up around the area you want to protect. Theres no guarantee it'll work, but might do something if theres a shred of the original pokemon still in there. Fungi based creatures will stay in the dappled shade and deep forest, they need shade and moisture to thrive, so exposing themselves in wide open fields much like Floroma has would be risky. Not something it should in theory do, unless pushed hard. Take your breaks and walks in the open spaces, bright sun, try to avoid the forests until the local rangers inform you further. Without more information i'd not be 100% certain what to suggest. Still, avoid it wherever possible.

Whatever is happening there, it could very well be very dangerous for the local flora and fauna, wonder where it came from, or what its goal is?

plz rangers, plz call us. We get a handful of cases like this per year, and each is totally wild, love studying it, usually gives some crazy data on the habits of invasive species.

[honkhonkrichard]

Theory: Stanley Uris was Murdered.

Tagging @vvanini I hope you can follow this okay it’s very word vomity lol

Okay So TW because this post will touch on Stan's death ad the methods behind it

I propose that Stan Uris was murdered. by IT. In his home on that fateful night. I think that Stan posed the biggest threat to IT and therefore IT felt the need to take him out before the battle even started.

Allow me to explain.

Okay, so, I need to lay out some basic "rules" or "facts" before I make my case. They are as follows.

- IT planted it's roots in Derry, and finds it difficult to leave, but still can at it’s own wil.  If you read the book (I honestly don't blame you if you haven't) You'd know that once the Losers kill IT for the final time, Derry (the Physical town) is obliterated. Buildings explode, sinkholes appear, things are flooded. The town is in ruins by the time that the Losers leave the sewers. The movies don't adapt this so If this is news to you thats fine. the bottom line is that destroying IT destroys Derry, like ripping a tree out of the ground with all it's roots. Because of this, we can make the claim that while it can Leave Derry (as it does every 27 years) it probably takes tremandous amount of power to do so, which is why IT only goes when the cycle is over. Why does this matter? Well, what if IT left Derry to get to Stan? The murders had stopped for about a week when they're all in the Jade of the Orient. Plenty of time for IT to cross from Maine to Georgia. Side Note: We KNOW IT leaevs Maine to elsewhere in the world because of King's extended universe all interconnecting. it's not far off at all to make the claim that IT is the same evil that haunts, say The Shining's Overlook Hotel, which is in Colarado.

- IT is omnipresent This is also a given, IT lives everywhere, and can fuck with time and space in godlike (or maybe eldritch like) ways. in IT: Chapter Two, when Mike claims "IT Doesn't know I know what I know" he's unfortunately wrong, because we know that IT can be in A) Multiple places at once, B) can manipulate anything on the drop of a hat (See: Stan being teleported away from everyone else in Chapter One, Everything about Neibolt, etc) and C) Knows everyone's deep fears. This is further proven by IT Saying things like "Beep Beep Richie" (although this is Horribly Horribly executed in the films, ugh.) and so on and so forth. On top of all of this, We can make the claim that IT can exist outside of Time as well, given that IT is immortal. SO, what's stopping IT from Knowing Mike was going to call them all back (Espically considering that IT TOLD Mike to do this?). Even if we keep IT's omnipresence to the location that IT inhabits (in this case Derry) IT would still have knowledge of where the losers are through Mike. And if you take the Lucky Seven/Chosen Seven route (oh my god I got theories on that too) you could argue IT knows where they are inherently due to their cosmic status.

- Stan is the "most Powerful" loser So, obviously all the Loser's are powerful, espically considering they're the ones who Defeat IT (Again going on to the Lucky/Chosen Seven theory). This next claim is going to be less focused on what the 2019/2017 Movies do because they are Bad Movies and that's a whole other rant. However, in the book, Stan is (to my knowledge feel free to correct me on any of this) the only loser to Actively ward off and 'defeat' IT on his own without running away. He uses his belief in this what is Real (birds) to ward off what is "not real" (IT). The other losers do manage to take down IT in their own Right, but Stan is ultimately the one to Really get IT. This is because Stan's character revolves around Belief and Willpower. These are, in some form or another, the ways to Defeat IT. the ritual of Chud is a battle of Wills. in the book, Bill takes IT down and Eddie does the final blow. In the Remake (ugh) the losers can defeat it Technically using the belief that IT isn't as powerful as it claims because IT's "just a clown" (Ihatethatfuckingendingsomuchugh). Stan being much more skeptical than the rest of the group in his ability to understand Reality vs IT's illusions is a powermove, and IT knows that ability doesn't go away as Stan grows up, but rather he gets more powerful. Stan is the Only loser out of the 6 who left that has any sort of knowledge about IT, where the other losers have nothing. Bev has nightmares, yes, but she still forgets them. We're told in his chapter (Chapter 3, Six Phone Calls (1985), Part One: Stanley Uris Takes a Bath) that he has some hazy knowledge of his place in the Lucky Seven, and even goes so far as to MENTION it sometimes, even if he doesn't quite remember or understand any of it, his knowledge of IT and Derry is worlds more prominent than that of the rest of the losers.

(page 52 of IT:  "Stanley, nothing's wrong with your life!"  "I don't mean from inside." he said. "From inside is fine. I'm talking about outside. Something that should be over and isn't. I wake up frmo these dreams and think, 'My whole pleasent life has been nothing but the eye of some storm I don't understand.' I'm afraid. But then it just... fades. The way dreams do." OR  page 45: He had been smiling a little. Now the smile faltered, and for a moment he seemed puzzled. His eyes had darkened, as if he looked inward, consulting some interior device which ticked and whirred correctly but which, ultimately he understood no more than the average man understands the workings of the watch on his wrist. "The turtle couldn't help us," he said suddenly. he said that quite clearly.)

So, Stan has some cosmic knowledge of IT and Maturin and his role in the battle against It. What does any of this have to do with his death? Well, let me point out some other things about Stan's death that always stuck out to me. - His death chapter is narrated by his wife, Patty, rather than himself. The other chapters - almost all the other chapters - are narrated by their respective Loser (the caviot for this is Ben, but Ben is also wasted out of his damn mind so its understandable.) - Stan's personality is few and far between in the book, but we know he has a weird little sense of humour and that he's incredibly logical. I think that this logical part of him would be able to understand that Suicide is Never Ever the answer, and that it would cause FAR more problems than it would solve. (the 2019 movie tries to reexplain his death and it's crap and i hate the letters i hate the letters so much im gonna explode) The other losers try to rationalize his death by saying "He would rather Die Clean than Live Dirty (Page 506, Chapter 10, The Reunion, part 3, 'Ben Hanscom Gets Skinny') but he had already BEEN Dirty when he defeated IT the first time, and I think he would've recognized that. - upon finding him, Patty (in her narration) notes that Stan's head is bent back over the edge of the bathtub, so from his sight she would have been upside down. If Stan DID kill himself, why would he be positioned like that? It's unnatural, like someone Posed him. - the cuts on his arms are two length wise cuts. I'm no expert but.. that's suspicious. That's weird. - IT is written in blood on the wall. Why? Why would Stan right THAT of all things? You know who DOES like to paint with blood? IT.

Alright, returning to my thesis statement, Stanley Uris was murdered. Do I think Stan genuinely was going to take a bath at 7pm (which we're told is weird for him)? Yes. I think that's absolutely a thing he could have done or planned to do. Do I think he slit his wrists and commited suicide so he wouldn't go back to Derry? No. Not even remotely.

Let me paint a New Picture.

It's May 28th, 2016, or 1985. Stanley Uris gets a call from Mike Hanlon. Stan is incredibly hesitant to go to, and says he needs time to think about it. Or tht he'll try. He can feel the starts of a Panic attack, and as he's remembering the circles of Hell he went through as a child, he tries to hold himself together. He doesn't want his darling wife to see his break, so he says "I think I'll take a bath" and nothing else before going upstairs. he hides in the bathroom. He closes and locks the door, because, well, he's panicking. Locking doors is one of The Small things he does. Is it usually the bathroom door? no, but still (OCD is a bitch, and even with medication, but this is a special case). He looks in the mirror and tries to breathe. This is fine. He can do this. They killed IT once before and they can do it again. He thinks about his younger self, the promises made, and how he could explain all of this Patty in time to catch a flight to Maine. It's terrifying, but if his friends are going to bite the dust, he wants to be there with them, wedding vows be Damned. Then he looks at his reflection again. A younger, rotted version of himself stares back at him. IT crawls through the mirror. Stan freaks out, obviously. This isn't real. This Can't be real. But IT utilizes this notion against him. It digs it's claws into his arms, and forces him to bleed out in the bathtub. IT then sets the scene nicely. Razorblades on the counter, a bloody signature on the wall, a horrible posture of Stan's neck. So on and So forth. and then IT returns to Derry. IT's a little weak, yeah, but Stan is dead. That's what matters. the Lucky Seven has now Officially broken, and the balance shifts in favour of the clown.

So that's the theory. feel free to correct me on anything or engage I have plenty of theories on this story and I like discussing this stuff :).

[blackfiire-archive-blog]

Its funny.

Sometimes one only hopes to join a specific environment, you know?

Just imagine: You were welcomed into a kind, loving environment after your old one became abandoned. You came with intentions to share your shiny doll with everyone.

You’ve always wanted to be there. You were always on the outside looking in whenever you walked by. Everyone looked so happy.

The space is full of warm, kind, generous people. They’re smiling at you, beckoning you to come forth. And while you make your way inside this bubble, in that moment, you are accepted into their space and your doll has been recognized for her unique stitching.

You are happy. Your doll that you dressed all pretty is being shared. Well. Only with some. There are others who gently pass it to the next because it is not their thing—that is ok. You were just honored to have the chance to show it to them. Then there are others in hoods who refuse to show their face who downright throw it away in disgust.

You are sad, but there are people who pick up your doll, brush her off and ask if you would like to see theirs.

You’re ecstatic! Finally! Somebody wishes to share and trade their doll with you. And yet.

You find that everyone adorns a tag—a tag that matches all others within the space. They’re beautiful, black onyx gems, hearts and all. You wish you could have one, to show them you want to be part of their world too, but. You already have a tag—old and withered. But its there.

You take a look at your wrist finding that your previous tag from your abandoned environment is rusted, old, falling apart. You cant help but only dream to become a new tag owner within this environment. However you are made aware that to earn this tag, you must first trade your doll with people. Other people. Not just the friends you made.

So. You try.

You hold out your doll to one person, they kindly refuse it. Thats all well and wonderful. You arent saddened. They have their own tastes and gently let you know. They’re really kind about it. Same as the next, and the next, and the next. You made decent acquaintances along the way—a few who would do anything to get your doll out there to share with the world. You are just so indebted to them. You dont know how to thank them for everything.

Time goes on. Your doll is in your arms, you’re cradling her as carefully as possible.

You then hear groups of people call attention to themselves who want to trade dolls and their background.

They looked fun!

Excitedly, you make your way to their cot. You tap, you ask, you show your doll. They all seemed interested. They all looked surprised! They allow you to see their dolls as well…but you may only look. You may not touch or trade. It is clear they do not trust you well. But who would? You are a complete stranger.

BUT!

You arent bothered by this. Sometimes you do that, too. But now could be your big chance to draw your doll a story with their help! You get your crayons and paper out and then…

Its until the moment you speak your words go unheard over the deafening sounds of group chatter and play. The dolls you werent able to touch are handled among the gathering of people—friends. You assume they could all play! And you try. They don't hear you…

You ask to be included in their fun. You had crayons for everyone! …They don't even look at you.

You peer down at your doll and wonder what you can do to make people see how wonderful she truly is. She has other qualities besides her stitching. Honest. She can be cool.

If only they’d given you a chance…

With that in mind, you’ve already bothered them enough, but as inspiration takes you, you decide it is time to make something special for your little companion.

Scooping up your doll, you hear the faint laughter of friends sharing, trading, and making each other gifts while you sit on a bench next to the one thing that makes you happy. You jot down ideas on paper and nail them to a public oak. You are there. The people see you. They walk by. They eat some treats from your cookie stand. But now, they don't approach you. Why?

You make pretty pieces of paper with glitter and glue to get over your nerves to make some friends with the previous bunch. You give your creations to them. They’re so happy. You like seeing them that way. And the few who loved your pictures gave you their dolly hideout location. If you wanted to talk outside of the space.

You made some friends!!

You try the same method once more. Nothing. You try a different approach. Nope.

You try. And try. and try. But…nothing. Nada.

Eventually, the two friends you made in this specific space approach you with a gift of their own. You’re overjoyed.

What could it be? A new piece of cardstock paper to make your glittery art? A board with pictures of your doll adorning every corner?

No. Its something more, but just as precious.

Revealing to your their gift, your eyes are wide. Their gift shines and dangles near your irises. Tears of joy find their way to the corners of your eyes. Your friends, they accepted you. They wanted you there with their doll. They wanted you to share your doll.

Tears stain your cheeks. Your doll doesn't get handled often, but the few friends you made along the way want you there.

You slip on the tag. Its beautiful. You couldn't be happier.

Just then. The friendly, warm, welcoming space you loved goes black. Everyone disappears. You can hear your friends calling to you in the darkness. You’re desperately fumbling around in the black abyss to feel for their hand.

Where are they?!

You panic. You cant see. Their voices are getting fainter and fainter. You’re running now. You scream for them. Their voices but a whisper of an echo.

You stop. Head lowered. What just happened? What...have you done?

You can see dim lights in the shape of people further on. Who are they, and why were they doing? A rescue?

You decide to go towards them. They were the only source of light in the darkness. You can hear them laughing. Having fun. Yet the more you walk, the further they got.

You start running. Trying to reach that very light that seemed so close, but now its so far away. It doesn't matter how long you continued forward, you were going nowhere. You weren't going to reach that light. Ever.

Gingerly wrapping your arms around your doll, you weep into her. All you wanted was to be in the light, with your friends. No one can hear you. No one can see you. Sometimes a faint calling of your name whispers all around. Maybe, it was the darkness’s way of keeping you busy—filling you with false hope so it can drain it repeatedly.

Sometimes footsteps could be heard lingering beyond the void, without a person in sight.

You are utterly alone.

You miss your friends.

Why did you take the tag? Why?

Maybe someday, a soul like you will drop on this plane. Hungry for adventure, starving for acceptance. Bright eyed and…ignorant. Just like you.

Today will not be that day, however.

Truly.

That day may never come.

[mcaputoart]

You ever had an idea for a pic that just would not leave you alone unless you actually did it? Well thats basically what happened here. Based on a pic I did back in 2012 and an idea I had for a crossover (just for fun).

The story for the most part is three of the chaos emeralds have been scattered to different worlds and its up to Sonic and Mitch (the girl in the pics and yes she has a boys name #idontgiveacrapdealwithit ) to go to those worlds and find the chaos emeralds before its to late.

maybe I’ll redo the pic I did in 2012 and write in a little summary/story about this later but until then enjoy ^^*

----------------------UPDATE----------------------------

I redrew the pic I did back in 2013. I have to say that I can deffinetlly see a diffrence from 4 years ago and I'm very happy with myself (i'll upload a before & after later) doing all 4 of these was very challenging but I'm glad I did them I feel like I've improved myself in away.

and just like the 2013 one I revamped the little story/summery I wrote for this. This was all done for fun and because I can XD (I would also like to point out in advance that I'M NOT THAT GREAT OF A WRITER!!!!). So without further delay... ENJOY MY AMATEUR WRITING EVERYBODY!! XD

                                                                             Sonic Across The Multiverse

                                       Concept by Michelle Caputo

                               Eggmans latest plan/creation is to use the power of the chaos emeralds to help him creat his empire and take over the world. but Sonic once again foils Eggmans evil planes and damages Eggmans machine. However this causes the machine to malfunction making three of the chaos emeralds to just disappear and then explodes leaving four of the emeralds behind. After analyzing the data from the four remaining chaos emeralds, Tails concluded that the three chaos emeralds that disappeared were somehow actually sent to different worlds/universe and if they don't get them back soon the emeralds will cause chaos and even destroy what ever world they're in and even destroy their own world as well (so they properly have about a week to find them before all hell breaks lose.... Absolutely no pressure)  It'll be up to Sonic to get them back but he's going to need help.

That's were my OC Mitchel comes in. A half human half creature who has the ability to travel to different worlds/dimensions/universes ect. Tails creates a portal ring that will open a portal to what ever world has a chaos emerald (which will make the search a little easier and go faster) However it will only work if there's a chaos emerald present and with  Mitchel's powers.

(Basically they need to find an emerald in order to go to the next world that has a chaos emerald and Mitchel is the only one that can power it and because they have four of the emeralds they'll be able to go the first world just fine but after that their on their own.)

Also will be taking three power rings for Sonic just incase of an emergency (hence the backpack and need a place to put the emeralds in). Tails will stay be hide to keep an eye on the remaining chaos emeralds while also be able to contact them if anything new develops. So into the unknown they go in search for the three missing chaos emeralds.

Jak & Daxter:

Mitch and Sonic have been wondering through the wasteland for hours trying to find the chaos emerald (and civilization to get out of the heat) when suddenly a metalhead beast comes out of nowhere and attacks them. Fortionatly in the far, far distant there was a city (Haven city). Sonic runs off to the city to get help while Mitchel stays be hide and fights off/distracts the metal head. While approaching the city a young man and his osttsel notices a blue blur pass them by and heading towards Haven city. Thinking it was a threat they got in their vehicle to go after Sonic. (Though the chase some how turned into a race) Not being able to keep up with Sonic, Jak's car flips over. Sonic then stops to help them from under their vehicle. Sonic then quickly tells them that his friend is in trouble and he came looking for help. Jak agrees to help so he gets in his vehicle and follows Sonic to the location of the metalhead.

Upon arriving they see that Mitch has already taken care of the metal head and was just waiting for Sonic to get back (well.. at lest Mitchel has a ride now). Mitch rides with Jak and Daxter (Sonic running beside the car of course) and they go back to Haven City. There Mitch and Sonic explained to Jak and friends about the situation and how the chaos emerald could destroy their world if they don't find it soon. They find out that the emerald landed in dark Eco which is causing a chain reaction to the worlds weather patterns which will lead to devastating results if it continues.  So they have to find and retrieve the dark Eco powered emerald before that happens. Or worse someone else finds it.

When they find the Emerald they discovered that it was tainted with dark Eco (do to it being in the dark Eco for to long) which not only made it very unstable, but it won't be able to open the portal ring to where the next chaos resulting in Sonic and Mitch being stuck there. But by Jak touching the emerald he was able to absorb the dark Eco from the chaos emerald returning it back to its normal state. Sonic and Mitch got the first of the three missing chaos emeralds and were now able to activate the portal ring to the next location for the 2nd chaos emerald.

Sly Cooper:

                           After wondering in the city of Paris for a while they find out that a crime boss named "Boss" (very creative I know XD;) has gotten his hands on the 2nd chaos emerald and has become very powerful in the crime world. They discovered that the emerald was being kept at a were house for a short time. So not wanting to draw to much attention to themselves they'll have to take a more silent approach and steal it back. The plan was simple Mitch would handle the security stuff while sonic goes in, get the chaos emerald and get out. Quick and easy. Get in, get out no worries.

However it would seem that they weren't the only ones after the emerald, as Sonic was confronted by a thieving raccoon. Their confrontation causes one of them tripping the alarm resulting in putting the place on lock down trapping them both in side the were house. Hearing the alarms going off from the were house Mitch quickly goes to help Sonic get out of there. They were able to get out of the were house but end up running into the boss's men who start shooting at them. They were able to take down a few of them but more kept coming surrounding the three. They were out matched, out gunned and needed to get out of there now.  They end up at a fence and started climbing only for Sly to get shot in his right arm making him unable to escape. Just when it seemed like they were cornered, a van drives through the fence and stops right between them and the men shooting. The door opens and inside the van was a hippo at the wheel and a turtle in a wheelchair telling Sly to get in the van. Sly turns to Sonic and Mitch and tells them to get in the van as well and drove (more like plow) their way out of there and took the two strangers back to their hide out.

There the Cooper gang introduce themselves and Mitch (while healing Sly's gunshot wound) explained to them who they were and how the jewel they were about to steal was a chaos emerald and if they don't get it back soon their world will be destroyed. They agreed to work together to take down this crime boss and get the chaos emerald back. (Which they do with planing, fighting and all that 007/mission impossible/Lupin the 3rd stuff XD)

The crime boss' empire was destroyed, put be hide bars, and they were able to get the chaos emerald back. Now having two of the chaos emeralds they went off to the next world to find the last and finale chaos emerald.

Ratchet & Clank:

                                After arriving they found themselves in the middle of an invasion. There where robots everywhere causing chaos and destruction and a few of them spotted Sonic and Mitch and went after them. The two where able to take them out. Sonic spotted another robot in the distance only it was a little robot being chased by a bigger robot. Without a moments hesitation charges right for them. Smashing the bigger robot and was about to go for the little one when Mitch stops him stating that the little robot he was about to smash didn't seem like it was part of the invasion. The little robot thanked them for saving him and introduced himself (Clank) and explained to them about the invasion and that he and his companion (Ratchet) got separated while fighting the robots and has been trying to find him. They agreed to help Clank find His friend but they soon find out that Ratchet has been captured by evil robotic geniuses (Dr Nefarious) and was kept prisoner on his new space ship ( it was more like a war ship but whatever XD). Now The three have to go sneak on Nefarious's ship and rescue the Ratchet. When they finally reach Ratchet it turns out to be a trap in order to get the two chaos emeralds by Nefarious new accomplice.......Dr Eggman. (DUN DUN DUUUUUUUNNNN!!!)

It was then revealed that Dr Eggman was here the whole time (using a portal that he created himself) and had teamed up with Dr Nefarious to take over the universe with the 3rd chaos emerald and was waiting for them to bring the last 2 chaos emeralds. Now that they have the 3 of the missing chaos emeralds they would conquer this universe, go to Mobius to get the remaining 4 chaos emeralds, conquer Mobius and then ALL OF THE MULTIVERSES!!! (maniacal laugh).

Of course while they were busy explaining/gloating about their evil plan Clank was able to break free and freed everyone else to escape from the space ship. But Eggman and Nefarious still had the 3 chaos emeralds so Ratchet, Clank, Sonic and Mitch set out to foil their evil plan and get the 3 chaos emeralds back (EPIC BATTLE!). Mitchel disappears and was nowhere to be found. But the remaining three continue on to fight and then were completely surrounded and captured (again). But then it's reveled that Eggman double crossed Nefarious and has complete control of the ship and the 3 chaos emeralds! (This however was a surprise to NO ONE as the three totally saw this coming. Plus Nefarious was also planing a double cross as well but Eggman beat him to it). Eggman was victorious!'

Just as he was about to finish them off a shadowy figure comes out of nowhere and steals back the 3 chaos emeralds. But who could it be? was revealed to be.....SLY COOPER! (GASP!) Then there was an explosion revealing all of Eggmans robots being destroyed. Who could have cause such destruction and chaos? When the smoke cleared it turned out to be Mitch who was accompanied by...... JAK AND DAXTER! (DOUBLE GASP!!). Then Sonic Clank and Ratchet were freed. But how? How were they able to get on the ship by passing the security codes? Why it was none other then......TAILS! (TRIPLE GASP!!!) and also had with him the OTHER FOUR CHAOS EMERALDS!!! (*head explosion*)

(When Mitch went a-wall before she actually went back to Mobius to get the 4 other chaos emeralds and Tails while also getting Sly, Jak and Daxter on the way back).

And now that all 7 chaos emeralds were percent, Sonic uses them to become Super Sonic, ruins Eggmans plans, destroys the spaceship and saves the day! (YAY!) After saying good bye to their new friends, Sonic asks Mitch if she was coming back with them. She told him no and that she was going to hang around here for awhile (plus she's has to take Sly, Jak and Daxter back to their own worlds) and that she'll see him later.

So with Eggman and the chaos emeralds in hand, Sonic and Tails go through the portal ring back to Mobius where they belong.

                                                     The End.

[the-kool-kyle]

Captain Marvel Review

Disclaimer: This review will start off with a couple of spoilers to Avengers: Infinity War. So if you haven't watch that yet don't read any further....but come guys we all know you've watched it.

It's been almost a year now since the shocking ending to Avengers: Infinity War where the mad titan Thanos used The Infinity Gauntlet with all six Infinity Stones to kill %50 of the universe population and also killing off a couple of our favourite characters as well. Setting up what is definitely the darkest time in the MCU's history. However before he disintegrated into dust Nick Fury sent out a distress call to an old friend of his.....Captain Marvel. Who is probably the best, last and only hope to undo the Mad Titan's plan. Now we've been given a origin story that's also a prequel to introduce this new character and how she'll play a role in MCU's later films.

Plus since this takes place 12 years before Iron Man this movie has a lot of references and foreshadowing to the other MCU movies.

Captain Marvel is a fun, thrilling, well written, perfectly acted and visually mind blowing movie that despite feeling a little out of place in phase 3 still explodes onto screens feeling like a much more fresh and original approach than anything we've seen in the last 3 years. The character Captain Marvel has been passed to many people throughout the marvel comics over the years and has also been known as Captain Mar-Vel. But this film is focusing on the Carol Danvers Captain Marvel.

Carol Danvers was originally known from the comics as being the love interest for the original Captain Mar-Vel and a damsel in distress (which was a bio product of the time). She eventually gets her own powers to becomes Miss Marvel and a member of the Avengers. However the film takes a more different approach to the origin story and she is instead introduced as a solider for the alien civilisation known as the Cree who experiences nightmares and flashbacks to her past life. She eventually crashes to earth in the year 1995 and must face a race of evil shape shifting aliens known as The Skrulls.

Brie Larson as Carol Danvers Aka Captain Marvel was the perfect choice for this iconic Avenger who is also a great match between actor and role. She plays a super-heroine that has something of a no nonsense but playful attitude and is also a strong independent female lead that really shows women can be great superheros just as much as men can. She's one of those comic book characters thats warm and friendly to her friends but deadly and shows no mercy to her enemies as she shows throughout most of the films runtime. But best of all she explodes onto the screen with her badass looking suit with the mohawk helmet that I personally really dig and her awesome super powers that include strength, flight, energy absorption and the ability to fire photon blasts from her hands.

Sam L Jackson returns as Nick Fury who in this movie is a junior agent at Shield and has two eyes!Since this is a much younger and inexperienced Fury he acts less of the wise, mysterious mentor with the iconic eye patch and more like a fun loving, stubborn young man with a great sense of humour. He shares a classic buddy cop friendship with Marvel which feels like something straight out of a classic 90s Tv show that really fits the decade this movie takes place in. So while he isn't as intimidating or as badass as he was in the other movies he still stands out as the cool, smooth talking secret agent.

As you may have noticed from the posters and trailers is that there's a cat in this movie known as “Goose”(which is a Top Gun reference). He straight up steals the show like Korg from Thor Ragnarok thanks to his adorable appearance and many crazy things he does...that I can't in good conscience spoil for you guys.

The many set pieces and locations in this movie look amazing both in outer space and earth. Since this movie is set in 1995 it has a lot 90's styled references and easter eggs like Blockbuster video, gameboys and ripped jeans. Plus this film's killer soundtrack contains many classic vintage tunes that rival Guardians of the Galaxy and reminding us how awesome the 90's were.

Unfortunately like many of the other MCU movies...this one's villains fell flat. We've all had to deal with disposable, generic villains that only last one movie and Captain Marvel's “The Skrulls” are no different. The Skrulls are a race of aliens that can shape shift into any form of any species making them the perfect enemies to hide in the shadows and pull strings from behind the scenes. While they are cool in the comics in this movie they are a far cry away from many of the MCU's good villains like Loki, Hela, Ultron and Killmonger. So once again we have forgettable boring villains in a superhero movie. But I will say this their shapeshifting scenes are really well done and look really real.

The supporting cast ranged from fun and cool to just generic and boring. Jude Law plays as Cap's commanding officer Yon-Rogg who is actually not all that interesting. While Law is a great actor he just doesn't really belong in this kind of comic book movie as he just basically acts like himself in real life and not like a Star-force Commander who is driven by belief and who is meant to be inspirational. Clark Gregg returns as a young agent Coulson who we were really looking forward to see since we haven’t seen him since the first Avengers or Agents of Shield but unfortunately he's barley used in the movie and felt wasted which was a bit of a let down. However Lashana Lynch's character Maria Rambeau really felt like someone we know in our own lives. She plays as the badass best friend of Carol Danvers that you don't really need to help out cause she can hold her own against anything plus she is seen as an equal to many of the films more powerful and independent characters with playful competitiveness. I found her as a very well played and respected female character.

Now the one thing that really blew this movie out of the water was it's visuals, CGI, costumes and action! The action was both thrilling and engaging and felt like moments ripped straight from the comics as Captain Marvel battles enemies in epic space battles in the cosmic void of space and the many familiar set pieces of earth. It truly is some of the best action sequences in the MCU to date. The CGI and visual effects were really well design and animated especially well during the space battles and epic fight scenes between Cap and the Skrulls. The CGI blended very well with the practical effects making it look a lot more real instead of just relying solely on CGI especially on Cap's suit. Which brings me to the costumes. I gotta give a 10/10 for the costumes that were used for the Skrulls, the Cree and Captain Marvel herself. Captain Marvel's suit looked really awesome with it's red, blue and gold colour design and it looks especially awesome when she uses the mohawk helmet. It makes her look even more badass and I think it's awesome that they used her own hair as the mohawk because it just makes really cool and was never used in the original old Miss Marvel comics. CGI was also used on Nick Fury to make him look younger in this film and while this has been either a hit or miss in the past they really nailed it for Fury. He looks exactly like what he'd look like if he were 20 years younger.

One thing that I feel I should mention is that some people saying that this movie has a major flaw. Since this movie is an origin story it feels out of place at this point in the MCU because were nearing the end of phase 3 and origin story movies mainly took place in phase 1. I really don't see how this is a problem so just make up your own mind if you feel this movie belongs in phase 1.

Final Verdict: Captain Marvel is an awesome, thrilling, entertaining movie with a well told story, plot twists, easter eggs galore, excellent acting but most importantly must be seen immediately because it ties in heavily to Avengers: Endgame and must be seen if your a true MCU fan like me. Because....Endgame will soon be upon us.

Final Score: 9/10

P.S. I got a bit emotional at a point in this because it has a tribute to Stan Lee.

[we-johnnygonzalez-blog]

A Guide to Setting Up Your Very Own Search Intent Projects

Posted by TheMozTeam

This post was originally published on the STAT blog.

Whether you’re tracking thousands or millions of keywords, if you expect to extract deep insights and trends just by looking at your keywords from a high-level, you’re not getting the full story.

Smart segmentation is key to making sense of your data. And you’re probably already applying this outside of STAT. So now, we’re going to show you how to do it in STAT to uncover boatloads of insights that will help you make super data-driven decisions.

To show you what we mean, let’s take a look at a few ways we can set up a search intent project to uncover the kinds of insights we shared in our whitepaper, Using search intent to connect with consumers.

Before we jump in, there are a few things you should have down pat:

1. Picking a search intent that works for you

Search intent is the motivating force behind search and it can be:

Informational: The searcher has identified a need and is looking for information on the best solution, ie. [blender], [food processor]

Commercial: The searcher has zeroed in on a solution and wants to compare options, ie. [blender reviews], [best blenders]

Transactional: The searcher has narrowed their hunt down to a few best options, and is on the precipice of purchase, ie. [affordable blenders], [blender cost]

Local (sub-category of transactional): The searcher plans to do or buy something locally, ie. [blenders in dallas]

Navigational (sub-category of transactional): The searcher wants to locate a specific website, ie. [Blendtec]

We left navigational intent out of our study because it’s brand specific and didn’t want to bias our data.

Our keyword set was a big list of retail products — from kitty pooper-scoopers to pricey speakers. We needed a straightforward way to imply search intent, so we added keyword modifiers to characterize each type of intent.

As always, different strokes for different folks: The modifiers you choose and the intent categories you look at may differ, but it’s important to map that all out before you get started.

2. Identifying the SERP features you really want

For our whitepaper research, we pretty much tracked every feature under the sun, but you certainly don’t have to.

You might already know which features you want to target, the ones you want to keep an eye on, or questions you want to answer. For example, are shopping boxes taking up enough space to warrant a PPC strategy?

In this blog post, we’re going to really focus-in on our most beloved SERP feature: featured snippets (called “answers” in STAT). And we’ll be using a sample project where we’re tracking 25,692 keywords against Amazon.com.

3. Using STAT’s segmentation tools

Setting up projects in STAT means making use of the segmentation tools. Here’s a quick rundown of what we used:

Standard tag: Best used to group your keywords into static themes — search intent, brand, product type, or modifier.

Dynamic tag: Like a smart playlist, automatically returns keywords that match certain criteria, like a given search volume, rank, or SERP feature appearance.

Data view: House any number of tags and show how those tags perform as a group.

Learn more about tags and data views in the STAT Knowledge Base.

Now, on to the main event…

1. Use top-level search intent to find SERP feature opportunities

To kick things off, we’ll identify the SERP features that appear at each level of search intent by creating tags.

Our first step is to filter our keywords and create standard tags for our search intent keywords (read more abou tfiltering keywords). Second, we create dynamic tags to track the appearance of specific SERP features within each search intent group. And our final step, to keep everything organized, is to place our tags in tidy little data views, according to search intent.

Here’s a peek at what that looks like in STAT:

What can we uncover?

Our standard tags (the blue tags) show how many keywords are in each search intent bucket: 2,940 commercial keywords. And our dynamic tags (the sunny yellow stars) show how many of those keywords return a SERP feature: 547 commercial keywords with a snippet.

This means we can quickly spot how much opportunity exists for each SERP feature by simply glancing at the tags. Boom!

By quickly crunching some numbers, we can see that snippets appear on 5 percent of our informational SERPs (27 out of 521), 19 percent of our commercial SERPs (547 out of 2,940), and 12 percent of our transactional SERPs (253 out of 2,058).

From this, we might conclude that optimizing our commercial intent keywords for featured snippets is the way to go since they appear to present the biggest opportunity. To confirm, let’s click on the commercial intent featured snippet tag to view the tag dashboard…

Voilà! There are loads of opportunities to gain a featured snippet.

Though, we should note that most of our keywords rank below where Google typically pulls the answer from. So, what we can see right away is that we need to make some serious ranking gains in order to stand a chance at grabbing those snippets.

2. Find SERP feature opportunities with intent modifiers

Now, let’s take a look at which SERP features appear most often for our different keyword modifiers.

To do this, we group our keywords by modifier and create a standard tag for each group. Then, we set up dynamic tags for our desired SERP features. Again, to keep track of all the things, we contained the tags in handy data views, grouped by search intent.

What can we uncover?

Because we saw that featured snippets appear most often for our commercial intent keywords, it’s time to drill on down and figure out precisely which modifiers within our commercial bucket are driving this trend.

Glancing quickly at the numbers in the tag titles in the image above, we can see that “best,” “reviews,” and “top” are responsible for the majority of the keywords that return a featured snippet:

212 out of 294 of our “best” keywords (72%)

109 out of 294 of our “reviews” keywords (37%)

170 out of 294 of our “top” keywords (59%)

This shows us where our efforts are best spent optimizing.

By clicking on the “best — featured snippets” tag, we’re magically transported into the dashboard. Here, we see that our average ranking could use some TLC.

There is a lot of opportunity to snag a snippet here, but we (actually, Amazon, who we’re tracking these keywords against) don’t seem to be capitalizing on that potential as much as we could. Let’s drill down further to see which snippets we already own.

We know we’ve got content that has won snippets, so we can use that as a guideline for the other keywords that we want to target.

3. See which pages are ranking best by search intent

In our blog post How Google dishes out content by search intent, we looked at what type of pages — category pages, product pages, reviews — appear most frequently at each stage of a searcher’s intent.

What we found was that Google loves category pages, which are the engine’s top choice for retail keywords across all levels of search intent. Product pages weren’t far behind.

By creating dynamic tags for URL markers, or portions of your URL that identify product pages versus category pages, and segmenting those by intent, you too can get all this glorious data. That’s exactly what we did for our retail keywords

What can we uncover?

Looking at the tags in the transactional page types data view, we can see that product pages are appearing far more frequently (526) than category pages (151).

When we glanced at the dashboard, we found that slightly more than half of the product pages were ranking on the first page (sah-weet!). That said, more than thirty percent appeared on page three and beyond. So despite the initial visual of “doing well”, there’s a lot of opportunity that Amazon could be capitalizing on.

We can also see this in the Daily Snapshot. In the image above, we compare category pages (left) to product pages (right), and we see that while there are less category pages ranking, the rank is significantly better. Amazon could take some of the lessons they’ve applied to their category pages to help their product pages out.

Wrapping it up

So what did we learn today?

Smart segmentation starts with a well-crafted list of keywords, grouped into tags, and housed in data views.

The more you segment, the more insights you’re gonna uncover.

Rely on the dashboards in STAT to flag opportunities and tell you what’s good, yo!

Want to see it all in action? Get a tailored walkthrough of STAT, here.

Or get your mitts on even more intent-based insights in our full whitepaper: Using search intent to connect with consumers.

Read on, readers!

More in our search intent series:

How SERP features respond to intent modifiers

How Google dishes out content by search intent

The basics of building an intent-based keyword list

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[lawrenceseitz22]

A guide to setting up your very own search intent projects

Posted by TheMozTeam

This post was originally published on the STAT blog.

Whether you’re tracking thousands or millions of keywords, if you expect to extract deep insights and trends just by looking at your keywords from a high-level, you’re not getting the full story.

Smart segmentation is key to making sense of your data. And you’re probably already applying this outside of STAT. So now, we’re going to show you how to do it in STAT to uncover boatloads of insights that will help you make super data-driven decisions.

To show you what we mean, let’s take a look at a few ways we can set up a search intent project to uncover the kinds of insights we shared in our whitepaper, Using search intent to connect with consumers.

Before we jump in, there are a few things you should have down pat:

1. Picking a search intent that works for you

Search intent is the motivating force behind search and it can be:

Informational: The searcher has identified a need and is looking for information on the best solution, ie. [blender], [food processor]

Commercial: The searcher has zeroed in on a solution and wants to compare options, ie. [blender reviews], [best blenders]

Transactional: The searcher has narrowed their hunt down to a few best options, and is on the precipice of purchase, ie. [affordable blenders], [blender cost]

Local (sub-category of transactional): The searcher plans to do or buy something locally, ie. [blenders in dallas]

Navigational (sub-category of transactional): The searcher wants to locate a specific website, ie. [Blendtec]

We left navigational intent out of our study because it’s brand specific and didn’t want to bias our data.

Our keyword set was a big list of retail products — from kitty pooper-scoopers to pricey speakers. We needed a straightforward way to imply search intent, so we added keyword modifiers to characterize each type of intent.

As always, different strokes for different folks: The modifiers you choose and the intent categories you look at may differ, but it’s important to map that all out before you get started.

2. Identifying the SERP features you really want

For our whitepaper research, we pretty much tracked every feature under the sun, but you certainly don’t have to.

You might already know which features you want to target, the ones you want to keep an eye on, or questions you want to answer. For example, are shopping boxes taking up enough space to warrant a PPC strategy?

In this blog post, we’re going to really focus-in on our most beloved SERP feature: featured snippets (called “answers” in STAT). And we’ll be using a sample project where we’re tracking 25,692 keywords against Amazon.com.

3. Using STAT’s segmentation tools

Setting up projects in STAT means making use of the segmentation tools. Here’s a quick rundown of what we used:

Standard tag: Best used to group your keywords into static themes — search intent, brand, product type, or modifier.

Dynamic tag: Like a smart playlist, automatically returns keywords that match certain criteria, like a given search volume, rank, or SERP feature appearance.

Data view: House any number of tags and show how those tags perform as a group.

Learn more about tags and data views in the STAT Knowledge Base.

Now, on to the main event…

1. Use top-level search intent to find SERP feature opportunities

To kick things off, we’ll identify the SERP features that appear at each level of search intent by creating tags.

Our first step is to filter our keywords and create standard tags for our search intent keywords (read more abou tfiltering keywords). Second, we create dynamic tags to track the appearance of specific SERP features within each search intent group. And our final step, to keep everything organized, is to place our tags in tidy little data views, according to search intent.

Here’s a peek at what that looks like in STAT:

What can we uncover?

Our standard tags (the blue tags) show how many keywords are in each search intent bucket: 2,940 commercial keywords. And our dynamic tags (the sunny yellow stars) show how many of those keywords return a SERP feature: 547 commercial keywords with a snippet.

This means we can quickly spot how much opportunity exists for each SERP feature by simply glancing at the tags. Boom!

By quickly crunching some numbers, we can see that snippets appear on 5 percent of our informational SERPs (27 out of 521), 19 percent of our commercial SERPs (547 out of 2,940), and 12 percent of our transactional SERPs (253 out of 2,058).

From this, we might conclude that optimizing our commercial intent keywords for featured snippets is the way to go since they appear to present the biggest opportunity. To confirm, let’s click on the commercial intent featured snippet tag to view the tag dashboard…

Voilà! There are loads of opportunities to gain a featured snippet.

Though, we should note that most of our keywords rank below where Google typically pulls the answer from. So, what we can see right away is that we need to make some serious ranking gains in order to stand a chance at grabbing those snippets.

2. Find SERP feature opportunities with intent modifiers

Now, let’s take a look at which SERP features appear most often for our different keyword modifiers.

To do this, we group our keywords by modifier and create a standard tag for each group. Then, we set up dynamic tags for our desired SERP features. Again, to keep track of all the things, we contained the tags in handy data views, grouped by search intent.

What can we uncover?

Because we saw that featured snippets appear most often for our commercial intent keywords, it’s time to drill on down and figure out precisely which modifiers within our commercial bucket are driving this trend.

Glancing quickly at the numbers in the tag titles in the image above, we can see that “best,” “reviews,” and “top” are responsible for the majority of the keywords that return a featured snippet:

212 out of 294 of our “best” keywords (72%)

109 out of 294 of our “reviews” keywords (37%)

170 out of 294 of our “top” keywords (59%)

This shows us where our efforts are best spent optimizing.

By clicking on the “best — featured snippets” tag, we’re magically transported into the dashboard. Here, we see that our average ranking could use some TLC.

There is a lot of opportunity to snag a snippet here, but we (actually, Amazon, who we’re tracking these keywords against) don’t seem to be capitalizing on that potential as much as we could. Let’s drill down further to see which snippets we already own.

We know we’ve got content that has won snippets, so we can use that as a guideline for the other keywords that we want to target.

3. See which pages are ranking best by search intent

In our blog post How Google dishes out content by search intent, we looked at what type of pages — category pages, product pages, reviews — appear most frequently at each stage of a searcher’s intent.

What we found was that Google loves category pages, which are the engine’s top choice for retail keywords across all levels of search intent. Product pages weren’t far behind.

By creating dynamic tags for URL markers, or portions of your URL that identify product pages versus category pages, and segmenting those by intent, you too can get all this glorious data. That’s exactly what we did for our retail keywords

What can we uncover?

Looking at the tags in the transactional page types data view, we can see that product pages are appearing far more frequently (526) than category pages (151).

When we glanced at the dashboard, we found that slightly more than half of the product pages were ranking on the first page (sah-weet!). That said, more than thirty percent appeared on page three and beyond. So despite the initial visual of “doing well”, there’s a lot of opportunity that Amazon could be capitalizing on.

We can also see this in the Daily Snapshot. In the image above, we compare category pages (left) to product pages (right), and we see that while there are less category pages ranking, the rank is significantly better. Amazon could take some of the lessons they’ve applied to their category pages to help their product pages out.

Wrapping it up

So what did we learn today?

Smart segmentation starts with a well-crafted list of keywords, grouped into tags, and housed in data views.

The more you segment, the more insights you’re gonna uncover.

Rely on the dashboards in STAT to flag opportunities and tell you what’s good, yo!

Want to see it all in action? Get a tailored walkthrough of STAT, here.

Or get your mitts on even more intent-based insights in our full whitepaper: Using search intent to connect with consumers.

Read on, readers!

More in our search intent series:

How SERP features respond to intent modifiers

How Google dishes out content by search intent

The basics of building an intent-based keyword list

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

from Blogger http://bit.ly/2S0EUR1 via IFTTT

[apsbicepstraining]

RTAG 1 TTOne day, you are going about your business when you catch sight of yourself wearing your favorite Hello Kitty t-shirt that ever attained you feel so free-spirited. Abruptly you think, “When did I turn into my Aunt Gladys? ” Many of us fall into the capture of wearing clothes that are too young for us, thinking that the alternative is to wear dowdy, frumpy robes. But here’s the rub: Ironically, when you dress too young, you often build yourself examine much older. And then there is the opposite capture of manufacturing yourself look older with out-of-date trends.( Please, please, say goodbye to the 1980 s Dynasty RTAG 12 TT Read more from Grandparents.com :Samsungs Gear S3 runs a little too big

Samsungs never shied away from running large-hearted. Big-hearted phones, big Tv, big-hearted watches. In fact, that was one of the essential characteristic for the first few generations of the Gear line, the first few of which were really more wrist-worn tablet than smartwatch.

Things thankfully mellowed out a bit last year with the purposes of applying S2, a more minimalist approaching to wrist-worn calculating that married cunning functionality with a refined OS and a designing that actually looked like an honest to goodness watch.

But 2016 celebrated a return to large-scale. Samsung was all about pushing happenings close to the breaking point this year, and in at least one conspicuous instance, going beyond. The Gear S3 marks a return to large-hearted. As ever, the companys jam-packed the watch with aspects which might feel like the latter are overflowing were the watch not so damned big-hearted in the first place. In numerous spaces, the new watch feels like the Galaxy Note strategy applied to the wrist albeit without all of the luggage that currently being become associated with that line.

Big time

This really needs to be mentioned right off the bat theres certainly no way around it the S3 is truly, really big. Truly, really. Sure, its not quite Galaxy Gear big, but its distractingly large-scale. Im roughly six hoofs towering and possess what I assume to be average-sized wrists for a male someone of my altitude, and the Gear S3 still seemed big-hearted. Just to the purposes of gossip, I requested two 54 coworkers to try it on, and the wearable appeared downright comical.

When the device first propelled at IFA, I questioned a rep about the thought process behind exhausting such a large watch, and he chalked it up to manner, quoting the notoriety of 42mm watches. Perhaps, but coupled with the added example penetration required for a smartwatchs electronics and battery, and youve got a invention that could serve to cut out a significant portion of the populace by sizing alone.

The S3 weighs in at 63 grams, owing in no small-minded place to its stainless steel casing. Thats around 13 grams heavier than the brand-new Apple watch( which was itself heavier than its precede ). And at 12.9 millimeters thick-skulled, its not really made for wearing with long sleeves. My sweater “ve managed” pulling over it( albeit with a visible protrusion ), but my button-up shirt had a bit more fus stirring it over.

And forget trying to sleep with the thing on. Its hard to understand why the company didnt, at the very least, give the watch in two different sizes. After all, its available in two different configurations. As such, Samsung has alienated all but a small fragment of the smartwatch-buying audience.

Big wheel keep on turning

The S3 Frontier also recognizes an aesthetic difference from its precede, with a steel speciman that takes on a more classic pattern that its sporty( some might have said plasticky) precede. Its certainly a classier and most versatile sound than many other smartwatches and fitness ensembles. With the right stripe, it can fit in comfortably in, suppose, country offices establish, which isnt something that can be said for many of the neon colored wearables out there.

The rubber strap that ships with the Frontier version is a marked step down from the design of the watch itself. Its designed to play alongside the watchs rugged focus, lending itself to outdoor outings and sweat-addled workouts. Of trend, the upside of the standardized 22 mm strap is that youll never miss for options on that front. Samsung actually teamed with a pair of decorators to develop cliques specifically for the watch but save yourself some currency and exactly pick up a regular old strap.

The S2s better facet has, thankfully returned. And its even better than before. The rotating bezel was a amazing addition to that last invention. At 1.3 inches, the exhibition isnt super small-minded, in so far as smartwatches move, but as with Apples offering, additional input is needed for immediately moving through screens.

The wheel does the job fantastically and even more intuitively than Apples option. This steel form is smooth, zipping through menu, though the small diction spread between bezel speciman seems a bit of a magnet for lint and other small-minded corpuscles that could necessitate the occasional bang of canned breeze for maintenance. The watch does sport a duo of buttons, as well back and ability which sit somewhat flush with the watch casing.

Saving face

The 1.3 -inch display is a touch larger than the S2s, but still doesnt extend the same soil as the Apple Watchs 1.65. At 278 ppi, its also a little bit less pixel dense, but its plenty bright and sharp-worded. Samsungs Tizen icons are clear and bright, even in daylight. The device boasts an Always On mode, to make it function more like an analog watch, though thats turned off by default and hidden under the Style menu in directs, for grounds the battery-life telling make clear.

Thats parcelled behind the most recent form of Gorilla Glass, making the watch shatter and scratch resistant. That, coupled with a big sword chassis, builds for an extremely rugged wearable. Its scheduled as MIL-STD-8 10 G Military Grade Rating, which protects it from stops up to 4.9 paws and IP68, which makes its water rating at up to five feet for 30 minutes. Its likewise protected from extreme temperatures, obliging the Frontier every bit as rugged as its mention implies.

Wearable hardware

The battery has been updated to 380 mAh, a marked hump over the Apple Watchs 273 mAh. The companionship paces life at around three days, but I was able to get closer to 2 day with Always On mode off owing likely in no small-minded area to the onboard LTE on the Frontier. Youll find yourself accusing it less often than the Apple Watch, but youre still not getting near fitness ensemble country here.

The LTE is a great option, the usefulness of which are dependent entirely upon how you interact with your watch. If you have your phone on you all or most of the time, its perhaps not worth the additional cost, which breaks down to an extra $10 a month in addition to an existing data plan or $40 for a brand new one on AT& T. If, however, youre looking to the wrist as an interim liberation from the watch for, allege, long cross-country leads, its a terrific feature.

Either way, its a solid addition to the smartwatch that apparently already has everything, giving speedy data directly to the watch without needing to be tethered to a handset at all times. And theres ever the bonus ability of using the built-in loudspeaker to reach wrist-based telephone call, lastly fulfilling the long-awaited Dick Tracy promise.

The S3 too returns built-in GPS to the watch( previously only available on the specialty 3G version of the S2 ), another big bonus for the wearables outdoorsy functionality, and brings a lot to the table on the fitness tracking figurehead, in particular for hikers and athletes who like to go long distance.

Tizen time

Among interesting thing, Samsungs got the chose assistance of several generations of smartwatches under its belt. The fellowship swopped from Android to Tizen between the Galaxy Gear and Gear 2, and genuinely affect its stride with last years S2. The application ordeal is smooth and customizable holding down on an icon, for example, lets you customize and re-order screens.

The app selection is still limited compared to the rivalry, but youve got some key ones here, including Uber and Flipboard, along with the most recent( and important) addition of Spotify. You can add a hand-picked number of apps immediately onto the watch or flip over to the phone to view more and get the full app store experience.

For the most part, I located my engagements is restricted to Samsungs own apps; the company has done a good job to be built its own ecosystem. The companys S Health has become fairly robust over the last few generations, building the best possible use of onboard sensors like GPS and heart rate, and Samsung Pay accompanies added utility of paying by searching your wrist near a card reader.

Final Frontier

Samsungs had a few generations more than much of its competition to refine its smartwatch know-how. Last year the company eventually hit upon a winning formula with the S2, a great combining of motif, functionality and software refinement.

And while the S2 is getting a good number of software upgrades to bring it up to accelerate, the $350 S3 Frontier offers some key hardware bumps over its precede. Those largely feel iterative, but welcome. The new size, on the other mitt, is a big misfire for Samsung. The smartwatch infinite is already a marginalized one, and making a massive machine like the S3 further curbs the make from too many wrists.

The post RTAG 1 TTOne day, you are going about your business when you catch sight of yourself wearing your favorite Hello Kitty t-shirt that ever attained you feel so free-spirited. Abruptly you think, “When did I turn into my Aunt Gladys? ” Many of us fall into the capture of wearing clothes that are too young for us, thinking that the alternative is to wear dowdy, frumpy robes. But here’s the rub: Ironically, when you dress too young, you often build yourself examine much older. And then there is the opposite capture of manufacturing yourself look older with out-of-date trends.( Please, please, say goodbye to the 1980 s Dynasty RTAG 12 TT Read more from Grandparents.com :Samsungs Gear S3 runs a little too big appeared first on apsbicepstraining.com.

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[smoothshift]

Japan Car Scene as a Tourist Pt 2 via /r/cars

Japan Car Scene as a Tourist Pt 2

First Part

Gallery <====== CLICK FOR TL;DR PICS

Instagram

Continued...

So a little further from harajuku and in shinjuku is a park were the greasers hangout on the weekends and dance. Also seemed fitting that i saw an oldskool porsche. We head back home, and doing so we pass shibuya crossing (the one from tokyo drift). Were i saw an dodge magnum on white lip rims. Again, not expecting that at all. So we head to the hotel, they crash but i'm still to amped, and go for midnight stroll. I look at the parking garages near the hotel to check out if i can see anything cool. I get lucky and find a Bently contiential, and another Porsche futher down.

Morning comes, and i'm the first to rise (again). I go for a walk around the neighborhood to get a feeling of urban living in the morning. I sneak around back of some hotels, and find a Ducati hidden away behind some bikes (another main transportation locally). Walk some more, and run into two Mercades parked as if they were in a photoshoot. I walk around some more and i run into what i feel is the best example of Japan. A small Kei car, parked next a vending machine with beer bottles, with a small establishment pulling it all together...oh and of course the bike. I walk a little further and start winding back to the hotel as my friends have woken up. I run into this bike, which i have no idea what it is, but notice that they take better care of the cars vs the motorcycles/bikes.

In the interest of time, i'm going to shorten a bit of my trip (mostly because it involved not many new cars). Back at night at shibuya crossing, it's the best place to car watch on a weekday if you don't have a car. I got to witness this gorgeous bike which unfortunately it was too dark for me to get a great picture of. Then this oldskool beetle rolls through. Followed by my all time dream car, in the color i adore...THE NISSAN SILVIA S15! This guy looks like he drifted it a couple of times, and to add insult to injury, i got this pic because it broke down, and i asked him if it was okay for me to take a pic while he waited for his friend to pick him up. A couple of bikes zoomed by, I don't know much about bikes so i can't tell you what they were. BUT one of the other stranger things i saw, was a modified (lowered) toyota prius. We don't really modify priuses in the states so it was interesting to see they will modify any car (this wasn't the only one btw).

Next we head to Akihabara. THIS was a big deal for me, being a video game and anime type person. But, we spent most of the day running from building to building while shopping. Btw, japan, seriously...SO MUCH PORN. Like 5 buildings had 3-5 floors dedicated to whatever you are into. Now the other things about akihabara is that their is this store/mall called the UDX building. A well know area for a certain sub car culture called "Itasha", likes to park their cars on the basement level in their parking garage on the weekends to show them off (think tokyo drift). Unfortunately this was the weekday. So i wasn't expecting much. We walk through electric town anyway and i spot this pretty dope Mazda RX8 with a lite bar, which i thought was neat. So we head to Akihabara UDX Parking garage. I get nervous because it looks like a regular department store. We get in and there are two basement levels, i take a chance and we head to the first floor. The doors open and i walk around the corner, just regular cars...then, there it is...godzillla itself, Nissan GTR R35 Nismo! Then, Bmw 7 Series (alpina?), Rolls Royce Ghost, Audi R8, Ferrari Maranello, another Ferrari 488, Ferrari Dino, Rolls Royce Phantom, Vintage Rolls Royce, Maserati Levante, Rolls Royce Wraith, Mercades G50, then this cute as a button Suzuki Hustler!(seriously I want one). It didn't stop there, we go to the other floor, and there was a Willys Jeep, Mazda RX8, Whatever THIS thing is, Nissan Skyline R32 Hugging work wheels (yum!), and this which i feel is based of an old toyota or acura.

So i'm falling in love with each isle i walk down, then i hear some japanese, and walk around the corner. I found what i was looking for. Itasha cars. Their was some guys there just shooting the breeze around their modified and heavy decaled cars. One was a lightly modified Subaru Impreza, and he kept his anime on the inside for the most part. Others had more race inspired livery still with anime influence. But while scooting over to take a shot of the cars i noticed something out of the corner of my eye. My first Lamborghini Aventador. This car was number 2 on my bucket list of cars to see before i die (veyron is number 1). So i had died and gone to heaven. Not to make the other guys feel unimportant because truly their cars are just as cool to me, i went back and shot some more. Another Subaru Impreza, Mitsubishi Lancer Evo 2, Mitsubishi Lancer Evo 8, and another Evo showed up and parked for display. One of my favorites was THIS evo, with it's decals on full blast. The guys were REALLY cool, and let me take pictures of their cars. Even though we had a language barrier we still knew we all liked cool cars. They even popped their hoods, for us. I took THIS, pic to show the difference in style from the exotic to the itasha tuner. We bowed and thanked them for allowing us to take pictures. VERY cool experience. We keep walking through the garage, and run into a Toyota Supra, Jaguar F-Type, and then another granddaddy. The Nissan GTR R34. We walked a bit more an ran into a Toyota Celica, whatever THIS is, whatever THIS, this Honda NM4(I had to look it up), Mitsubishi i-Miev, another GTR, Ferrari Scaglietti, and last a super smooth GTR. That was it, then we left to go home before the trains stop.

Okay at this point, I was thinking of starting a new thread for mobile users, but lets keep this ball rolling

The next day we go to Asakusa and ran into this biker which was super cool. Then into this Lexus(sorry i can't tell which one), right before this Porsche. Walked some more, then saw this Suzuki Ignis which again i think is cool. Skyline R32(honestly, i forget what the original models are called i think they are prince or princess). We took the boat to Odaiba, which was amazing. Straight off the boat we see this oldskool bug, then this Porsche, rolls by it. We start walking towards palette town to hit toyota megaweb, which is a display location for new toyota models and a museum for older cars of all makes. But first, we saw this PIZZA MAKING ROBOT!, yes a pizza making robot!

We make it tokyo Mega web and first thing we see is a FRS Police Edition. They have a couple of race spec models, including a race spec LF-A, and RC-F. They also had many concept cars. Now, right now, you can't talk about toyota without talking about the "new supra", the FT-1. They had display games and an actual version of the car on the floor. They also had some models we don't get here in the states (at least not in their original forms), and if you had your international drivers license you could actually test drive them there.

Next we went to the museum, and seen a bunch of oldskool cars (most which i don't know what they are). Corvette, Mazda RX3, fairlady Z, and Toyota Celica. Obviously while we were in odaiba we had to check out what was left of the giant Gundam statue as they take it down. Next we head to Yokohama, and right away see an oldskool Skyline GTR. Another car on my bucket list. Then saw a Lotus Elise (i think?). Yokohama is suppose to have a great racing hertiage, and tracks, unfortunately we couldn't get out to any and didn't see much cars.

Next we head to Kyoto. Now Kyoto isn't know for cars, it's mostly known for it's old hertiage way of doing things, and vintage Japanese culture. Lots of kimonos, slower pace and machiya houses. Well, color me shocked when i see this beautiful Silvia S15. Best part it was around the corner of our airbnb so i got to see it almost everyday while there. Then when i walked a little further there was a dealership, and another Silvia, this time an S13. Most of the vehicles in Kyoto were noticeably everyday drivers or work cars, like this nissan pickup truck. But with that said, as always you will see some sporter cars like this Jag or Skyline. Kyoto like most of Japan is big on taxing it's space, so most of the houses are build thin and high. Smaller foot print but 2 and 3 story houses. But, they still love their cars, and will hide a GTR no problem.

Next there was a huge flea market going on in kyoto (highly suggest you go if you want a kimono), and upon arrival, again another american car i didn't expect to see, a mustang! Around the corner from there, we find what i consider one of the most "powerful" japanese import cars we get in the US, a toyota Supra! We head to Osaka, which is for the most part known as the "food spot" and also a great night time hangout. Lots of great food, and even thought it was crowded a great place to visit. They have obamas chicken and waffles below the drunken clam karaoke bar in Dotonbori. Seeing as it seemed like a party neighborhood i wasn't surprised to see this lexus with red on red. The next day we went to Nara, which is known for it's largest bronze buddha statue, and deer that roam freely. But, no cars...(still recommend as it's an experience).

Next we head to Himeji (known for it's castle thats be featured in multiple movies, and is a hertiage site), and then Kobe (known for it's beef). Himeji you pretty much see the castle from the station, so we didn't get to explore and see the cars. However Kobe.... Kobe is/was a port city and being so has a interesting mix of cultures and ideas. Yes i had kobe beef and it was amazing, but i found the whole city (what little i visited) amazing. Imagine my surprise when i found a little small with a shop that sold native american clothing. YES, native AMERICAN. Blew my mind. I also seen a MR2 Spyder, and dropped Civic.

That's it for the most part. I didn't go into detail as i probably could've about the drinking, the touts offering sexual favors, or the bullet trains, because i wanted to keep it about the cars and culture. I know my writing is horrible, but really i just wanted to share this experience and i feel like you fellow "car" guys/gals will get it hopefully.

[viralhottopics]

Were on the Brink of a Revolution in Crazy-Smart Digital Assistants

Heres a quick story youve probably heard before, followed by one you probably havent. In 1979 a young Steve Jobs paid a visit to Xerox PARC, the legendary R&D lab in Palo Alto, California, and witnessed a demonstration of something now called the graphical user interface. An engineer from PARC used a prototype mouse to navigate a computer screen studded with icons, drop-down menus, and windows that overlapped each other like sheets of paper on a desktop. It was unlike anything Jobs had seen before, and he was beside himself. Within 10 minutes, he would later say, it was so obvious that every computer would work this way someday.

As legend has it, Jobs raced back to Apple and commanded a team to set about replicating and improving on what he had just seen at PARC. And with that, personal computing sprinted off in the direction it has been traveling for the past 40 years, from the first Macintosh all the way up to the iPhone. This visual mode of computing ended the tyranny of the command linethe demanding, text-heavy interface that was dominant at the timeand brought us into a world where vastly more people could use computers. They could just point, click, and drag.

In the not-so-distant future, though, we may look back at this as the wrong PARC-related creation myth to get excited about. At the time of Jobs visit, a separate team at PARC was working on a completely different model of human-computer interaction, today called the conversational user interface. These scientists envisioned a world, probably decades away, in which computers would be so powerful that requiring users to memorize a special set of commands or workflows for each action and device would be impractical. They imagined that we would instead work collaboratively with our computers, engaging in a running back-and-forth dialog to get things done. The interface would be ordinary human language.

Pipe Down, Jarvis

For decades, the talking tech in movies has eclipsed anything weve been able to build in the real world. Thats finally starting to change.

Computer from Star Trek | A kind of proto-Google with a voice, the Enterprises computer provides status updates, calculations and tea, Earl Grey, hot.

HAL 9000 from 2001: A Space Odyssey | HAL, the psychotic AI with an FM-DJ voice, is able to control every last detail of a mission to Jupiter.

KITT from Knight Rider | Michael Knights in-dash AI partner is sarcastic, indestructible, and always ready to get Knight out of a jam.

Jarvis from Iron Man | You never see Jarvis, but his diagnostics, worried nagging, and instant calculations are crucial to Iron Mans superheroness.

Samantha from Her | She starts by reading his emailand eventually becomes much more than a helpful assistant in Theodore Twomblys ear.

One of the scientists in that group was a guy named Ron Kaplan, who today is a stout, soft-spoken man with a gray goatee and thinning hair. Kaplan is equal parts linguist, psychologist, and computer scientista guy as likely to invoke Chomskys theories about the construction of language as he is Moores law. He says that his team got pretty far in sketching out one crucial component of a working conversational user interface back in the 70s; they rigged up a system that allowed you to book flights by exchanging typed messages with a computer in normal, unencumbered English. But the technology just wasnt there to make the system work on a large scale. It wouldve cost, I dont know, a million dollars a user, he says. They needed faster, more distributed processing and smarter, more efficient computers. Kaplan thought it would take about 15 years.

Forty years later, Kaplan says, were ready. And so is the rest of the world, it turns out.

Today, Kaplan is a vice president and distinguished scientist at Nuance Communications, which has become probably the biggest player in the voice interface business: It powers Fords in-car Sync system, was critical in Siris development, and has partnerships across nearly every industry. But Nuance finds itself in a crowded marketplace these days. Nearly every major tech companyfrom Amazon to Intel to Microsoft to Googleis chasing the sort of conversational user interface that Kaplan and his colleagues at PARC imagined decades ago. Dozens of startups are in the game too. All are scrambling to come out on top in the midst of a powerful shift under way in our relationship with technology. One day soon, these companies believe, you will talk to your gadgets the way you talk to your friends. And your gadgets will talk back. They will be able to hear what you say and figure out what you mean.

If youre already steeped in todays technology, these new tools will extend the reach of your digital life into places and situations where the graphical user interface cannot safely, pleasantly, or politely go. And the increasingly conversational nature of your back-and-forth with your devices will make your relationship to technology even more intimate, more loyal, more personal.

But the biggest effect of this shift will be felt well outside Silicon Valleys core audience. What Steve Jobs saw in the graphical user interface back in 1979 was a way to expand the popular market for computers. But even the GUI still left huge numbers of people outside the light of the electronic campfire. As elegant and efficient as it is, the GUI still requires humans to learn a computers language. Now computers are finally learning how to speak ours. In the bargain, hundreds of millions more people could gain newfound access to tech.

Voice interfaces have been around for years, but lets face it: Thus far, theyve been pretty dumb. We need not dwell on the indignities of automated phone trees (If youre calling to make a payment, say payment). Even our more sophisticated voice interfaces have relied on speech but somehow missed the power of language. Ask Google Now for the population of New York City and it obliges. Ask for the location of the Empire State Building: good to go. But go one logical step further and ask for the population of the city that contains the Empire State Building and it falters. Push Siri too hard and the assistant just refers you to a Google search. Anyone reared on scenes of Captain Kirk talking to the Enterprises computer or of Tony Stark bantering with Jarvis cant help but be perpetually disappointed.

Ask around Silicon Valley these days, though, and you hear the same refrain over and over: Its different now.

One hot day in early June, Keyvan Mohajer, CEO of SoundHound, shows me a prototype of a new app that his company has been working on in secret for almost 10 years. You may recognize SoundHound as the name of a popular music-recognition appthe one that can identify a tune for you if you hum it into your phone. It turns out that app was largely just a way of fueling Mohajers real dream: to create the best voice-based artificial-intelligence assistant in the world.

The prototype is called Hound, and its pretty incredible. Holding a black Nexus 5 smartphone, Mohajer taps a blue and white microphone icon and begins asking questions. He starts simply, asking for the time in Berlin and the population of Japan. Basic search-result stufffollowed by a twist: What is the distance between them? The app understands the context and fires back, About 5,536 miles.

Mohajer rattles off a barrage of questions, and the app answers every one. Correctly.

Then Mohajer gets rolling, smiling as he rattles off a barrage of questions that keep escalating in complexity. He asks Hound to calculate the monthly mortgage payments on a million-dollar home, and the app immediately asks him for the interest rate and the term of the loan before dishing out its answer: $4,270.84.

What is the population of the capital of the country in which the Space Needle is located? he asks. Hound figures out that Mohajer is fishing for the population of Washington, DC, faster than I do and spits out the correct answer in its rapid-fire robotic voice. What is the population and capital for Japan and China, and their areas in square miles and square kilometers? And also tell me how many people live in India, and what is the area code for Germany, France, and Italy? Mohajer would keep on adding questions, but he runs out of breath. Ill spare you the minute-long response, but Hound answers every question. Correctly.

Hound, which is now in beta, is probably the fastest and most versatile voice recognition system unveiled thus far. It has an edge for now because it can do speech recognition and natural language processing simultaneously. But really, its only a matter of time before other systems catch up.

After all, the underlying ingredientswhat Kaplan calls the gating technologies necessary for a strong conversational interfaceare all pretty much available now to whoevers buying. Its a classic story of technological convergence: Advances in processing power, speech recognition, mobile connectivity, cloud computing, and neural networks have all surged to a critical mass at roughly the same time. These tools are finally good enough, cheap enough, and accessible enough to make the conversational interface realand ubiquitous.

But its not just that conversational technology is finally possible to build. Theres also a growing need for it. As more devices come online, particularly those without screensyour light fixtures, your smoke alarmwe need a way to interact with them that doesnt require buttons, menus, and icons.

When I started using Alexa late last year, I discovered it could tell me the weather, answer basic factual questions, create shopping lists that later appear in text on my smartphone, play music on commandnothing too transcendent. But Alexa quickly grew smarter and better. It got familiar with my voice, learned funnier jokes, and started being able to run multiple timers simultaneously (which is pretty handy when your cooking gets a little ambitious). In just the seven months between its initial beta launch and its public release in 2015, Alexa went from cute but infuriating to genuinely, consistently useful. I got to know it, and it got to know me.

This gets at a deeper truth about conversational tech: You only discover its capabilities in the course of a personal relationship with it. The big players in the industry all realize this and are trying to give their assistants the right balance of personality, charm, and respectful distanceto make them, in short, likable. In developing Cortana, for instance, Microsoft brought in the videogame studio behind Halowhich inspired the name Cortana in the first placeto turn a disembodied voice into a kind of character. That wittiness and that toughness come through, says Mike Calcagno, director of Cortanas engineering team. And they seem to have had the desired effect: Even in its early days, when Cortana was unreliable, unhelpful, and dumb, people got attached to it.

Theres a strategic reason for this charm offensive. In their research, Microsoft, Nuance, and others have all come to the same conclusion: A great conversational agent is only fully useful when its everywhere, when it can get to know you in multiple contextslearning your habits, your likes and dislikes, your routine and schedule. The way to get there is to have your AI colonize as many apps and devices as possible.

To that end, Amazon, Google, Microsoft, Nuance, and SoundHound are all offering their conversational platform technology to developers everywhere. The companies know that you are liable to stick with the conversational agent that knows you best. So get ready to meet some new disembodied voices. Once you pick one, you might never break up.

David Pierce (@piercedavid) is a senior writer at WIRED.

Read more: http://bit.ly/2jcdA2u

from Were on the Brink of a Revolution in Crazy-Smart Digital Assistants

[we-johnnygonzalez-blog]

A Guide to Setting Up Your Very Own Search Intent Projects

Posted by TheMozTeam

This post was originally published on the STAT blog.

Whether you’re tracking thousands or millions of keywords, if you expect to extract deep insights and trends just by looking at your keywords from a high-level, you’re not getting the full story.

Smart segmentation is key to making sense of your data. And you’re probably already applying this outside of STAT. So now, we’re going to show you how to do it in STAT to uncover boatloads of insights that will help you make super data-driven decisions.

To show you what we mean, let’s take a look at a few ways we can set up a search intent project to uncover the kinds of insights we shared in our whitepaper, Using search intent to connect with consumers.

Before we jump in, there are a few things you should have down pat:

1. Picking a search intent that works for you

Search intent is the motivating force behind search and it can be:

Informational: The searcher has identified a need and is looking for information on the best solution, ie. [blender], [food processor]

Commercial: The searcher has zeroed in on a solution and wants to compare options, ie. [blender reviews], [best blenders]

Transactional: The searcher has narrowed their hunt down to a few best options, and is on the precipice of purchase, ie. [affordable blenders], [blender cost]

Local (sub-category of transactional): The searcher plans to do or buy something locally, ie. [blenders in dallas]

Navigational (sub-category of transactional): The searcher wants to locate a specific website, ie. [Blendtec]

We left navigational intent out of our study because it’s brand specific and didn’t want to bias our data.

Our keyword set was a big list of retail products — from kitty pooper-scoopers to pricey speakers. We needed a straightforward way to imply search intent, so we added keyword modifiers to characterize each type of intent.

As always, different strokes for different folks: The modifiers you choose and the intent categories you look at may differ, but it’s important to map that all out before you get started.

2. Identifying the SERP features you really want

For our whitepaper research, we pretty much tracked every feature under the sun, but you certainly don’t have to.

You might already know which features you want to target, the ones you want to keep an eye on, or questions you want to answer. For example, are shopping boxes taking up enough space to warrant a PPC strategy?

In this blog post, we’re going to really focus-in on our most beloved SERP feature: featured snippets (called “answers” in STAT). And we’ll be using a sample project where we’re tracking 25,692 keywords against Amazon.com.

3. Using STAT’s segmentation tools

Setting up projects in STAT means making use of the segmentation tools. Here’s a quick rundown of what we used:

Standard tag: Best used to group your keywords into static themes — search intent, brand, product type, or modifier.

Dynamic tag: Like a smart playlist, automatically returns keywords that match certain criteria, like a given search volume, rank, or SERP feature appearance.

Data view: House any number of tags and show how those tags perform as a group.

Learn more about tags and data views in the STAT Knowledge Base.

Now, on to the main event…

1. Use top-level search intent to find SERP feature opportunities

To kick things off, we’ll identify the SERP features that appear at each level of search intent by creating tags.

Our first step is to filter our keywords and create standard tags for our search intent keywords (read more abou tfiltering keywords). Second, we create dynamic tags to track the appearance of specific SERP features within each search intent group. And our final step, to keep everything organized, is to place our tags in tidy little data views, according to search intent.

Here’s a peek at what that looks like in STAT:

What can we uncover?

Our standard tags (the blue tags) show how many keywords are in each search intent bucket: 2,940 commercial keywords. And our dynamic tags (the sunny yellow stars) show how many of those keywords return a SERP feature: 547 commercial keywords with a snippet.

This means we can quickly spot how much opportunity exists for each SERP feature by simply glancing at the tags. Boom!

By quickly crunching some numbers, we can see that snippets appear on 5 percent of our informational SERPs (27 out of 521), 19 percent of our commercial SERPs (547 out of 2,940), and 12 percent of our transactional SERPs (253 out of 2,058).

From this, we might conclude that optimizing our commercial intent keywords for featured snippets is the way to go since they appear to present the biggest opportunity. To confirm, let’s click on the commercial intent featured snippet tag to view the tag dashboard…

Voilà! There are loads of opportunities to gain a featured snippet.

Though, we should note that most of our keywords rank below where Google typically pulls the answer from. So, what we can see right away is that we need to make some serious ranking gains in order to stand a chance at grabbing those snippets.

2. Find SERP feature opportunities with intent modifiers

Now, let’s take a look at which SERP features appear most often for our different keyword modifiers.

To do this, we group our keywords by modifier and create a standard tag for each group. Then, we set up dynamic tags for our desired SERP features. Again, to keep track of all the things, we contained the tags in handy data views, grouped by search intent.

What can we uncover?

Because we saw that featured snippets appear most often for our commercial intent keywords, it’s time to drill on down and figure out precisely which modifiers within our commercial bucket are driving this trend.

Glancing quickly at the numbers in the tag titles in the image above, we can see that “best,” “reviews,” and “top” are responsible for the majority of the keywords that return a featured snippet:

212 out of 294 of our “best” keywords (72%)

109 out of 294 of our “reviews” keywords (37%)

170 out of 294 of our “top” keywords (59%)

This shows us where our efforts are best spent optimizing.

By clicking on the “best — featured snippets” tag, we’re magically transported into the dashboard. Here, we see that our average ranking could use some TLC.

There is a lot of opportunity to snag a snippet here, but we (actually, Amazon, who we’re tracking these keywords against) don’t seem to be capitalizing on that potential as much as we could. Let’s drill down further to see which snippets we already own.

We know we’ve got content that has won snippets, so we can use that as a guideline for the other keywords that we want to target.

3. See which pages are ranking best by search intent

In our blog post How Google dishes out content by search intent, we looked at what type of pages — category pages, product pages, reviews — appear most frequently at each stage of a searcher’s intent.

What we found was that Google loves category pages, which are the engine’s top choice for retail keywords across all levels of search intent. Product pages weren’t far behind.

By creating dynamic tags for URL markers, or portions of your URL that identify product pages versus category pages, and segmenting those by intent, you too can get all this glorious data. That’s exactly what we did for our retail keywords

What can we uncover?

Looking at the tags in the transactional page types data view, we can see that product pages are appearing far more frequently (526) than category pages (151).

When we glanced at the dashboard, we found that slightly more than half of the product pages were ranking on the first page (sah-weet!). That said, more than thirty percent appeared on page three and beyond. So despite the initial visual of “doing well”, there’s a lot of opportunity that Amazon could be capitalizing on.

We can also see this in the Daily Snapshot. In the image above, we compare category pages (left) to product pages (right), and we see that while there are less category pages ranking, the rank is significantly better. Amazon could take some of the lessons they’ve applied to their category pages to help their product pages out.

Wrapping it up

So what did we learn today?

Smart segmentation starts with a well-crafted list of keywords, grouped into tags, and housed in data views.

The more you segment, the more insights you’re gonna uncover.

Rely on the dashboards in STAT to flag opportunities and tell you what’s good, yo!

Want to see it all in action? Get a tailored walkthrough of STAT, here.

Or get your mitts on even more intent-based insights in our full whitepaper: Using search intent to connect with consumers.

Read on, readers!

More in our search intent series:

How SERP features respond to intent modifiers

How Google dishes out content by search intent

The basics of building an intent-based keyword list

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[we-johnnygonzalez-blog]

A Guide to Setting Up Your Very Own Search Intent Projects

Posted by TheMozTeam

This post was originally published on the STAT blog.

Whether you’re tracking thousands or millions of keywords, if you expect to extract deep insights and trends just by looking at your keywords from a high-level, you’re not getting the full story.

Smart segmentation is key to making sense of your data. And you’re probably already applying this outside of STAT. So now, we’re going to show you how to do it in STAT to uncover boatloads of insights that will help you make super data-driven decisions.

To show you what we mean, let’s take a look at a few ways we can set up a search intent project to uncover the kinds of insights we shared in our whitepaper, Using search intent to connect with consumers.

Before we jump in, there are a few things you should have down pat:

1. Picking a search intent that works for you

Search intent is the motivating force behind search and it can be:

Informational: The searcher has identified a need and is looking for information on the best solution, ie. [blender], [food processor]

Commercial: The searcher has zeroed in on a solution and wants to compare options, ie. [blender reviews], [best blenders]

Transactional: The searcher has narrowed their hunt down to a few best options, and is on the precipice of purchase, ie. [affordable blenders], [blender cost]

Local (sub-category of transactional): The searcher plans to do or buy something locally, ie. [blenders in dallas]

Navigational (sub-category of transactional): The searcher wants to locate a specific website, ie. [Blendtec]

We left navigational intent out of our study because it’s brand specific and didn’t want to bias our data.

Our keyword set was a big list of retail products — from kitty pooper-scoopers to pricey speakers. We needed a straightforward way to imply search intent, so we added keyword modifiers to characterize each type of intent.

As always, different strokes for different folks: The modifiers you choose and the intent categories you look at may differ, but it’s important to map that all out before you get started.

2. Identifying the SERP features you really want

For our whitepaper research, we pretty much tracked every feature under the sun, but you certainly don’t have to.

You might already know which features you want to target, the ones you want to keep an eye on, or questions you want to answer. For example, are shopping boxes taking up enough space to warrant a PPC strategy?

In this blog post, we’re going to really focus-in on our most beloved SERP feature: featured snippets (called “answers” in STAT). And we’ll be using a sample project where we’re tracking 25,692 keywords against Amazon.com.

3. Using STAT’s segmentation tools

Setting up projects in STAT means making use of the segmentation tools. Here’s a quick rundown of what we used:

Standard tag: Best used to group your keywords into static themes — search intent, brand, product type, or modifier.

Dynamic tag: Like a smart playlist, automatically returns keywords that match certain criteria, like a given search volume, rank, or SERP feature appearance.

Data view: House any number of tags and show how those tags perform as a group.

Learn more about tags and data views in the STAT Knowledge Base.

Now, on to the main event…

1. Use top-level search intent to find SERP feature opportunities

To kick things off, we’ll identify the SERP features that appear at each level of search intent by creating tags.

Our first step is to filter our keywords and create standard tags for our search intent keywords (read more abou tfiltering keywords). Second, we create dynamic tags to track the appearance of specific SERP features within each search intent group. And our final step, to keep everything organized, is to place our tags in tidy little data views, according to search intent.

Here’s a peek at what that looks like in STAT:

What can we uncover?

Our standard tags (the blue tags) show how many keywords are in each search intent bucket: 2,940 commercial keywords. And our dynamic tags (the sunny yellow stars) show how many of those keywords return a SERP feature: 547 commercial keywords with a snippet.

This means we can quickly spot how much opportunity exists for each SERP feature by simply glancing at the tags. Boom!

By quickly crunching some numbers, we can see that snippets appear on 5 percent of our informational SERPs (27 out of 521), 19 percent of our commercial SERPs (547 out of 2,940), and 12 percent of our transactional SERPs (253 out of 2,058).

From this, we might conclude that optimizing our commercial intent keywords for featured snippets is the way to go since they appear to present the biggest opportunity. To confirm, let’s click on the commercial intent featured snippet tag to view the tag dashboard…

Voilà! There are loads of opportunities to gain a featured snippet.

Though, we should note that most of our keywords rank below where Google typically pulls the answer from. So, what we can see right away is that we need to make some serious ranking gains in order to stand a chance at grabbing those snippets.

2. Find SERP feature opportunities with intent modifiers

Now, let’s take a look at which SERP features appear most often for our different keyword modifiers.

To do this, we group our keywords by modifier and create a standard tag for each group. Then, we set up dynamic tags for our desired SERP features. Again, to keep track of all the things, we contained the tags in handy data views, grouped by search intent.

What can we uncover?

Because we saw that featured snippets appear most often for our commercial intent keywords, it’s time to drill on down and figure out precisely which modifiers within our commercial bucket are driving this trend.

Glancing quickly at the numbers in the tag titles in the image above, we can see that “best,” “reviews,” and “top” are responsible for the majority of the keywords that return a featured snippet:

212 out of 294 of our “best” keywords (72%)

109 out of 294 of our “reviews” keywords (37%)

170 out of 294 of our “top” keywords (59%)

This shows us where our efforts are best spent optimizing.

By clicking on the “best — featured snippets” tag, we’re magically transported into the dashboard. Here, we see that our average ranking could use some TLC.

There is a lot of opportunity to snag a snippet here, but we (actually, Amazon, who we’re tracking these keywords against) don’t seem to be capitalizing on that potential as much as we could. Let’s drill down further to see which snippets we already own.

We know we’ve got content that has won snippets, so we can use that as a guideline for the other keywords that we want to target.

3. See which pages are ranking best by search intent

In our blog post How Google dishes out content by search intent, we looked at what type of pages — category pages, product pages, reviews — appear most frequently at each stage of a searcher’s intent.

What we found was that Google loves category pages, which are the engine’s top choice for retail keywords across all levels of search intent. Product pages weren’t far behind.

By creating dynamic tags for URL markers, or portions of your URL that identify product pages versus category pages, and segmenting those by intent, you too can get all this glorious data. That’s exactly what we did for our retail keywords

What can we uncover?

Looking at the tags in the transactional page types data view, we can see that product pages are appearing far more frequently (526) than category pages (151).

When we glanced at the dashboard, we found that slightly more than half of the product pages were ranking on the first page (sah-weet!). That said, more than thirty percent appeared on page three and beyond. So despite the initial visual of “doing well”, there’s a lot of opportunity that Amazon could be capitalizing on.

We can also see this in the Daily Snapshot. In the image above, we compare category pages (left) to product pages (right), and we see that while there are less category pages ranking, the rank is significantly better. Amazon could take some of the lessons they’ve applied to their category pages to help their product pages out.

Wrapping it up

So what did we learn today?

Smart segmentation starts with a well-crafted list of keywords, grouped into tags, and housed in data views.

The more you segment, the more insights you’re gonna uncover.

Rely on the dashboards in STAT to flag opportunities and tell you what’s good, yo!

Want to see it all in action? Get a tailored walkthrough of STAT, here.

Or get your mitts on even more intent-based insights in our full whitepaper: Using search intent to connect with consumers.

Read on, readers!

More in our search intent series:

How SERP features respond to intent modifiers

How Google dishes out content by search intent

The basics of building an intent-based keyword list

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[we-johnnygonzalez-blog]

A Guide to Setting Up Your Very Own Search Intent Projects

Posted by TheMozTeam

This post was originally published on the STAT blog.

Whether you’re tracking thousands or millions of keywords, if you expect to extract deep insights and trends just by looking at your keywords from a high-level, you’re not getting the full story.

Smart segmentation is key to making sense of your data. And you’re probably already applying this outside of STAT. So now, we’re going to show you how to do it in STAT to uncover boatloads of insights that will help you make super data-driven decisions.

To show you what we mean, let’s take a look at a few ways we can set up a search intent project to uncover the kinds of insights we shared in our whitepaper, Using search intent to connect with consumers.

Before we jump in, there are a few things you should have down pat:

1. Picking a search intent that works for you

Search intent is the motivating force behind search and it can be:

Informational: The searcher has identified a need and is looking for information on the best solution, ie. [blender], [food processor]

Commercial: The searcher has zeroed in on a solution and wants to compare options, ie. [blender reviews], [best blenders]

Transactional: The searcher has narrowed their hunt down to a few best options, and is on the precipice of purchase, ie. [affordable blenders], [blender cost]

Local (sub-category of transactional): The searcher plans to do or buy something locally, ie. [blenders in dallas]

Navigational (sub-category of transactional): The searcher wants to locate a specific website, ie. [Blendtec]

We left navigational intent out of our study because it’s brand specific and didn’t want to bias our data.

Our keyword set was a big list of retail products — from kitty pooper-scoopers to pricey speakers. We needed a straightforward way to imply search intent, so we added keyword modifiers to characterize each type of intent.

As always, different strokes for different folks: The modifiers you choose and the intent categories you look at may differ, but it’s important to map that all out before you get started.

2. Identifying the SERP features you really want

For our whitepaper research, we pretty much tracked every feature under the sun, but you certainly don’t have to.

You might already know which features you want to target, the ones you want to keep an eye on, or questions you want to answer. For example, are shopping boxes taking up enough space to warrant a PPC strategy?

In this blog post, we’re going to really focus-in on our most beloved SERP feature: featured snippets (called “answers” in STAT). And we’ll be using a sample project where we’re tracking 25,692 keywords against Amazon.com.

3. Using STAT’s segmentation tools

Setting up projects in STAT means making use of the segmentation tools. Here’s a quick rundown of what we used:

Standard tag: Best used to group your keywords into static themes — search intent, brand, product type, or modifier.

Dynamic tag: Like a smart playlist, automatically returns keywords that match certain criteria, like a given search volume, rank, or SERP feature appearance.

Data view: House any number of tags and show how those tags perform as a group.

Learn more about tags and data views in the STAT Knowledge Base.

Now, on to the main event…

1. Use top-level search intent to find SERP feature opportunities

To kick things off, we’ll identify the SERP features that appear at each level of search intent by creating tags.

Our first step is to filter our keywords and create standard tags for our search intent keywords (read more abou tfiltering keywords). Second, we create dynamic tags to track the appearance of specific SERP features within each search intent group. And our final step, to keep everything organized, is to place our tags in tidy little data views, according to search intent.

Here’s a peek at what that looks like in STAT:

What can we uncover?

Our standard tags (the blue tags) show how many keywords are in each search intent bucket: 2,940 commercial keywords. And our dynamic tags (the sunny yellow stars) show how many of those keywords return a SERP feature: 547 commercial keywords with a snippet.

This means we can quickly spot how much opportunity exists for each SERP feature by simply glancing at the tags. Boom!

By quickly crunching some numbers, we can see that snippets appear on 5 percent of our informational SERPs (27 out of 521), 19 percent of our commercial SERPs (547 out of 2,940), and 12 percent of our transactional SERPs (253 out of 2,058).

From this, we might conclude that optimizing our commercial intent keywords for featured snippets is the way to go since they appear to present the biggest opportunity. To confirm, let’s click on the commercial intent featured snippet tag to view the tag dashboard…

Voilà! There are loads of opportunities to gain a featured snippet.

Though, we should note that most of our keywords rank below where Google typically pulls the answer from. So, what we can see right away is that we need to make some serious ranking gains in order to stand a chance at grabbing those snippets.

2. Find SERP feature opportunities with intent modifiers

Now, let’s take a look at which SERP features appear most often for our different keyword modifiers.

To do this, we group our keywords by modifier and create a standard tag for each group. Then, we set up dynamic tags for our desired SERP features. Again, to keep track of all the things, we contained the tags in handy data views, grouped by search intent.

What can we uncover?

Because we saw that featured snippets appear most often for our commercial intent keywords, it’s time to drill on down and figure out precisely which modifiers within our commercial bucket are driving this trend.

Glancing quickly at the numbers in the tag titles in the image above, we can see that “best,” “reviews,” and “top” are responsible for the majority of the keywords that return a featured snippet:

212 out of 294 of our “best” keywords (72%)

109 out of 294 of our “reviews” keywords (37%)

170 out of 294 of our “top” keywords (59%)

This shows us where our efforts are best spent optimizing.

By clicking on the “best — featured snippets” tag, we’re magically transported into the dashboard. Here, we see that our average ranking could use some TLC.

There is a lot of opportunity to snag a snippet here, but we (actually, Amazon, who we’re tracking these keywords against) don’t seem to be capitalizing on that potential as much as we could. Let’s drill down further to see which snippets we already own.

We know we’ve got content that has won snippets, so we can use that as a guideline for the other keywords that we want to target.

3. See which pages are ranking best by search intent

In our blog post How Google dishes out content by search intent, we looked at what type of pages — category pages, product pages, reviews — appear most frequently at each stage of a searcher’s intent.

What we found was that Google loves category pages, which are the engine’s top choice for retail keywords across all levels of search intent. Product pages weren’t far behind.

By creating dynamic tags for URL markers, or portions of your URL that identify product pages versus category pages, and segmenting those by intent, you too can get all this glorious data. That’s exactly what we did for our retail keywords

What can we uncover?

Looking at the tags in the transactional page types data view, we can see that product pages are appearing far more frequently (526) than category pages (151).

When we glanced at the dashboard, we found that slightly more than half of the product pages were ranking on the first page (sah-weet!). That said, more than thirty percent appeared on page three and beyond. So despite the initial visual of “doing well”, there’s a lot of opportunity that Amazon could be capitalizing on.

We can also see this in the Daily Snapshot. In the image above, we compare category pages (left) to product pages (right), and we see that while there are less category pages ranking, the rank is significantly better. Amazon could take some of the lessons they’ve applied to their category pages to help their product pages out.

Wrapping it up

So what did we learn today?

Smart segmentation starts with a well-crafted list of keywords, grouped into tags, and housed in data views.

The more you segment, the more insights you’re gonna uncover.

Rely on the dashboards in STAT to flag opportunities and tell you what’s good, yo!

Want to see it all in action? Get a tailored walkthrough of STAT, here.

Or get your mitts on even more intent-based insights in our full whitepaper: Using search intent to connect with consumers.

Read on, readers!

More in our search intent series:

How SERP features respond to intent modifiers

How Google dishes out content by search intent

The basics of building an intent-based keyword list

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[we-johnnygonzalez-blog]

A Guide to Setting Up Your Very Own Search Intent Projects

Posted by TheMozTeam

This post was originally published on the STAT blog.

Whether you’re tracking thousands or millions of keywords, if you expect to extract deep insights and trends just by looking at your keywords from a high-level, you’re not getting the full story.

Smart segmentation is key to making sense of your data. And you’re probably already applying this outside of STAT. So now, we’re going to show you how to do it in STAT to uncover boatloads of insights that will help you make super data-driven decisions.

To show you what we mean, let’s take a look at a few ways we can set up a search intent project to uncover the kinds of insights we shared in our whitepaper, Using search intent to connect with consumers.

Before we jump in, there are a few things you should have down pat:

1. Picking a search intent that works for you

Search intent is the motivating force behind search and it can be:

Informational: The searcher has identified a need and is looking for information on the best solution, ie. [blender], [food processor]

Commercial: The searcher has zeroed in on a solution and wants to compare options, ie. [blender reviews], [best blenders]

Transactional: The searcher has narrowed their hunt down to a few best options, and is on the precipice of purchase, ie. [affordable blenders], [blender cost]

Local (sub-category of transactional): The searcher plans to do or buy something locally, ie. [blenders in dallas]

Navigational (sub-category of transactional): The searcher wants to locate a specific website, ie. [Blendtec]

We left navigational intent out of our study because it’s brand specific and didn’t want to bias our data.

Our keyword set was a big list of retail products — from kitty pooper-scoopers to pricey speakers. We needed a straightforward way to imply search intent, so we added keyword modifiers to characterize each type of intent.

As always, different strokes for different folks: The modifiers you choose and the intent categories you look at may differ, but it’s important to map that all out before you get started.

2. Identifying the SERP features you really want

For our whitepaper research, we pretty much tracked every feature under the sun, but you certainly don’t have to.

You might already know which features you want to target, the ones you want to keep an eye on, or questions you want to answer. For example, are shopping boxes taking up enough space to warrant a PPC strategy?

In this blog post, we’re going to really focus-in on our most beloved SERP feature: featured snippets (called “answers” in STAT). And we’ll be using a sample project where we’re tracking 25,692 keywords against Amazon.com.

3. Using STAT’s segmentation tools

Setting up projects in STAT means making use of the segmentation tools. Here’s a quick rundown of what we used:

Standard tag: Best used to group your keywords into static themes — search intent, brand, product type, or modifier.

Dynamic tag: Like a smart playlist, automatically returns keywords that match certain criteria, like a given search volume, rank, or SERP feature appearance.

Data view: House any number of tags and show how those tags perform as a group.

Learn more about tags and data views in the STAT Knowledge Base.

Now, on to the main event…

1. Use top-level search intent to find SERP feature opportunities

To kick things off, we’ll identify the SERP features that appear at each level of search intent by creating tags.

Our first step is to filter our keywords and create standard tags for our search intent keywords (read more abou tfiltering keywords). Second, we create dynamic tags to track the appearance of specific SERP features within each search intent group. And our final step, to keep everything organized, is to place our tags in tidy little data views, according to search intent.

Here’s a peek at what that looks like in STAT:

What can we uncover?

Our standard tags (the blue tags) show how many keywords are in each search intent bucket: 2,940 commercial keywords. And our dynamic tags (the sunny yellow stars) show how many of those keywords return a SERP feature: 547 commercial keywords with a snippet.

This means we can quickly spot how much opportunity exists for each SERP feature by simply glancing at the tags. Boom!

By quickly crunching some numbers, we can see that snippets appear on 5 percent of our informational SERPs (27 out of 521), 19 percent of our commercial SERPs (547 out of 2,940), and 12 percent of our transactional SERPs (253 out of 2,058).

From this, we might conclude that optimizing our commercial intent keywords for featured snippets is the way to go since they appear to present the biggest opportunity. To confirm, let’s click on the commercial intent featured snippet tag to view the tag dashboard…

Voilà! There are loads of opportunities to gain a featured snippet.

Though, we should note that most of our keywords rank below where Google typically pulls the answer from. So, what we can see right away is that we need to make some serious ranking gains in order to stand a chance at grabbing those snippets.

2. Find SERP feature opportunities with intent modifiers

Now, let’s take a look at which SERP features appear most often for our different keyword modifiers.

To do this, we group our keywords by modifier and create a standard tag for each group. Then, we set up dynamic tags for our desired SERP features. Again, to keep track of all the things, we contained the tags in handy data views, grouped by search intent.

What can we uncover?

Because we saw that featured snippets appear most often for our commercial intent keywords, it’s time to drill on down and figure out precisely which modifiers within our commercial bucket are driving this trend.

Glancing quickly at the numbers in the tag titles in the image above, we can see that “best,” “reviews,” and “top” are responsible for the majority of the keywords that return a featured snippet:

212 out of 294 of our “best” keywords (72%)

109 out of 294 of our “reviews” keywords (37%)

170 out of 294 of our “top” keywords (59%)

This shows us where our efforts are best spent optimizing.

By clicking on the “best — featured snippets” tag, we’re magically transported into the dashboard. Here, we see that our average ranking could use some TLC.

There is a lot of opportunity to snag a snippet here, but we (actually, Amazon, who we’re tracking these keywords against) don’t seem to be capitalizing on that potential as much as we could. Let’s drill down further to see which snippets we already own.

We know we’ve got content that has won snippets, so we can use that as a guideline for the other keywords that we want to target.

3. See which pages are ranking best by search intent

In our blog post How Google dishes out content by search intent, we looked at what type of pages — category pages, product pages, reviews — appear most frequently at each stage of a searcher’s intent.

What we found was that Google loves category pages, which are the engine’s top choice for retail keywords across all levels of search intent. Product pages weren’t far behind.

By creating dynamic tags for URL markers, or portions of your URL that identify product pages versus category pages, and segmenting those by intent, you too can get all this glorious data. That’s exactly what we did for our retail keywords

What can we uncover?

Looking at the tags in the transactional page types data view, we can see that product pages are appearing far more frequently (526) than category pages (151).

When we glanced at the dashboard, we found that slightly more than half of the product pages were ranking on the first page (sah-weet!). That said, more than thirty percent appeared on page three and beyond. So despite the initial visual of “doing well”, there’s a lot of opportunity that Amazon could be capitalizing on.

We can also see this in the Daily Snapshot. In the image above, we compare category pages (left) to product pages (right), and we see that while there are less category pages ranking, the rank is significantly better. Amazon could take some of the lessons they’ve applied to their category pages to help their product pages out.

Wrapping it up

So what did we learn today?

Smart segmentation starts with a well-crafted list of keywords, grouped into tags, and housed in data views.

The more you segment, the more insights you’re gonna uncover.

Rely on the dashboards in STAT to flag opportunities and tell you what’s good, yo!

Want to see it all in action? Get a tailored walkthrough of STAT, here.

Or get your mitts on even more intent-based insights in our full whitepaper: Using search intent to connect with consumers.

Read on, readers!

More in our search intent series:

How SERP features respond to intent modifiers

How Google dishes out content by search intent

The basics of building an intent-based keyword list

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[we-johnnygonzalez-blog]

A Guide to Setting Up Your Very Own Search Intent Projects

Posted by TheMozTeam

This post was originally published on the STAT blog.

Whether you’re tracking thousands or millions of keywords, if you expect to extract deep insights and trends just by looking at your keywords from a high-level, you’re not getting the full story.

Smart segmentation is key to making sense of your data. And you’re probably already applying this outside of STAT. So now, we’re going to show you how to do it in STAT to uncover boatloads of insights that will help you make super data-driven decisions.

To show you what we mean, let’s take a look at a few ways we can set up a search intent project to uncover the kinds of insights we shared in our whitepaper, Using search intent to connect with consumers.

Before we jump in, there are a few things you should have down pat:

1. Picking a search intent that works for you

Search intent is the motivating force behind search and it can be:

Informational: The searcher has identified a need and is looking for information on the best solution, ie. [blender], [food processor]

Commercial: The searcher has zeroed in on a solution and wants to compare options, ie. [blender reviews], [best blenders]

Transactional: The searcher has narrowed their hunt down to a few best options, and is on the precipice of purchase, ie. [affordable blenders], [blender cost]

Local (sub-category of transactional): The searcher plans to do or buy something locally, ie. [blenders in dallas]

Navigational (sub-category of transactional): The searcher wants to locate a specific website, ie. [Blendtec]

We left navigational intent out of our study because it’s brand specific and didn’t want to bias our data.

Our keyword set was a big list of retail products — from kitty pooper-scoopers to pricey speakers. We needed a straightforward way to imply search intent, so we added keyword modifiers to characterize each type of intent.

As always, different strokes for different folks: The modifiers you choose and the intent categories you look at may differ, but it’s important to map that all out before you get started.

2. Identifying the SERP features you really want

For our whitepaper research, we pretty much tracked every feature under the sun, but you certainly don’t have to.

You might already know which features you want to target, the ones you want to keep an eye on, or questions you want to answer. For example, are shopping boxes taking up enough space to warrant a PPC strategy?

In this blog post, we’re going to really focus-in on our most beloved SERP feature: featured snippets (called “answers” in STAT). And we’ll be using a sample project where we’re tracking 25,692 keywords against Amazon.com.

3. Using STAT’s segmentation tools

Setting up projects in STAT means making use of the segmentation tools. Here’s a quick rundown of what we used:

Standard tag: Best used to group your keywords into static themes — search intent, brand, product type, or modifier.

Dynamic tag: Like a smart playlist, automatically returns keywords that match certain criteria, like a given search volume, rank, or SERP feature appearance.

Data view: House any number of tags and show how those tags perform as a group.

Learn more about tags and data views in the STAT Knowledge Base.

Now, on to the main event…

1. Use top-level search intent to find SERP feature opportunities

To kick things off, we’ll identify the SERP features that appear at each level of search intent by creating tags.

Our first step is to filter our keywords and create standard tags for our search intent keywords (read more abou tfiltering keywords). Second, we create dynamic tags to track the appearance of specific SERP features within each search intent group. And our final step, to keep everything organized, is to place our tags in tidy little data views, according to search intent.

Here’s a peek at what that looks like in STAT:

What can we uncover?

Our standard tags (the blue tags) show how many keywords are in each search intent bucket: 2,940 commercial keywords. And our dynamic tags (the sunny yellow stars) show how many of those keywords return a SERP feature: 547 commercial keywords with a snippet.

This means we can quickly spot how much opportunity exists for each SERP feature by simply glancing at the tags. Boom!

By quickly crunching some numbers, we can see that snippets appear on 5 percent of our informational SERPs (27 out of 521), 19 percent of our commercial SERPs (547 out of 2,940), and 12 percent of our transactional SERPs (253 out of 2,058).

From this, we might conclude that optimizing our commercial intent keywords for featured snippets is the way to go since they appear to present the biggest opportunity. To confirm, let’s click on the commercial intent featured snippet tag to view the tag dashboard…

Voilà! There are loads of opportunities to gain a featured snippet.

Though, we should note that most of our keywords rank below where Google typically pulls the answer from. So, what we can see right away is that we need to make some serious ranking gains in order to stand a chance at grabbing those snippets.

2. Find SERP feature opportunities with intent modifiers

Now, let’s take a look at which SERP features appear most often for our different keyword modifiers.

To do this, we group our keywords by modifier and create a standard tag for each group. Then, we set up dynamic tags for our desired SERP features. Again, to keep track of all the things, we contained the tags in handy data views, grouped by search intent.

What can we uncover?

Because we saw that featured snippets appear most often for our commercial intent keywords, it’s time to drill on down and figure out precisely which modifiers within our commercial bucket are driving this trend.

Glancing quickly at the numbers in the tag titles in the image above, we can see that “best,” “reviews,” and “top” are responsible for the majority of the keywords that return a featured snippet:

212 out of 294 of our “best” keywords (72%)

109 out of 294 of our “reviews” keywords (37%)

170 out of 294 of our “top” keywords (59%)

This shows us where our efforts are best spent optimizing.

By clicking on the “best — featured snippets” tag, we’re magically transported into the dashboard. Here, we see that our average ranking could use some TLC.

There is a lot of opportunity to snag a snippet here, but we (actually, Amazon, who we’re tracking these keywords against) don’t seem to be capitalizing on that potential as much as we could. Let’s drill down further to see which snippets we already own.

We know we’ve got content that has won snippets, so we can use that as a guideline for the other keywords that we want to target.

3. See which pages are ranking best by search intent

In our blog post How Google dishes out content by search intent, we looked at what type of pages — category pages, product pages, reviews — appear most frequently at each stage of a searcher’s intent.

What we found was that Google loves category pages, which are the engine’s top choice for retail keywords across all levels of search intent. Product pages weren’t far behind.

By creating dynamic tags for URL markers, or portions of your URL that identify product pages versus category pages, and segmenting those by intent, you too can get all this glorious data. That’s exactly what we did for our retail keywords

What can we uncover?

Looking at the tags in the transactional page types data view, we can see that product pages are appearing far more frequently (526) than category pages (151).

When we glanced at the dashboard, we found that slightly more than half of the product pages were ranking on the first page (sah-weet!). That said, more than thirty percent appeared on page three and beyond. So despite the initial visual of “doing well”, there’s a lot of opportunity that Amazon could be capitalizing on.

We can also see this in the Daily Snapshot. In the image above, we compare category pages (left) to product pages (right), and we see that while there are less category pages ranking, the rank is significantly better. Amazon could take some of the lessons they’ve applied to their category pages to help their product pages out.

Wrapping it up

So what did we learn today?

Smart segmentation starts with a well-crafted list of keywords, grouped into tags, and housed in data views.

The more you segment, the more insights you’re gonna uncover.

Rely on the dashboards in STAT to flag opportunities and tell you what’s good, yo!

Want to see it all in action? Get a tailored walkthrough of STAT, here.

Or get your mitts on even more intent-based insights in our full whitepaper: Using search intent to connect with consumers.

Read on, readers!

More in our search intent series:

How SERP features respond to intent modifiers

How Google dishes out content by search intent

The basics of building an intent-based keyword list

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