#path of titans referral code

[elfo8792]

https://alderongames.com/refer-a-friend/013-780-222

Please? I want the Blue Jay skin for Deinonychus.

[redwingraptor]

Also! If anyone is interested in buying Path of Titans soon or hasn't used a referral link yet, please consider using mine! I'd be happy to play with anyone who uses my code so we can get the passive growth buff from playing together, as well as exclusive skins and such!

The link above will bring you to the purchase options using my referral link I believe!

[dimorphodon-x]

You've got me wanting to play path of titans... I showed your gameplay to my little brother and he wants to try it too XD

Heeeey you should tooootally use my referral code 👀

JK you don't have to I just want more skins lol

[sugarspooks15]

This is a bit off topic from my normal posts but I’ve gotten into play path of titans and I’m just going to post my referral code here.

[uwo]

slightly updated my pinned w extra info. not necessary but i feel like being a person ^_^

also also. *takes out my pocketwatch* ooooo u want to play path of titans with me OOOOO u want to use my referral code and play dinosaur simulator game with me soooo bad

[aralyndarkwhisper]

PATH OF TITANS REFER A FRIEND!

Want to get into Path of Titans for yourself & get a sweet Kingfisher bird based Suchomimus skin (various colour combinations!) & an Allo statue for your homecave, use my referral code below!

[rinniekins]

Path of Titans got an update so now you can grow your dino from a tiny baby to an adult!

And with it came this refer a friend thingy so I thought why not slap it in here just in case anyone happens to be interested in buying the game.

I really recommend it if you like dinosaurs or/and animal MMORPGs! Keep in mind that it’s still a DEMO though, but the developers have been doing an astounding job so far and I am really enjoying each new update!

https://alderongames.com/refer-a-friend/699-412-313 Here’s my code for the refer a friend thingy! If you use it when buying the game, you and me both will get the refer a friend exclusive Allosaurus Wildfire skin which is hecking gorgeous, and of course the growth buff and the Allosaurus statue. :)

I’d be more than happy to play with y’all and help you learn the ropes!

[mihovilart]

Probably not something anyone expected but I love dinosaurs and did some quick studies of my allosaurus character and her in-game mother.

(game: Path Of Titans; my referral code: here)

(the mother, owned by Janiiness)

[iamnightduchess]

WIP: Chills (T, Modern AU)

Summary:

A grieving mother finds herself confronting the shadows of her guilt, the long overdue failing of her marriage and memories of the one who could have been the moment they wheeled in an injured soldier from Marley straight into her operating room. The day she saved the life of Vice Commander Braun of Marley’s prized Titan unit was also the day he saved her own lost soul in return.

More often, memories may be lost forever but the heart never lies. He still makes shivers dance down her spine heading down to her feet just like he used to do twelve years ago and his heart still beats as hard for her the same way. Even when he can’t ever remember why. ReinerxMikasa. Modern + SnK HighSchool (Attack on High School Caste) AU.

Ship(s): Reiner x Mikasa (ReiKasa)

AU: Love Like This

-----

Snippet:

June 9, Present Year

Trost Military Hospital, Paradis

The sounds of her boots stepping hurriedly on the polished floors resonated against the clean, white walls of the hallways in hollowed echoes. A voice caught her dead in her tracks as soon as she turned into the corner leading into the more secluded operations wing of the hospital’s main building.

“Good afternoon, Dr. Jeager?” A young man, who seemed to be waiting anxiously near the entrance to the operating theatre DM05, approached her as soon as she came into his view. From his security tag and the embroidered emblem on his coat, it was very apparent that he is the personnel from Marley that she’s supposed to be liaising with on the emergency procedure she was called in for.

After quite some time, she casually corrected this stranger’s greeting underneath her breath. “It’s actually Dr. Ackerman now.”

“I’m sorry?” Perplexed, the man, still apologized for his potential blunder yet his tone remained polite despite the obvious confusion in his tone. “Also, I'm very sorry, I might have a misguided notion that the famous neurosurgeon in Paradis would be a--”

She turned her head to the side. “Some old, bearded guy with a bad sense of humor?” She couldn’t hold back the untimely humor laced with cynical sarcasm within her own voice.

She could see the other young man began to swallow a metaphorical knot nervously down his own throat and his trickling sweat didn’t help her observation either. “You’re not wrong actually. The original Dr. Jeager, my foster father, had been the famous one. Not me.”

“I’m sorry, Dr. Jeager, I mean Ackerman. I got confused.”

“No harm done.” Even she would be confused at her own status. She shook her head, dismissing her own earlier persistence in wanting to be addressed with her own maiden name again. A stranger doesn’t need to know her personal issues or the status of her marriage.

But she really needed to sort this shit out with the administration before more people get confused.

Nevertheless, she prompted for the attending personnel to continue his words.

“Thank you so much for scrubbing in. I’m Marcus Daniels, the attending physician for the patient. We apologize for this short notice but since it’s summer break, all of our neurosurgeons are away for volunteering or break. Rest assured, we have received the signed disclaimer from the patient’s next of kin, his mother, along with the referral from Marley’s Military Hospital. The paperwork has been received by the administration. We’re good to proceed with the emergency procedure.”

The raven-haired woman shook her head, disregarding the standard same ‘ole assurance from the Medical Officer who was tasked to accompany the Marleyan patient currently in between life and death on that table inside her Operation Theatre. Her patients’ lives take precedence before any incidents that could warrant a potential lawsuit. She gestured for the MO to follow suit as she put on the green scrubs and surgical cap available inside the prep room. “Walk with me, Daniels. Give me a brief of the patient. How long ago was the initial contact?”

“Male, 31, a military vet from Marley’s prized Special Ops Unit. The reported time of the initial impact was twelve hours ago. Patient’s BP is stable, X-ray did not display any shrapnels, bullet’s still in one piece but the bleeding unfortunately, had begun to spread to the patient’s medial temporal lobe since six hours ago….and...well….”

They stopped short just in front of the door that leads to the main wash area of the operating room. Her nose picked up the overwhelming scent of industrial disinfectant coming from behind that door. Her eyes leered back at the MO, her forehead creased in reaction to the other man’s trailing words. She did not like that tone or even the single last word of his sentence at all. “What is it?”

“Ma’am, the First Response team had to perform an emergency resuscitation and this could not be just an on-site training incident. There was an excessive amount of Paxil together with alcohol from the patient’s digestive tract. Patient was under the influence right before he went in to support the unit’s rookie training. Bloodwork confirmed this.” The young man, who looked like he’s only several years younger than she is, could only shook his head in absolute empathy.

Paxil and liquor are a deadly mix. The patient must have been aware of his own prescriptions. There was an immediate flash of concern upon her face before she pressed for a confirmation to her impulsive suspicion; asking, “C-PTSD? ‘Intentional’ incident?” She couldn’t possibly be discreet if she’s dealing with more than just the life of a war veteran on the line. An unstable patient with self-harming tendencies requires a much delicate approach especially if the injuries sustained by the patient would require a full invasive craniotomy to stop the source of bleeding from the bullet.

The MO shook his head in return. “We can’t rule that out or in yet without looking into the patient’s psych eval records. Those files are sealed by the Psychiatric unit in Marley, Dr. Jea-Ackerman. We’d need a referral from your Psychiatrist here to access those files after for the patient's recovery.”

“There’s no time to waste then.” There was a short pause in her words as she pressed a digital button on the room’s intercom system. “Nurse Rheinberger, Dr. Ackerman in OT-DM05. Code Blue. Requesting assistance to page Dr. Ian Dietrich, Psychiatry to support emergency neurosurgery a.s.ap. Over.”

She turned her head back to the young MO and inquired as a formality, even though she was very aware that the patient had been placed under anesthesia. “Patient’s name?”

“Uhm…” Daniels flipped open the paper folder in his hands and read the patient’s name out loud. “Braun, Reiner.”

She stopped dead in her tracks, her heart skipped not one but two immediate beats and she could feel it hitting hard against her chest. “Come again?”

“Reiner Braun, Dr. Ackerman. No middle name.”

There are a lot of people with the same name. “Birthdate?” It’s just not possible.

“August 1, 19xx.”

Her hands stood frozen against the door of the operation theater. From where she stood, she could see the motionless body hooked on multiple wires connecting to a life support system on top of her operation table from between the clear glass screens.

“Doctor?”

She looked back at the other man but not before blinking back the shock-induced tears gathered inside her eyelids. “Please get Dr. Dietrich here. Now. It would be against my protocol to operate on a patient with past or existing personal attachments without a senior physician’s supervision.”

“You know the patient?”

“Yes…He was...” Her words trailed unfinished, which only roused the other person’s curiosity although it was none of his business. “Just go. NOW.”

“Sorry, sorry!” The man quickly disappeared behind the main door in a flash leaving her behind with a much needed space and air to breathe.

Oh my God, Reiner. What happened to you?

She rushed towards the faucet and hurriedly splashed her face with the cold water just so she could hide the stubborn tears already running down her cheeks.

Out of all the times, why now? Why here? Why do their paths cross again after six years - with him; his life barely hanging on a thread right now on her very own operating table?

She can’t fuck this up. Never had she ever did before, but never had she ever performed a procedure on someone she personally knew. There are just too many reasons why and too little time for her to be caught in another mulling.

[didanawisgi]

“After I wrote Why it's time for a new social networking platform and how to make it successful, I was contacted on Twitter by an account I'd never heard of. The account was Minds, and they invited me to give its social networking platform a try.

Minds was launched five years ago by Bill Ottman; since then, the site has continued on in the shadow of the Facebook juggernaut. With a nod to irony, a large portion of Facebook users complain about the service on a daily basis--some even go so far as to say they'd leave Facebook if only an alternative existed. It seems that alternative does exist.

Case in point: Minds is surprisingly similar to Facebook in layout and features, though Minds isn't a simple clone of Facebook. Minds offers much of what I detailed in my previous article about a new social networking platform.

It's open source and transparent.

It offers free and paid accounts.

Its ownership and management enforce no political or social bias.

User data is not monetized.

It offers all the features users are accustomed to.

It minimizes hate speech without infringing upon free speech.

Minds uses cryptocurrency that users can earn and spend. The earned tokens can be used to boost posts, and a paid user account costs five tokens per month. The paid account earns users features like:

Access to exclusive content;

The ability to become verified; and

The ability to banish all the boosted posts from their feed.

Users earn tokens by:

Posting;

Commenting;

Receiving upvotes (similar to Likes on Facebook); and

Inviting others to join the platform (referral link).

So my curiosity was piqued. I created an account and began to poke around. After a few days, I drew the conclusion that Minds could very well be that social networking platform we've all been waiting for. To that end, I reached out to the CEO of Minds, Bill Ottman, to ask the questions that were on my mind about the site.

Jack Wallen: What made you start Minds?

Bill Ottman: I have always considered it an absolute necessity and historical inevitability that a free and open source social network rises up to become competitive with the proprietary tech titans. The top global communication platforms of humanity need to respect the freedom and voice of the community; otherwise, we end up where we are with a status-quo of surveillance, algorithmic manipulation, and exploitation. We knew we could not possibly be a sustainable network without building an independent social engine from the ground up, totally non-reliant on big tech APIs.

Jack Wallen: What is it that the likes of Facebook and Twitter are doing wrong?

Continuously audit configs and get alerted if a device is out of compliance. Be able to remediate vulnerabilities through bulk config deployment. Help prevent unauthorized network changes through change delegation, monitoring, and alerting.

Bill Ottman: There's minimal transparency with regards to both governance and software. Proprietary software should not be acceptable from our top networks, as it is impossible to audit. Their content policies are essentially indecipherable, inconsistent, and subjective. They prevent you from reaching your audience with hidden default algorithms. We are not anti-algo, but believe users should decide if they want to use them or not. They pretend to care about your privacy, offering a number of visibility controls, but ignore the ability to be invisible from them.

Jack Wallen: What is it that Facebook and Twitter are doing right?

Bill Ottman: The UX and design is excellent. Clearly they have brilliant developers and product designers who are able to build out robust features from live streaming to messaging services all interoperating cross-platform. They have vast resources to make acquisitions and deeply understand the functionality that people want. Unfortunately, the foundation of everything is upside down.

Jack Wallen: Explain, to the uninitiated, what sets Minds apart from other social platforms?

Bill Ottman:

We try to push the boundaries with radical transparency with open source code and even financials.

We are community-owned from an early stage with over 1,500 users who actually own stock.

We have implemented revenue-sharing and monetization tools to help people earn money, both fiat currency and crypto.

We believe that you should be rewarded for your contributions to the network and the engagement that you drive.

We don't require any personal information and encrypt any given.

We want to minimize hate speech with free speech, not censorship. In fact, we launched a whole initiative about this at https://change.minds.com. Research shows censorship may in fact cause greater polarization and radicalization than facilitation of legal civil discourse.

Jack Wallen: What made you opt to go the crypto route?

Bill Ottman: Prior to moving to Ethereum, we had a centralized virtual currency called points. This was one of our most popular features, as 1 point=1 view and could be used to Boost posts for greater reach, which people were losing on Facebook at alarming rates. You earned points for many types of engagement. Once Ethereum emerged we saw every reason to migrate the wholereward system to it, as this allows the token economy to become decentralized where users can hold their tokens in their own wallets and transact on-chain, which provides greater transparency as well.

Now, users can accept fiat (via stripe), Bitcoin, Ether, and Minds tokens which are ERC-20. The crypto community typically adheres to values aligned with internet freedom. You can't and shouldn't run everything on a blockchain , but we are committed to the P2P route everywhere that makes sense and isn't an impossible UX. Providing people with options and control is paramount. Do I want to publish this post to an immutable distributed system or not? That's a choice we want to provide rather than forcing a particular path.

Jack Wallen: How will Minds deal with some of the issues that have faced other platforms such as hate speech and groups that espouse such speech?

Bill Ottman: We launched the Change Minds initiative with our advisor Daryl Davis, who famously deradicalized over 200 members of the KKK through open discourse, basically, befriending them. This human approach, based in free expression and civil dialogue, is much more aligned with our values and peer-reviewed research than blanket ban policies. The goal is to provide a breeding ground for changing minds via civil discourse as Daryl has proven can work, even if it takes years. We also built a jury system for the appeals process to bring the community into the moderation structure. Our approach is long-term and synced with the First Amendment. We care a lot about building tools for people to not see anything they don't want to see as well as reporting truly harmful content. We think policies involving censorship should be data driven. What actually works?...”

[samiam03x]

How to Use the New Lifetime Value Feature in Google Analytics

You’re drowning in data.

You’ve got enough KPIs to track and report on already.

Why would you possibly need another one? What good would come of adding yet another hour to the end of you’re already long work day in order to dig it up?

The truth, in this case, is that you can’t afford not to.

Lifetime Value isn’t just another vanity metric. It’s THE metric. The one that stands head and shoulders above all others.

IF there was one and only one metric you were tracking, this should be it.

And now you can do it simply and easily inside Google Analytics. Here’s how.

What is Lifetime Value (And Why Does it Matter?)

Metrics often lead you astray.

Take Cost Per Click.

They range wildly from industry to industry. $2 bucks in one industry, but $50 bucks in another.

Crazy, right? Surely that $50 is just “too expensive.”

Not necessarily, obviously.

The first easy answer is your break-even point. If your Cost Per Acquisition is less than your initial average order value, you’re golden.

But sometimes, in some cases, you actually want to willingly lose money initially.

Image Source

Ever heard of Netflix? How about Amazon?

Amazon routinely enters a new market with razor thin (or even negative) profit margins so they can grab market share. Only to then turn the dial back once they’ve gained a market leadership position.

Image Source

So what’s a reasonable Cost Per Click in that scenario? Now it depends.

This can even change from company to company within a vertical (and their appetite for risk).

Let’s talk insurance.

Two ways to make money:

Upfront commission when you close a sale

Ongoing residual payments over the life of each deal.

So you’ve got a new company. Entering a new market and trying to expand.

Would you willingly, purposefully sacrifice #1 in order to scale #2?

Of course you would.

Why? Because the lifetime value of a customer.

The full potential value of each new client you add will eclipse the initial commision. So as long as you can stomach the negative cash flow for a bit, you’d probably be willing to drive that Cost Per Click as high as humanely possible.

You go all in, when the stakes are right, and drive everyone else out.

All of this sounds perfect, except for one teeny, tiny detail.

Does your company track lifetime value? ‘Cause most don’t.

I’ve personally worked with dozens (hundreds?) of clients over the past few years and I can count on one hand the number who were actually tracking conversions properly. Let alone seeing anything past the first purchase.

One of the reasons is because tracking this info, with current systems, isn’t always easy. It might be easy if you’re using a Shopify and do all sales in a single channel or two. That way, everything happens inside one platform.

But usually your business is spread out. Each department has their own independent systems. So it’s tough to bring everything together.

Thankfully, Google Analytics has been hard at work recently.

Their new Lifetime Value report helps business owners acquire data to understand how valuable certain users/customers are to their business based on their lifetime performance.

And best of all, it pulls together lifetime values for people acquired through different channels and mediums, like social, email, and paid search. You’ll also be able to view data by engagement (pageviews, goals, events) and then trends (like 90 days after customer acquisition).

Using this will help you determine which sources are driving the most valuable traffic and which corresponding marketing investments are truly delivering an ROI.

Here’s how to run a lifetime value report inside Google Analytics.

How to Run a Lifetime Value Report

Start by signing into your Google Analytics account and then follow these simple steps:

Step 1: Click on Reports Section Step 2: Click on Audience Step 3: Click on Lifetime Value

Note: The Lifetime Value feature should already be available inside your GA account (no need to change your code!).

Now let’s get started generating a report. Here’s how to setup your graph first:

Start by setting your acquisition date range (the option on the far right). Any customer acquired during this date range (May 2017 on this example) will be included in the LTV report.

Let’s say you ran a promotional campaign or online sale during the month of May, you can easily analyze the data for these customers and segment by date based on your campaigns.

For steps two and three, you can select the following list of metrics to compare:

Now let’s break this graph down a bit to help you understand what the heck is going on:

Essentially, this graph is showing site users acquired during the month of May, and how their lifetime value changes based on the page views and session duration metrics over a 90-day period on the site.

These are obviously engagement metrics, you can customize this even further to track the exact amount spent if you have eCommerce tracking enabled.

Now, let’s jump to the table below:

Now we’re able to compare the number of acquired users (and the Pageviews per User) in this case by acquisition channel.

Click on the dropdown above the table to pull up different granular sorting options like Source, Medium, or Campaign.

How is this helpful? Check it out:

Let me break it down:

Blue: Acquisition channel. This shows what channel the users were acquired through, i.e, direct, organic, social, referral.

Pink: Users. The amount of users in the specified acquisition date range (May 2017 in this example)

Purple: Your selected lifetime value metric. In this example, pageviews per user is the LTV. This column is where the data begins to get interesting.

Let’s zoom in on the last column in detail to see if there’s any insight we can already glean from these reports.

Now we start to notice patterns among the different channels. For example, Referral traffic has double the pageviews per user (LTV) than almost every other channel. While Organic pageviews per user (LTV) is beginning to fall behind.

Want to pull back the curtain even more? Like being able to see things what individual Referral sites are driving higher LTV’s?

Head back over to the “Acquisition Source” on your table. Now we can break down which individual websites are sending us the most valuable traffic (based on LTV). And the winner is…

Kissmetrics! What, what!

Here’s why this new insight important.

Data Lies. LTV Forces it to Tell the Truth

Data lies to you daily.

For example, pull up your Goals inside Google Analytics to conduct a similar analysis to the one we just did.

You can even view the Reverse Funnel Path to see which pages, posts, or campaigns delivered the most conversions. This report is helpful… to a point. If you understand its limitations.

For example:

❌ Problem #1. These could be subscribers or leads. Not solid purchases. So you’re basing hard decisions off of ‘top of funnel’ data.

One campaign or channel might send 100 subscribers while the other only sends 20. But none of this takes into account how many of those people are converting. Or even how much money each is spending.

❌ Problem #2. Oh, these are sales, you say? Ok.

Except for one thing: You can’t tell if they’re one-off or repeat. So you can’t tell if each customer is a $100 order or a $1,000 one.

Which is kinda important when you’re looking backwards to see how that content investment performed vs. the paid campaign.

❌ Problem #3. A/B tests lie, too.

Things start off great. That new button resulted in a big conversion rate leap.

The only problem is that these small, temporary fluctuates often regress back to the mean. Larry Kim likened it to “moving desk chairs around the Titanic.”

Image Source

There might only be a literal surface level change, without ever fundamentally improving the organization as a whole.

When does this commonly happen? When you over-optimize.

❌ Problem #4. Over-optimization.

A/B tests that increase top line metrics often backfire.

For example, another study from Larry Kim showed that for every increase you made in a conversion rate, the lower your rate of Marketing Qualified Leads.

Image Source

In other words, the more aggressive you at are collecting that initial opt-in or lead can often lower the overall quality of the leads that are getting in. Which doesn’t make a whole lot of sense in the grand scheme of things when you think about it.

The point is that there are many, many ways data often lies to us. We think we’re seeing the whole picture, when in reality, it’s only a tiny slice of it.

Conclusion

Metrics aren’t always they appear. And data often lies.

What’s an “expensive” Cost Per Click for one business, isn’t for another. And sometimes that overall conversion rate we’re looking at to base our decisions around is fraught with peril in reality.

The one savior is Lifetime Value.

It gives us a broader, big picture context when viewing other bits of information. It helps us put things into proper context.

So we can not only make better decisions to drive additional revenue. But also realize when we’re about to make a few costly mistakes.

About the Author: Brad Smith is the founder of Codeless, a B2B content creation company. Frequent contributor to Kissmetrics, Unbounce, WordStream, AdEspresso, Search Engine Journal, Autopilot, and more.

http://ift.tt/2t8dyMA from MarketingRSS http://ift.tt/2uah2D9 via Youtube

[marie85marketing]

How to Use the New Lifetime Value Feature in Google Analytics

You’re drowning in data.

You’ve got enough KPIs to track and report on already.

Why would you possibly need another one? What good would come of adding yet another hour to the end of you’re already long work day in order to dig it up?

The truth, in this case, is that you can’t afford not to.

Lifetime Value isn’t just another vanity metric. It’s THE metric. The one that stands head and shoulders above all others.

IF there was one and only one metric you were tracking, this should be it.

And now you can do it simply and easily inside Google Analytics. Here’s how.

What is Lifetime Value (And Why Does it Matter?)

Metrics often lead you astray.

Take Cost Per Click.

They range wildly from industry to industry. $2 bucks in one industry, but $50 bucks in another.

Crazy, right? Surely that $50 is just “too expensive.”

Not necessarily, obviously.

The first easy answer is your break-even point. If your Cost Per Acquisition is less than your initial average order value, you’re golden.

But sometimes, in some cases, you actually want to willingly lose money initially.

Image Source

Ever heard of Netflix? How about Amazon?

Amazon routinely enters a new market with razor thin (or even negative) profit margins so they can grab market share. Only to then turn the dial back once they’ve gained a market leadership position.

Image Source

So what’s a reasonable Cost Per Click in that scenario? Now it depends.

This can even change from company to company within a vertical (and their appetite for risk).

Let’s talk insurance.

Two ways to make money:

Upfront commission when you close a sale

Ongoing residual payments over the life of each deal.

So you’ve got a new company. Entering a new market and trying to expand.

Would you willingly, purposefully sacrifice #1 in order to scale #2?

Of course you would.

Why? Because the lifetime value of a customer.

The full potential value of each new client you add will eclipse the initial commision. So as long as you can stomach the negative cash flow for a bit, you’d probably be willing to drive that Cost Per Click as high as humanely possible.

You go all in, when the stakes are right, and drive everyone else out.

All of this sounds perfect, except for one teeny, tiny detail.

Does your company track lifetime value? ‘Cause most don’t.

I’ve personally worked with dozens (hundreds?) of clients over the past few years and I can count on one hand the number who were actually tracking conversions properly. Let alone seeing anything past the first purchase.

One of the reasons is because tracking this info, with current systems, isn’t always easy. It might be easy if you’re using a Shopify and do all sales in a single channel or two. That way, everything happens inside one platform.

But usually your business is spread out. Each department has their own independent systems. So it’s tough to bring everything together.

Thankfully, Google Analytics has been hard at work recently.

Their new Lifetime Value report helps business owners acquire data to understand how valuable certain users/customers are to their business based on their lifetime performance.

And best of all, it pulls together lifetime values for people acquired through different channels and mediums, like social, email, and paid search. You’ll also be able to view data by engagement (pageviews, goals, events) and then trends (like 90 days after customer acquisition).

Using this will help you determine which sources are driving the most valuable traffic and which corresponding marketing investments are truly delivering an ROI.

Here’s how to run a lifetime value report inside Google Analytics.

How to Run a Lifetime Value Report

Start by signing into your Google Analytics account and then follow these simple steps:

Step 1: Click on Reports Section Step 2: Click on Audience Step 3: Click on Lifetime Value

Note: The Lifetime Value feature should already be available inside your GA account (no need to change your code!).

Now let’s get started generating a report. Here’s how to setup your graph first:

Start by setting your acquisition date range (the option on the far right). Any customer acquired during this date range (May 2017 on this example) will be included in the LTV report.

Let’s say you ran a promotional campaign or online sale during the month of May, you can easily analyze the data for these customers and segment by date based on your campaigns.

For steps two and three, you can select the following list of metrics to compare:

Now let’s break this graph down a bit to help you understand what the heck is going on:

Essentially, this graph is showing site users acquired during the month of May, and how their lifetime value changes based on the page views and session duration metrics over a 90-day period on the site.

These are obviously engagement metrics, you can customize this even further to track the exact amount spent if you have eCommerce tracking enabled.

Now, let’s jump to the table below:

Now we’re able to compare the number of acquired users (and the Pageviews per User) in this case by acquisition channel.

Click on the dropdown above the table to pull up different granular sorting options like Source, Medium, or Campaign.

How is this helpful? Check it out:

Let me break it down:

Blue: Acquisition channel. This shows what channel the users were acquired through, i.e, direct, organic, social, referral.

Pink: Users. The amount of users in the specified acquisition date range (May 2017 in this example)

Purple: Your selected lifetime value metric. In this example, pageviews per user is the LTV. This column is where the data begins to get interesting.

Let’s zoom in on the last column in detail to see if there’s any insight we can already glean from these reports.

Now we start to notice patterns among the different channels. For example, Referral traffic has double the pageviews per user (LTV) than almost every other channel. While Organic pageviews per user (LTV) is beginning to fall behind.

Want to pull back the curtain even more? Like being able to see things what individual Referral sites are driving higher LTV’s?

Head back over to the “Acquisition Source” on your table. Now we can break down which individual websites are sending us the most valuable traffic (based on LTV). And the winner is…

Kissmetrics! What, what!

Here’s why this new insight important.

Data Lies. LTV Forces it to Tell the Truth

Data lies to you daily.

For example, pull up your Goals inside Google Analytics to conduct a similar analysis to the one we just did.

You can even view the Reverse Funnel Path to see which pages, posts, or campaigns delivered the most conversions. This report is helpful… to a point. If you understand its limitations.

For example:

❌ Problem #1. These could be subscribers or leads. Not solid purchases. So you’re basing hard decisions off of ‘top of funnel’ data.

One campaign or channel might send 100 subscribers while the other only sends 20. But none of this takes into account how many of those people are converting. Or even how much money each is spending.

❌ Problem #2. Oh, these are sales, you say? Ok.

Except for one thing: You can’t tell if they’re one-off or repeat. So you can’t tell if each customer is a $100 order or a $1,000 one.

Which is kinda important when you’re looking backwards to see how that content investment performed vs. the paid campaign.

❌ Problem #3. A/B tests lie, too.

Things start off great. That new button resulted in a big conversion rate leap.

The only problem is that these small, temporary fluctuates often regress back to the mean. Larry Kim likened it to “moving desk chairs around the Titanic.”

Image Source

There might only be a literal surface level change, without ever fundamentally improving the organization as a whole.

When does this commonly happen? When you over-optimize.

❌ Problem #4. Over-optimization.

A/B tests that increase top line metrics often backfire.

For example, another study from Larry Kim showed that for every increase you made in a conversion rate, the lower your rate of Marketing Qualified Leads.

Image Source

In other words, the more aggressive you at are collecting that initial opt-in or lead can often lower the overall quality of the leads that are getting in. Which doesn’t make a whole lot of sense in the grand scheme of things when you think about it.

The point is that there are many, many ways data often lies to us. We think we’re seeing the whole picture, when in reality, it’s only a tiny slice of it.

Conclusion

Metrics aren’t always they appear. And data often lies.

What’s an “expensive” Cost Per Click for one business, isn’t for another. And sometimes that overall conversion rate we’re looking at to base our decisions around is fraught with peril in reality.

The one savior is Lifetime Value.

It gives us a broader, big picture context when viewing other bits of information. It helps us put things into proper context.

So we can not only make better decisions to drive additional revenue. But also realize when we’re about to make a few costly mistakes.

About the Author: Brad Smith is the founder of Codeless, a B2B content creation company. Frequent contributor to Kissmetrics, Unbounce, WordStream, AdEspresso, Search Engine Journal, Autopilot, and more.

[alissaselezneva]

How to Use the New Lifetime Value Feature in Google Analytics

You’re drowning in data.

You’ve got enough KPIs to track and report on already.

Why would you possibly need another one? What good would come of adding yet another hour to the end of you’re already long work day in order to dig it up?

The truth, in this case, is that you can’t afford not to.

Lifetime Value isn’t just another vanity metric. It’s THE metric. The one that stands head and shoulders above all others.

IF there was one and only one metric you were tracking, this should be it.

And now you can do it simply and easily inside Google Analytics. Here’s how.

What is Lifetime Value (And Why Does it Matter?)

Metrics often lead you astray.

Take Cost Per Click.

They range wildly from industry to industry. $2 bucks in one industry, but $50 bucks in another.

Crazy, right? Surely that $50 is just “too expensive.”

Not necessarily, obviously.

The first easy answer is your break-even point. If your Cost Per Acquisition is less than your initial average order value, you’re golden.

But sometimes, in some cases, you actually want to willingly lose money initially.

Image Source

Ever heard of Netflix? How about Amazon?

Amazon routinely enters a new market with razor thin (or even negative) profit margins so they can grab market share. Only to then turn the dial back once they’ve gained a market leadership position.

Image Source

So what’s a reasonable Cost Per Click in that scenario? Now it depends.

This can even change from company to company within a vertical (and their appetite for risk).

Let’s talk insurance.

Two ways to make money:

Upfront commission when you close a sale

Ongoing residual payments over the life of each deal.

So you’ve got a new company. Entering a new market and trying to expand.

Would you willingly, purposefully sacrifice #1 in order to scale #2?

Of course you would.

Why? Because the lifetime value of a customer.

The full potential value of each new client you add will eclipse the initial commision. So as long as you can stomach the negative cash flow for a bit, you’d probably be willing to drive that Cost Per Click as high as humanely possible.

You go all in, when the stakes are right, and drive everyone else out.

All of this sounds perfect, except for one teeny, tiny detail.

Does your company track lifetime value? ‘Cause most don’t.

I’ve personally worked with dozens (hundreds?) of clients over the past few years and I can count on one hand the number who were actually tracking conversions properly. Let alone seeing anything past the first purchase.

One of the reasons is because tracking this info, with current systems, isn’t always easy. It might be easy if you’re using a Shopify and do all sales in a single channel or two. That way, everything happens inside one platform.

But usually your business is spread out. Each department has their own independent systems. So it’s tough to bring everything together.

Thankfully, Google Analytics has been hard at work recently.

Their new Lifetime Value report helps business owners acquire data to understand how valuable certain users/customers are to their business based on their lifetime performance.

And best of all, it pulls together lifetime values for people acquired through different channels and mediums, like social, email, and paid search. You’ll also be able to view data by engagement (pageviews, goals, events) and then trends (like 90 days after customer acquisition).

Using this will help you determine which sources are driving the most valuable traffic and which corresponding marketing investments are truly delivering an ROI.

Here’s how to run a lifetime value report inside Google Analytics.

How to Run a Lifetime Value Report

Start by signing into your Google Analytics account and then follow these simple steps:

Step 1: Click on Reports Section Step 2: Click on Audience Step 3: Click on Lifetime Value

Note: The Lifetime Value feature should already be available inside your GA account (no need to change your code!).

Now let’s get started generating a report. Here’s how to setup your graph first:

Start by setting your acquisition date range (the option on the far right). Any customer acquired during this date range (May 2017 on this example) will be included in the LTV report.

Let’s say you ran a promotional campaign or online sale during the month of May, you can easily analyze the data for these customers and segment by date based on your campaigns.

For steps two and three, you can select the following list of metrics to compare:

Now let’s break this graph down a bit to help you understand what the heck is going on:

Essentially, this graph is showing site users acquired during the month of May, and how their lifetime value changes based on the page views and session duration metrics over a 90 day period on the site.

These are obviously engagement metrics, you can customize this even further to track the exact amount spent if you have eCommerce tracking enabled.

Now, let’s jump to the table below:

Now we’re able to compare the number of acquired users (and the Pageviews per User) in this case by acquisition channel.

Click on the dropdown above the table to pull up different granular sorting options like Source, Medium, or Campaign.

How is this helpful? Check it out:

Let me break it down:

Blue: Acquisition channel. This shows what channel the users were acquired through, i.e, direct, organic, social, referral.

Pink: Users. The amount of users in the specified acquisition date range (May 2017 in this example)

Purple: Your selected lifetime value metric. In this example, pageviews per user is the LTV. This column is where the data begins to get interesting.

Let’s zoom in on the last column in detail to see if there’s any insight we can already glean from these reports.

Now we start to notice patterns among the different channels. For example, Referral traffic has double the pageviews per user (LTV) than almost every other channel. While Organic pageviews per user (LTV) is beginning to fall behind.

Want to pull back the curtain even more? Like being able to see things what individual Referral sites are driving higher LTV’s?

Head back over to the “Acquisition Source” on your table. Now we can break down which individual websites are sending us the most valuable traffic (based on LTV). And the winner is…

Kissmetrics! What, what!

Here’s why this new insight important.

Data Lies. LTV Forces it to Tell the Truth

Data lies to you daily.

For example, pull up your Goals inside Google Analytics to conduct a similar analysis to the one we just did.

You can even view the Reverse Funnel Path to see which pages, posts, or campaigns delivered the most conversions. This report is helpful… to a point. If you understand its limitations.

For example:

❌ Problem #1. These could be subscribers or leads. Not solid purchases. So you’re basing hard decisions off of ‘top of funnel’ data.

One campaign or channel might send 100 subscribers while the other only sends 20. But none of this takes into account how many of those people are converting. Or even how much money each is spending.

❌ Problem #2. Oh, these are sales, you say? Ok.

Except for one thing: You can’t tell if they’re one-off or repeat. So you can’t tell if each customer is a $100 order or a $1,000 one.

Which is kinda important when you’re looking backwards to see how that content investment performed vs. the paid campaign.

❌ Problem #3. A/B tests lie, too.

Things start off great. That new button resulted in a big conversion rate leap.

The only problem is that these small, temporary fluctuates often regress back to the mean. Larry Kim likened it to “moving desk chairs around the Titanic.”

Image Source

There might only be a literal surface level change, without ever fundamentally improving the organization as a whole.

When does this commonly happen? When you over-optimize.

❌ Problem #4. Over-optimization.

A/B tests that increase top line metrics often backfire.

For example, another study from Larry Kim showed that for every increase you made in a conversion rate, the lower your rate of Marketing Qualified Leads.

Image Source

In other words, the more aggressive you at are collecting that initial opt-in or lead can often lower the overall quality of the leads that are getting in. Which doesn’t make a whole lot of sense in the grand scheme of things when you think about it.

The point is that there are many, many ways data often lies to us. We think we’re seeing the whole picture, when in reality, it’s only a tiny slice of it.

Conclusion

Metrics aren’t always they appear. And data often lies.

What’s an “expensive” Cost Per Click for one business, isn’t for another. And sometimes that overall conversion rate we’re looking at to base our decisions around is fraught with peril in reality.

The one savior is Lifetime Value.

It gives us a broader, big picture context when viewing other bits of information. It helps us put things into proper context.

So we can not only make better decisions to drive additional revenue. But also realize when we’re about to make a few costly mistakes.

About the Author: Brad Smith is the founder of Codeless, a B2B content creation company. Frequent contributor to Kissmetrics, Unbounce, WordStream, AdEspresso, Search Engine Journal, Autopilot, and more.

from WordPress https://reviewandbonuss.wordpress.com/2017/07/10/how-to-use-the-new-lifetime-value-feature-in-google-analytics/

[uwo]

if anyones interested in getting path of titans lmk and ill give u my referral code 💖 well both get little goodies

[filipeteimuraz]

How to Use the New Lifetime Value Feature in Google Analytics

You’re drowning in data.

You’ve got enough KPIs to track and report on already.

Why would you possibly need another one? What good would come of adding yet another hour to the end of you’re already long work day in order to dig it up?

The truth, in this case, is that you can’t afford not to.

Lifetime Value isn’t just another vanity metric. It’s THE metric. The one that stands head and shoulders above all others.

IF there was one and only one metric you were tracking, this should be it.

And now you can do it simply and easily inside Google Analytics. Here’s how.

What is Lifetime Value (And Why Does it Matter?)

Metrics often lead you astray.

Take Cost Per Click.

They range wildly from industry to industry. $2 bucks in one industry, but $50 bucks in another.

Crazy, right? Surely that $50 is just “too expensive.”

Not necessarily, obviously.

The first easy answer is your break-even point. If your Cost Per Acquisition is less than your initial average order value, you’re golden.

But sometimes, in some cases, you actually want to willingly lose money initially.

Image Source

Ever heard of Netflix? How about Amazon?

Amazon routinely enters a new market with razor thin (or even negative) profit margins so they can grab market share. Only to then turn the dial back once they’ve gained a market leadership position.

Image Source

So what’s a reasonable Cost Per Click in that scenario? Now it depends.

This can even change from company to company within a vertical (and their appetite for risk).

Let’s talk insurance.

Two ways to make money:

Upfront commission when you close a sale

Ongoing residual payments over the life of each deal.

So you’ve got a new company. Entering a new market and trying to expand.

Would you willingly, purposefully sacrifice #1 in order to scale #2?

Of course you would.

Why? Because the lifetime value of a customer.

The full potential value of each new client you add will eclipse the initial commision. So as long as you can stomach the negative cash flow for a bit, you’d probably be willing to drive that Cost Per Click as high as humanely possible.

You go all in, when the stakes are right, and drive everyone else out.

All of this sounds perfect, except for one teeny, tiny detail.

Does your company track lifetime value? ‘Cause most don’t.

I’ve personally worked with dozens (hundreds?) of clients over the past few years and I can count on one hand the number who were actually tracking conversions properly. Let alone seeing anything past the first purchase.

One of the reasons is because tracking this info, with current systems, isn’t always easy. It might be easy if you’re using a Shopify and do all sales in a single channel or two. That way, everything happens inside one platform.

But usually your business is spread out. Each department has their own independent systems. So it’s tough to bring everything together.

Thankfully, Google Analytics has been hard at work recently.

Their new Lifetime Value report helps business owners acquire data to understand how valuable certain users/customers are to their business based on their lifetime performance.

And best of all, it pulls together lifetime values for people acquired through different channels and mediums, like social, email, and paid search. You’ll also be able to view data by engagement (pageviews, goals, events) and then trends (like 90 days after customer acquisition).

Using this will help you determine which sources are driving the most valuable traffic and which corresponding marketing investments are truly delivering an ROI.

Here’s how to run a lifetime value report inside Google Analytics.

How to Run a Lifetime Value Report

Start by signing into your Google Analytics account and then follow these simple steps:

Step 1: Click on Reports Section Step 2: Click on Audience Step 3: Click on Lifetime Value

Note: The Lifetime Value feature should already be available inside your GA account (no need to change your code!).

Now let’s get started generating a report. Here’s how to setup your graph first:

Start by setting your acquisition date range (the option on the far right). Any customer acquired during this date range (May 2017 on this example) will be included in the LTV report.

Let’s say you ran a promotional campaign or online sale during the month of May, you can easily analyze the data for these customers and segment by date based on your campaigns.

For steps two and three, you can select the following list of metrics to compare:

Now let’s break this graph down a bit to help you understand what the heck is going on:

Essentially, this graph is showing site users acquired during the month of May, and how their lifetime value changes based on the page views and session duration metrics over a 90 day period on the site.

These are obviously engagement metrics, you can customize this even further to track the exact amount spent if you have eCommerce tracking enabled.

Now, let’s jump to the table below:

Now we’re able to compare the number of acquired users (and the Pageviews per User) in this case by acquisition channel.

Click on the dropdown above the table to pull up different granular sorting options like Source, Medium, or Campaign.

How is this helpful? Check it out:

Let me break it down:

Blue: Acquisition channel. This shows what channel the users were acquired through, i.e, direct, organic, social, referral.

Pink: Users. The amount of users in the specified acquisition date range (May 2017 in this example)

Purple: Your selected lifetime value metric. In this example, pageviews per user is the LTV. This column is where the data begins to get interesting.

Let’s zoom in on the last column in detail to see if there’s any insight we can already glean from these reports.

Now we start to notice patterns among the different channels. For example, Referral traffic has double the pageviews per user (LTV) than almost every other channel. While Organic pageviews per user (LTV) is beginning to fall behind.

Want to pull back the curtain even more? Like being able to see things what individual Referral sites are driving higher LTV’s?

Head back over to the “Acquisition Source” on your table. Now we can break down which individual websites are sending us the most valuable traffic (based on LTV). And the winner is…

Kissmetrics! What, what!

Here’s why this new insight important.

Data Lies. LTV Forces it to Tell the Truth

Data lies to you daily.

For example, pull up your Goals inside Google Analytics to conduct a similar analysis to the one we just did.

You can even view the Reverse Funnel Path to see which pages, posts, or campaigns delivered the most conversions. This report is helpful… to a point. If you understand its limitations.

For example:

❌ Problem #1. These could be subscribers or leads. Not solid purchases. So you’re basing hard decisions off of ‘top of funnel’ data.

One campaign or channel might send 100 subscribers while the other only sends 20. But none of this takes into account how many of those people are converting. Or even how much money each is spending.

❌ Problem #2. Oh, these are sales, you say? Ok.

Except for one thing: You can’t tell if they’re one-off or repeat. So you can’t tell if each customer is a $100 order or a $1,000 one.

Which is kinda important when you’re looking backwards to see how that content investment performed vs. the paid campaign.

❌ Problem #3. A/B tests lie, too.

Things start off great. That new button resulted in a big conversion rate leap.

The only problem is that these small, temporary fluctuates often regress back to the mean. Larry Kim likened it to “moving desk chairs around the Titanic.”

Image Source

There might only be a literal surface level change, without ever fundamentally improving the organization as a whole.

When does this commonly happen? When you over-optimize.

❌ Problem #4. Over-optimization.

A/B tests that increase top line metrics often backfire.

For example, another study from Larry Kim showed that for every increase you made in a conversion rate, the lower your rate of Marketing Qualified Leads.

Image Source

In other words, the more aggressive you at are collecting that initial opt-in or lead can often lower the overall quality of the leads that are getting in. Which doesn’t make a whole lot of sense in the grand scheme of things when you think about it.

The point is that there are many, many ways data often lies to us. We think we’re seeing the whole picture, when in reality, it’s only a tiny slice of it.

Conclusion

Metrics aren’t always they appear. And data often lies.

What’s an “expensive” Cost Per Click for one business, isn’t for another. And sometimes that overall conversion rate we’re looking at to base our decisions around is fraught with peril in reality.

The one savior is Lifetime Value.

It gives us a broader, big picture context when viewing other bits of information. It helps us put things into proper context.

So we can not only make better decisions to drive additional revenue. But also realize when we’re about to make a few costly mistakes.

About the Author: Brad Smith is the founder of Codeless, a B2B content creation company. Frequent contributor to Kissmetrics, Unbounce, WordStream, AdEspresso, Search Engine Journal, Autopilot, and more.

Read more here - http://review-and-bonuss.blogspot.com/2017/07/how-to-use-new-lifetime-value-feature.html

[ericsburden-blog]

How to Use the New Lifetime Value Feature in Google Analytics

You’re drowning in data.

You’ve got enough KPIs to track and report on already.

Why would you possibly need another one? What good would come of adding yet another hour to the end of you’re already long work day in order to dig it up?

The truth, in this case, is that you can’t afford not to.

Lifetime Value isn’t just another vanity metric. It’s THE metric. The one that stands head and shoulders above all others.

IF there was one and only one metric you were tracking, this should be it.

And now you can do it simply and easily inside Google Analytics. Here’s how.

What is Lifetime Value (And Why Does it Matter?)

Metrics often lead you astray.

Take Cost Per Click.

They range wildly from industry to industry. $2 bucks in one industry, but $50 bucks in another.

Crazy, right? Surely that $50 is just “too expensive.”

Not necessarily, obviously.

The first easy answer is your break-even point. If your Cost Per Acquisition is less than your initial average order value, you’re golden.

But sometimes, in some cases, you actually want to willingly lose money initially.

Image Source

Ever heard of Netflix? How about Amazon?

Amazon routinely enters a new market with razor thin (or even negative) profit margins so they can grab market share. Only to then turn the dial back once they’ve gained a market leadership position.

Image Source

So what’s a reasonable Cost Per Click in that scenario? Now it depends.

This can even change from company to company within a vertical (and their appetite for risk).

Let’s talk insurance.

Two ways to make money:

Upfront commission when you close a sale

Ongoing residual payments over the life of each deal.

So you’ve got a new company. Entering a new market and trying to expand.

Would you willingly, purposefully sacrifice #1 in order to scale #2?

Of course you would.

Why? Because the lifetime value of a customer.

The full potential value of each new client you add will eclipse the initial commision. So as long as you can stomach the negative cash flow for a bit, you’d probably be willing to drive that Cost Per Click as high as humanely possible.

You go all in, when the stakes are right, and drive everyone else out.

All of this sounds perfect, except for one teeny, tiny detail.

Does your company track lifetime value? ‘Cause most don’t.

I’ve personally worked with dozens (hundreds?) of clients over the past few years and I can count on one hand the number who were actually tracking conversions properly. Let alone seeing anything past the first purchase.

One of the reasons is because tracking this info, with current systems, isn’t always easy. It might be easy if you’re using a Shopify and do all sales in a single channel or two. That way, everything happens inside one platform.

But usually your business is spread out. Each department has their own independent systems. So it’s tough to bring everything together.

Thankfully, Google Analytics has been hard at work recently.

Their new Lifetime Value report helps business owners acquire data to understand how valuable certain users/customers are to their business based on their lifetime performance.

And best of all, it pulls together lifetime values for people acquired through different channels and mediums, like social, email, and paid search. You’ll also be able to view data by engagement (pageviews, goals, events) and then trends (like 90 days after customer acquisition).

Using this will help you determine which sources are driving the most valuable traffic and which corresponding marketing investments are truly delivering an ROI.

Here’s how to run a lifetime value report inside Google Analytics.

How to Run a Lifetime Value Report

Start by signing into your Google Analytics account and then follow these simple steps:

Step 1: Click on Reports Section Step 2: Click on Audience Step 3: Click on Lifetime Value

Note: The Lifetime Value feature should already be available inside your GA account (no need to change your code!).

Now let’s get started generating a report. Here’s how to setup your graph first:

Start by setting your acquisition date range (the option on the far right). Any customer acquired during this date range (May 2017 on this example) will be included in the LTV report.

Let’s say you ran a promotional campaign or online sale during the month of May, you can easily analyze the data for these customers and segment by date based on your campaigns.

For steps two and three, you can select the following list of metrics to compare:

Now let’s break this graph down a bit to help you understand what the heck is going on:

Essentially, this graph is showing site users acquired during the month of May, and how their lifetime value changes based on the page views and session duration metrics over a 90 day period on the site.

These are obviously engagement metrics, you can customize this even further to track the exact amount spent if you have eCommerce tracking enabled.

Now, let’s jump to the table below:

Now we’re able to compare the number of acquired users (and the Pageviews per User) in this case by acquisition channel.

Click on the dropdown above the table to pull up different granular sorting options like Source, Medium, or Campaign.

How is this helpful? Check it out:

Let me break it down:

Blue: Acquisition channel. This shows what channel the users were acquired through, i.e, direct, organic, social, referral.

Pink: Users. The amount of users in the specified acquisition date range (May 2017 in this example)

Purple: Your selected lifetime value metric. In this example, pageviews per user is the LTV. This column is where the data begins to get interesting.

Let’s zoom in on the last column in detail to see if there’s any insight we can already glean from these reports.

Now we start to notice patterns among the different channels. For example, Referral traffic has double the pageviews per user (LTV) than almost every other channel. While Organic pageviews per user (LTV) is beginning to fall behind.

Want to pull back the curtain even more? Like being able to see things what individual Referral sites are driving higher LTV’s?

Head back over to the “Acquisition Source” on your table. Now we can break down which individual websites are sending us the most valuable traffic (based on LTV). And the winner is…

Kissmetrics! What, what!

Here’s why this new insight important.

Data Lies. LTV Forces it to Tell the Truth

Data lies to you daily.

For example, pull up your Goals inside Google Analytics to conduct a similar analysis to the one we just did.

You can even view the Reverse Funnel Path to see which pages, posts, or campaigns delivered the most conversions. This report is helpful… to a point. If you understand its limitations.

For example:

❌ Problem #1. These could be subscribers or leads. Not solid purchases. So you’re basing hard decisions off of ‘top of funnel’ data.

One campaign or channel might send 100 subscribers while the other only sends 20. But none of this takes into account how many of those people are converting. Or even how much money each is spending.

❌ Problem #2. Oh, these are sales, you say? Ok.

Except for one thing: You can’t tell if they’re one-off or repeat. So you can’t tell if each customer is a $100 order or a $1,000 one.

Which is kinda important when you’re looking backwards to see how that content investment performed vs. the paid campaign.

❌ Problem #3. A/B tests lie, too.

Things start off great. That new button resulted in a big conversion rate leap.

The only problem is that these small, temporary fluctuates often regress back to the mean. Larry Kim likened it to “moving desk chairs around the Titanic.”

Image Source

There might only be a literal surface level change, without ever fundamentally improving the organization as a whole.

When does this commonly happen? When you over-optimize.

❌ Problem #4. Over-optimization.

A/B tests that increase top line metrics often backfire.

For example, another study from Larry Kim showed that for every increase you made in a conversion rate, the lower your rate of Marketing Qualified Leads.

Image Source

In other words, the more aggressive you at are collecting that initial opt-in or lead can often lower the overall quality of the leads that are getting in. Which doesn’t make a whole lot of sense in the grand scheme of things when you think about it.

The point is that there are many, many ways data often lies to us. We think we’re seeing the whole picture, when in reality, it’s only a tiny slice of it.

Conclusion

Metrics aren’t always they appear. And data often lies.

What’s an “expensive” Cost Per Click for one business, isn’t for another. And sometimes that overall conversion rate we’re looking at to base our decisions around is fraught with peril in reality.

The one savior is Lifetime Value.

It gives us a broader, big picture context when viewing other bits of information. It helps us put things into proper context.

So we can not only make better decisions to drive additional revenue. But also realize when we’re about to make a few costly mistakes.

About the Author: Brad Smith is the founder of Codeless, a B2B content creation company. Frequent contributor to Kissmetrics, Unbounce, WordStream, AdEspresso, Search Engine Journal, Autopilot, and more.

How to Use the New Lifetime Value Feature in Google Analytics