#Behavioral Data

[jcmarchi]

How AI Can Deliver the Consumer-Like Experience B2B Buyers Now Expect

New Post has been published on https://thedigitalinsider.com/how-ai-can-deliver-the-consumer-like-experience-b2b-buyers-now-expect/

How AI Can Deliver the Consumer-Like Experience B2B Buyers Now Expect

The B2B sales landscape is undergoing a rapid transformation. Economic uncertainty, shifting buyer expectations, and technologies like generative AI are compelling sales leaders to rethink how they operate. This shift is driven by the fact that B2B buyers now expect the same level of personalization, ease, and omnichannel engagement they experience as consumers. As a result, no deal is guaranteed, and static sales processes are no longer sustainable. To succeed, sales teams must embrace agility, innovation, and technology like never before.

Despite the numerous and diverse challenges, smart sales efforts yield significant results. We know that leaders who implement a growth mindset in their actions are likely to achieve success. Those who outperform on growth invest more aggressively in digital-led transformations and AI. It helps them boost sales and marketing productivity. The statistics show us that those that master innovation excellence see an additional four-percentage-points-higher cumulative total shareholder return growth than their peers.

To gain a deeper understanding of how successful B2B sales organizations use technology to improve accuracy and speed, our team spoke with more than 70 commercial leaders around the world to learn how they propel above-market, sustainable growth. We found that growth leaders in B2B sales are using AI to find new pockets of growth both within their core business and beyond. Here are four ways they are achieving this:

1. Use AI to spot white space opportunities

The first step to consistent B2B selling success is to spot the right opportunities. By analyzing vast datasets, AI can help sales teams identify fast-growing niches, engage with customers more effectively through micro-segmentation, and surface valuable opportunities.

For example, with the right information and setup, AI-enabled tools can suggest possible white space markets for existing products, identify new verticals, or brainstorm product development opportunities to use distinctive technologies in adjacent spaces. If the company can identify areas for new investment and swiftly capitalize on them, the routes to success will be rapidly increased.

Likewise, machine learning enables companies to segment customers by analyzing attributes that influence sales, prioritizing key customer groups, and tailoring offers accordingly. These insights inform decisions such as how to personalize value propositions or prioritize leads – all crucial to effective sales. These new opportunities to offer specific products or services in tailored ways to targeted customers, delivered at scale, can have a significant impact. What’s more, with B2B sellers’ growing taste for consumer-like experiences, the ability to segment accurately and to a high degree of granularity will become increasingly key to success.

2. Leverage AI insights for customer targeting and prioritization

AI can also help identify which potential customers are most likely to respond well to an approach, improving the flow of SQLs into the system.

For example, when combined with external data sources, gen AI can create a granular view of a company’s market. This includes a robust map of potential customers, projected spend by product line, current share by customer, and detailed customer data (such as industry, subindustry, purchase trends of similar customers, and location). When integrated with a customer relationship management (CRM) system, this information can be transformed into qualified leads by an inside sales team, which can thenbe turned into sales opportunities. This can significantly expand the new customer pipeline.

However, this technology is still in its infancy. Many B2B sellers are in the early stages of using generative AI. Just 21% of commercial leaders report that their companies have fully enabled enterprise-wide adoption of gen AI in B2B buying and selling, and 22% have only piloted specific use cases. So, there’s work to be done – but the results could be significant.

3. Delight and keep customers with AI-enabled engagement

It’s not enough to just find new customers and opportunities, though – strong sales organizations focus on retention as much as acquisition. Beyond finding new customers, AI is key to helping companies delight and keep their customers. By identifying patterns in customer behavior, sales teams can proactively mitigate churn risks and deliver more value through personalized follow-ups, ensuring long-term relationships.

For example, AI can help address churn by examining several factors such as pricing, service, or product features, helping sales leaders understand the reasons behind customer churn and when it might occur. By deploying analytical methods, including sentiment analysis and behavioral data in customer interactions, companies can better anticipate the key drivers and levels of future churn across different markets, business lines, and individual customers. Equipped with this knowledge, they can identify and implement proactive measures for effective retention.

Retention also flows from positive customer experiences of the brand itself, whether in the marketing materials they receive or the speed with which they can access answers to their questions and challenges. AI-enabled content targeting and chatbot communications, for example, can rapidly help enhance these key customer engagement channels, moving away from broad-brush, one-size-fits-all approaches and unhelpful, nuance-lacking bots.

4. Recognize that AI isn’t just tech, it’s a lever for growth

Despite growing enthusiasm for AI and other digital technologies, only 20% of B2B sales leaders can point to a proven track record of consistently implementing tech to drive outsize growth. Many are still in the early stages, experimenting with AI but not fully unlocking its potential. However, the companies that commit to AI as a strategic enabler—rather than just another tool—are already pulling ahead.

The message is clear: AI isn’t just a competitive advantage; it’s becoming the foundation of modern B2B sales. Those who embrace it now will be the ones to define the next era of growth—identifying untapped markets, acquiring high-value customers, and bui

[raybittechnologies]

Understanding the Internet of Behavior: Transforming Technology Through Personalization

We are no longer living in a ‘hyper-connected world’ where the technology has graduated from just connecting devices to understand and anticipate our needs, desires, and even our behavior. This is called the Internet of Behavior, an emerging concept building on top of IoT but adding a powerful layer of behavioral insights. IoB seeks to interpret data about human actions and patterns to offer tailored experiences, improve business outcomes, and even enhance public welfare. But it comes with ethical issues regarding its use on questions of privacy and proper applications for personal data.

What is the Internet of Behaviour (IoB)?

Internet of Behaviour is essentially the collection of user data that can be obtained from multiple sources including connected devices, social media, purchasing patterns, as well as location tracking for the understanding and predictability of human behavior. This includes taking a step further to analyze the data and hence creating actionable insights about the people using those devices when making the focus on gathering data from multiple devices in IoT.

This enables the IoB to analyze the “what” and “why” within the actions of users, thereby helping organizations provide more personalized services or tailor their offerings to accommodate particular needs, thereby influencing future user behavior in a directed manner.

How Does IoB Work?

IoB leverages a mix of technologies, including AI, machine learning, and big data analytics, to process and interpret data collected from various sources:

1. Data Collection: It collects data from different sources, including IoT devices, social media activity, browsing history, purchase history, wearable health devices, and mobile applications. Each of them provides evidence to a person’s behaviors, preferences, and motivations in more concrete manners.

2. Data Analysis: AI algorithms analyze such data to find patterns and correlations, which may signify particular behaviors. For example, analyzing what one browses and purchases might show purchase motivations, preferred brands, and needs.

3. Behavioral Insights and Actions: Now that the data is processed, it provides companies and organizations with the ability to decide upon how they engage the individuals. Such insights can be used in tailoring product recommendations, delivering targeted advertising, or even adjusting service delivery according to what resonates best with certain segments.

4. Feedback Loops: The other essential aspect of IoB is that it provides a real-time feedback loop. And while users respond to the customized services, IoB aggregates more data about the interactions that have been made, thus refining the accuracy of future predictions and allowing the systems to “learn” the user’s preferences in a deeper pattern over time.

Real-World Applications of IoB

IoB is already transforming various sectors, bringing personalized, data-driven experiences to users. Here’s how it’s being applied in some critical areas:

1. Healthcare and Wellness IoB allows medical professionals to create highly personalized treatment plans. Wearables, like fitness monitors and smartwatches, can track activity levels, heartbeat, and even sleep patterns. They can, based on this data, provide healthcare professionals with recommendations for lifestyle adjustments, remote monitoring of health, or even the prediction of possible medical problems before they worsen.

2. Retail and E-commerce Online vendors use the Internet of Behavior to learn users’ shopping behavior and styles for a more personalized recommendation, for which, with the information of how and what users prefer or spend on with their interest in products, can effectively be used by e-commerce sites to make recommendations most aligned with the tastes of the buyer, thus increasing conversion rates and loyalty.

3. Public Safety IoB data can be employed to facilitate city authorities to increase public safety through foot traffic patterns, climatic conditions, and previous incidents for the identification of high-risk areas and times. Resource allocation and proactive safety measures through predictive ability

4. Marketing and Advertising IoB greatly benefits the marketing industry. Considering that the behavior of online subjects is now analyzed, IoB can assist marketers in recognizing what message or offer works best for which particular audience segment. Even personalized ads, email campaigns, and dynamic web content are more accurate and attractive with the insight rendered by IoB.

5. Workplace Productivity Companies have just begun to apply IoB tools to understand patterns of employee workflows, communication habits, and other performance metrics. Companies can create a more effective workplace, improve the well-being of employees, and reduce burnout by making suggestions for breaks or changes in routines based on how people work best.

Benefits of IoB

Enhanced Personalization: Hyper-personalized services and products in IoB lead to increased customer satisfaction and brand loyalty.

Improves decision-making: Companies can even make more informed decisions based on their products, services, and marketing strategies to appeal directly to their users.

Predictive Capabilities: The IoB allows companies to anticipate or know the need or behavior of a customer, thus solving problems even before they develop, or it provides pro-active support to a customer.

Ethical and Privacy Challenges

While IoB offers numerous benefits, it also raises significant ethical and privacy concerns. Here are some of the main challenges associated with the Internet of Behaviour:

1. Privacy Risks IoB necessitates collecting elaborate data that is associated with privacy risks, as the study of users’ personal and sometime sensitive information is being monitored. Organizations need to be able to ensure that organizations can comply with data protection regulations like GDPR to guarantee the right protection of user privacy.

2. Data Security IoB relies heavily on data sources that could be termed easy preys for cyberattacks. Thus, data security and therefore tightening cybersecurity measures to protect associated sensitive information at large is important.

3. Ethical Use of Data IoB has influence as well as manipulation power over behavior; therefore, companies should ensure that data collected from IoB must be used responsibly without exploiting or manipulating the consumer. Transparency is also essential about data usage, and consent must be obtained.

4. Bias in Algorithms Since IoB relies heavily on AI and machine learning, biases in the algorithms can skew results at best and may influence decisions about people. Algorithmic fairness has to be considered because IoB cannot unfairly target or exclude certain groups of users.

The Future of IoB: What Lies Ahead?

Further evolution of IoB will spread its impact towards business and society as a whole. Future developments of IoB include more regulations concerning the usage of data, better technologies for transparency and security. Added with IoB could be Augmented Reality (AR) or Virtual Reality (VR) to create some immersive, behavior-responsive experience in gaming, education, and retail.

Responsible IoB will attract enormous attention because companies balance personalized services with respect to user privacy and ethical considerations. Inasmuch as responsible data is accorded, IoB will revolutionize the way we interface with technology and the world.

Final Thoughts

Internet of Behaviour leaps forward in data-driven insight, thus meaning organizations can serve people more customised and user-centric. But with all new opportunities comes a sense of responsibility by which business will need to ensure good deal of data management through ethical and secure means. Once matured, IoB would need transparency, trust and responsible data practices to make its maximum potential fruitful for the benefit of individuals, businesses, and society as a whole.

This balance of innovation and ethical responsibility makes IoB the key player toward a digital future transforming the ways in which we interact and expect from technology.

[encounteratnearpoint]

Just casually stroking your hand down your coworker’s back as you walk by…

[mostlysignssomeportents]

Ad-tech targeting is an existential threat

I'm on a 20+ city book tour for my new novel PICKS AND SHOVELS. Catch me TORONTO on SUNDAY (Feb 23) at Another Story Books, and in NYC on WEDNESDAY (26 Feb) with JOHN HODGMAN. More tour dates here.

The commercial surveillance industry is almost totally unregulated. Data brokers, ad-tech, and everyone in between – they harvest, store, analyze, sell and rent every intimate, sensitive, potentially compromising fact about your life.

Late last year, I testified at a Consumer Finance Protection Bureau hearing about a proposed new rule to kill off data brokers, who are the lynchpin of the industry:

https://pluralistic.net/2023/08/16/the-second-best-time-is-now/#the-point-of-a-system-is-what-it-does

The other witnesses were fascinating – and chilling, There was a lawyer from the AARP who explained how data-brokers would let you target ads to categories like "seniors with dementia." Then there was someone from the Pentagon, discussing how anyone could do an ad-buy targeting "people enlisted in the armed forces who have gambling problems." Sure, I thought, and you don't even need these explicit categories: if you served an ad to "people 25-40 with Ivy League/Big Ten law or political science degrees within 5 miles of Congress," you could serve an ad with a malicious payload to every Congressional staffer.

Now, that's just the data brokers. The real action is in ad-tech, a sector dominated by two giant companies, Meta and Google. These companies claim that they are better than the unregulated data-broker cowboys at the bottom of the food-chain. They say they're responsible wielders of unregulated monopoly surveillance power. Reader, they are not.

Meta has been repeatedly caught offering ad-targeting like "depressed teenagers" (great for your next incel recruiting drive):

https://www.technologyreview.com/2017/05/01/105987/is-facebook-targeting-ads-at-sad-teens/

And Google? They just keep on getting caught with both hands in the creepy commercial surveillance cookie-jar. Today, Wired's Dell Cameron and Dhruv Mehrotra report on a way to use Google to target people with chronic illnesses, people in financial distress, and national security "decision makers":

https://www.wired.com/story/google-dv360-banned-audience-segments-national-security/

Google doesn't offer these categories itself, they just allow data-brokers to assemble them and offer them for sale via Google. Just as it's possible to generate a target of "Congressional staffers" by using location and education data, it's possible to target people with chronic illnesses based on things like whether they regularly travel to clinics that treat HIV, asthma, chronic pain, etc.

Google claims that this violates their policies, and that they have best-of-breed technical measures to prevent this from happening, but when Wired asked how this data-broker was able to sell these audiences – including people in menopause, or with "chronic pain, fibromyalgia, psoriasis, arthritis, high cholesterol, and hypertension" – Google did not reply.

The data broker in the report also sold access to people based on which medications they took (including Ambien), people who abuse opioids or are recovering from opioid addiction, people with endocrine disorders, and "contractors with access to restricted US defense-related technologies."

It's easy to see how these categories could enable blackmail, spear-phishing, scams, malvertising, and many other crimes that threaten individuals, groups, and the nation as a whole. The US Office of Naval Intelligence has already published details of how "anonymous" people targeted by ads can be identified:

https://www.odni.gov/files/ODNI/documents/assessments/ODNI-Declassified-Report-on-CAI-January2022.pdf

The most amazing part is how the 33,000 targeting segments came to public light: an activist just pretended to be an ad buyer, and the data-broker sent him the whole package, no questions asked. Johnny Ryan is a brilliant Irish privacy activist with the Irish Council for Civil Liberties. He created a fake data analytics website for a company that wasn't registered anywhere, then sent out a sales query to a brokerage (the brokerage isn't identified in the piece, to prevent bad actors from using it to attack targeted categories of people).

Foreign states, including China – a favorite boogeyman of the US national security establishment – can buy Google's data and target users based on Google ad-tech stack. In the past, Chinese spies have used malvertising – serving targeted ads loaded with malware – to attack their adversaries. Chinese firms spend billions every year to target ads to Americans:

https://www.nytimes.com/2024/03/06/business/google-meta-temu-shein.html

Google and Meta have no meaningful checks to prevent anyone from establishing a shell company that buys and targets ads with their services, and the data-brokers that feed into those services are even less well-protected against fraud and other malicious act.

All of this is only possible because Congress has failed to act on privacy since 1988. That's the year that Congress passed the Video Privacy Protection Act, which bans video store clerks from telling the newspapers which VHS cassettes you have at home. That's also the last time Congress passed a federal consumer privacy law:

https://en.wikipedia.org/wiki/Video_Privacy_Protection_Act

The legislative history of the VPPA is telling: it was passed after a newspaper published the leaked video-rental history of a far-right judge named Robert Bork, whom Reagan hoped to elevate to the Supreme Court. Bork failed his Senate confirmation hearings, but not because of his video rentals (he actually had pretty good taste in movies). Rather, it was because he was a Nixonite criminal and virulent loudmouth racist whose record was strewn with the most disgusting nonsense imaginable).

But the leak of Bork's video-rental history gave Congress the cold grue. His video rental history wasn't embarrassing, but it sure seemed like Congress had some stuff in its video-rental records that they didn't want voters finding out about. They beat all land-speed records in making it a crime to tell anyone what kind of movies they (and we) were watching.

And that was it. For 37 years, Congress has completely failed to pass another consumer privacy law. Which is how we got here – to this moment where you can target ads to suicidal teens, gambling addicted soldiers in Minuteman silos, grannies with Alzheimer's, and every Congressional staffer on the Hill.

Some people think the problem with mass surveillance is a kind of machine-driven, automated mind-control ray. They believe the self-aggrandizing claims of tech bros to have finally perfected the elusive mind-control ray, using big data and machine learning.

But you don't need to accept these outlandish claims – which come from Big Tech's sales literature, wherein they boast to potential advertisers that surveillance ads are devastatingly effective – to understand how and why this is harmful. If you're struggling with opioid addiction and I target an ad to you for a fake cure or rehab center, I haven't brainwashed you – I've just tricked you. We don't have to believe in mind-control to believe that targeted lies can cause unlimited harms.

And those harms are indeed grave. Stein's Law predicts that "anything that can't go on forever eventually stops." Congress's failure on privacy has put us all at risk – including Congress. It's only a matter of time until the commercial surveillance industry is responsible for a massive leak, targeted phishing campaign, or a ghastly national security incident involving Congress. Perhaps then we will get action.

In the meantime, the coalition of people whose problems can be blamed on the failure to update privacy law continues to grow. That coalition includes protesters whose identities were served up to cops, teenagers who were tracked to out-of-state abortion clinics, people of color who were discriminated against in hiring and lending, and anyone who's been harassed with deepfake porn:

https://pluralistic.net/2023/12/06/privacy-first/#but-not-just-privacy

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2025/02/20/privacy-first-second-third/#malvertising

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[backwardscapcarlos]

(x)

[egophiliac]

I have never been more concerned for a JP update from your art than I am seeing a Cheka knowing the context of Leona’s dream.

My bois ok right?????? My sweet nephews ok right??????

well

uhhhh

I'm sure the real one is fine :)

[neopuff]

[mostly-natm]

can you draw bashir?

I can. The jury is still out on if I should.

[segretecose]

"i am 15% scandinavian 18% french 3% eastern europea-" okay well i will kill 100% of you

[itellmyselfsecrets]

“There are plenty of accounts of hostility from men when women venture into supposedly gender-neutral shared exercise spaces. Like transit environments…Gyms are often a classic example of a male-biased public space masquerading as equal access.” - Caroline Criado Perez (Invisible Women: Data Bias in a World Designed for Men)

[bananonbinary]

god i miss when the internet wasn't garbage. you can't google anything these days without whatever answer you're looking for getting lost under a deluge of seo ai bullshit. cannot wait until the bubble pops and we might get useable search engines again.

[wetslug]

yayyyyy participated in a fMRI research study on autism today. i hope i got a good score in autism, which is a normal and achievable goal

[hyper-lynx]

Oh God I'm thinking about rewriting my whole mod to be all data driven......... I already added KubeJS support I really don't have to do this, the people can already make reactions in modpacks !!

(But it'd be cool)

It would but, but...

[enterprise-bee]

constant war in my brain while watching TNG that goes like this:

one the one hand. fandoms having adult characters be “adopted” by other adult characters as a parent and child is a pet peeve of mine for how it forces those characters into roles that do not fit them and is frequently infantilizing. it doesn’t help that this is frequently done with characters that are neurodivergent coded in some way, stripping away their agency and competency in the name of a nuclear family archetype.

on the other hand. picard and crusher attending data’s first string quartet performance to support his interests and cheer him on… picard’s upset he got called away for the episode’s plot and couldn’t continue to support him… dad behavior.