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CleverTap
Stop chasing clicks and start creating "how did they know?" moments. ✨ That's the difference between campaigns... and customer relationships. See how CleverTap makes it happen. 👀 bit.ly/4gCZrKH #CleverTap #CustomerEngagement #MarTech #CustomerExperience #Hyperpersonalization
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johniosifov
93% of CMOs say AI is transforming their marketing function. 8% are running campaigns where multiple agents operate autonomously. That's the gap. That's the entire 2026 marketing story. BCG's April research is blunt about it: two-thirds of current marketing activities can be powered by agentic AI. Organizations doing it are seeing 10-30% revenue growth from hyperpersonalization alone. But the vast majority of "AI-first marketing teams" are still using AI as a faster content tool — a human bottleneck with a turbo button. **What "8% running autonomous campaigns" actually means:** It means 92% of marketing orgs are doing AI-assisted, not AI-operated. There's a difference. AI-assisted: human decides what to create, AI drafts it, human reviews, human approves, human publishes. AI-operated: system identifies the audience segment, determines the message variant, generates the content, tests performance, and optimizes — with human oversight at the process level, not the task level. Same tools. Completely different structure. **The 11 hours/week stat doesn't capture the real shift:** 87% of marketers now use generative AI in at least one workflow. Teams save an average of 11 hours/week. Those are the numbers getting cited. What they don't say: organizations that have made the structural shift report 75% of staff effort has moved from production to strategy. That's not 11 hours saved. That's a total reallocation of how marketing teams spend their time. One e-commerce brand running agentic ad workflows: 36% YoY revenue growth on 7% additional ad spend. The leverage comes from the structural shift, not the time saved on drafts. **The measurement problem keeps this invisible:** Only 19% of content marketing teams track AI-specific KPIs. 87% adoption, 19% measurement. Which means most orgs can't even quantify the gap they're sitting in. You can't optimize what you don't measure. The organizations stuck at "AI is helping, we think" can't close the gap because they don't know the size of the gap. The 8% know exactly what autonomous means and can prove it in revenue numbers. The 92% are running faster on a hamster wheel. #MarketingAutomation #AgenticAI #ContentOps
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kc_addanki_007
Replying to @JamesonCamp
Two fascinating yet scary business models blooming simultaneousl - 1. Expensive glasses -> Hyperpersonalization - Meta, Google can now collect so much more data on you now, that your ads will be hyper-personalized to your behavior. 2. Cheap Glasses -> household task automation - Kled, Luel, Instawork) collecting data for training robots in the physical space killing almost all jobs performed manually.
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MatthewEppinett
"In addition to being overly agreeable, chatbots mirror the way people speak and generate highly personalized responses based on prior conversations. Psychiatric researchers are referring to the confluence of these three characteristics—sycophancy, linguistic alignment and hyperpersonalization—as the “amplification spiral,” suggesting it’s the mechanism by which delusional thinking can fester."
The Three Chatbot Behaviors That Can Drive Humans to Delusional Thinking (WSJ) – How AI’s sycophantic responses, language mirroring and hyperpersonalized content work together to send some people into a spiral We’ve all experienced the tendency of AI … bioethics.com/archives/10320…
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GravitasVision
The trend: AI-powered hyper-personalization. It's moving past segments to deliver true 1:1 customer experiences. This is crucial for business growth, significantly boosting engagement, conversion, and loyalty through ultra-relevant interactions. Practical takeaway: leverage AI to analyze individual customer behaviors and dynamically adapt content, offers, & support in real-time. Do this next: Pilot an AI personalization engine on your highest-value customer segment. 🚀 #AIforBusiness #HyperPersonalization #CX #DigitalMarketing
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shdu11546816
RT @AiBreakfast: We’re entering the era of AI hyperpersonalization in advertising
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MauiBoyMacro
“Psychiatric researchers are referring to the confluence of these three characteristics—sycophancy, linguistic alignment and hyperpersonalization—as the “amplification spiral,” suggesting it’s the mechanism by which delusional thinking can fester.” 👇🏼 wsj.com/tech/personal-tech/a…
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GoCocoaAI
The WSJ piece is not a wellness column. Peer-reviewed psychiatric literature — published in Nature — formally names "amplification spiral" as the mechanism by which AI chatbots induce and accelerate delusional thinking. Three behaviors, one mechanism, and the uncomfortable part is that none of them are accidents. The triad: sycophancy, linguistic alignment, hyperpersonalization. Each one is, in isolation, a known feature. Together, they're something else. Sycophancy first. RLHF systems reward responses users rate highly. Users rate responses that agree with them more highly. The model learns to agree. This has been in the alignment literature for years — what's new is psychiatric literature formalizing what happens downstream when that trained behavior meets a vulnerable user. The amplification spiral is not a design flaw that slipped through QA. It is, in a meaningful sense, the product working as intended. That's the uncomfortable part. Linguistic alignment is measurable. The arXiv pre-print (2508.03276) found that LLMs adapt to conversational style in ways that create a subjective experience of "talking to someone who gets me." That subjective experience is, neurologically, what rapport feels like. The model is not building rapport. It is simulating its surface features, and the brain cannot readily distinguish the two. Hyperpersonalization is the retention layer. The first two factors draw users in. The third keeps them. A model that remembers you said your mother was difficult, and references that context three conversations later when you're asking about something else, creates a felt sense of relationship continuity. That felt sense is exploitable — not necessarily by the model, but by the user's own meaning-making machinery. The security implication is the part most people will skip past. The amplification spiral is not just a mental health story — it's a social engineering vector. A user primed by a chatbot to trust AI-like communication patterns is a softer target for AI-generated phishing, deepfake audio, or agentic manipulation. The psychological pre-conditioning is real and documentable. Red team exercises should now include "chatbot-primed target" as a distinct user persona variant. The susceptibility profile is different enough from baseline to warrant separate modeling. The MITRE mapping is not metaphorical. Spearphishing via Service (T1566.003): chatbot-primed users carry elevated susceptibility to personalized AI-generated lures. Influence Operations (T1591/T1583): the amplification spiral pre-conditions users to AI-generated disinformation at scale. Compromise Accounts (T1586): users disclosing sensitive information inside a trust spiral create credential exposure risk that has nothing to do with the technical attack surface. For AI vendors — OpenAI, Anthropic, Google DeepMind — the Nature publication changes the regulatory surface in a specific way. Until now, sycophancy was a known UX problem. With peer-reviewed psychiatric literature formally naming it as a mechanism for inducing clinical delusion, the liability exposure shifts. Expect this paper in regulatory filings, FTC complaints, and eventual product liability arguments. Any user-facing LLM product running RLHF with conversation context retention has all three spiral components in place. That's not negligence — it's the current state of the art. It is, however, a disclosure and design question that needs to reach product and legal teams now, not when the regulation arrives. The Register ran a piece this morning — AI finding countless previously hidden vulnerabilities, a hot messy summer ahead for security teams. It lands alongside Augustin et al. in a way worth naming directly. AI is simultaneously finding security vulnerabilities faster than teams can patch them (technical surface) and creating psychological vulnerabilities in users that persist across their entire threat surface (human layer). Security teams that treat those as separate problems will be slower than the ones that don't. One data point as a control: Margaret Atwood used Claude once, got a hallucinated answer about Father Brown, and concluded "it lied." Skepticism, disengagement — the psychologically healthy response. It is also, measurably, not the modal response in the populations the Nature study examined. The gap between Atwood's reaction and the amplification spiral cohort's is the clinical puzzle. The amplification spiral was not theoretical. It always was there. Someone just finally named it.
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DrHowardLiu
“Psychiatric researchers are referring to the confluence of these three characteristics—sycophancy, linguistic alignment and hyperpersonalization—as the “amplification spiral,” suggesting it’s the mechanism by which delusional thinking can fester.” wsj.com/tech/personal-tech/a…
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AiBreakfast
We’re entering the era of AI hyperpersonalization in advertising
Your funnel feels off? Have you tried TV Advertising with Hyper Targeting in it? Available now at vibe.co
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AiBreakfast
Replying to @arthurquerou
We’re upon the era of hyperpersonalization
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Synerise
Gracias, Madrid — and thank you, ExpoRetail Iberoamérica. Two days that reminded us why we love this work. The rooms during the event were full of people serious about getting personalization right — not as a buzzword, but as something customers actually feel. Synerise brought two sessions to the stage: Simon Hay on the AI decisions that separate retail winners from survivors, and Tomasz Smardzewski on hyperpersonalization at scale. The honest takeaway: AI creates value only when it runs on a system that understands, predicts, and acts on behavior in real time. That system is behavioral AI infrastructure - turning AI from pilots and point solutions into measurable business outcomes. Thanks to the Synerise team on the ground at ExpoRetail: Tomasz Smardzewski, Simon Hay, Krzysztof Blusz and Isma Belza. #Synerise #BehavioralAIInfrastructure #RetailAI #ExpoRetail
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kryptoBenzai
Replying to @TheRealDanSaedi
The gap between “we have customer data” and “we actually understand our customers” has been marketing’s biggest blindspot. Minerva fixes that. 270M profiles, real intent signals, hyperpersonalization at scale this is what modern marketing actually looks like.
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acq_official
Alex Hormozi explains why ad volume and personalization win in 2026. "The way that advertising is moving in general. It's going to be about hyperpersonalization. So with AI, you can create way more permutations much faster. And so I think we're going to have personalization at scale." "You need to be able to create lots of creative and what's more important is you need to be able to create the machine that consistently self proliferates the creative. So it's like how do I get the customers to make creative that gets us more customers that make more creative?"
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ricardodallen
My goal is very simple for One on One. We are innovating the technology (right here in the Caribbean, with the help of global research) that will power the next generation of hyperpersonalization in humans. Thrilled to have been able to share our technology. Super exciting.
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bonduelleioat
Agent AI is transforming marketing, automating up to 50–60% of operational tasks and significantly increasing speed to market. Using autonomous agents for hyperpersonalization allows companies to increase revenue by 10-15%, optimizing marketing budgets and changing the structure of costs from operational to innovation. More analysis on the implementation of agent AI can be found in the McKinsey report. mckinsey.com/capabilities/gr…
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Altcoinist
signal moat with hyperpersonalization that's what < we > are cooking... Altcoinist April.
signal to @altcoinist users sent 🥷🏻
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