---
title: "The Holy Grail in AI Marketing Will Make Everything Wonderfully Terrible"
description: "Using consumers' digital footprints to simulate them as shoppers lets you infinitely pre-test marketing campaigns for the desired result."
kind: "article"
section: "Society"
author: "Josh Alley"
author_url: "https://hastalavista.ai/authors/alley"
published: "2026-10-11T18:06:18.932Z"
updated: "2026-10-11T18:49:17.783Z"
canonical: "https://hastalavista.ai/society/the-holy-grail-in-ai-marketing-will-make-everything-wonderfully-terrible"
---

# The Holy Grail in AI Marketing Will Make Everything Wonderfully Terrible

*Using consumers' digital footprints to simulate them as shoppers lets you infinitely pre-test marketing campaigns for the desired result.*

By [Josh Alley](https://hastalavista.ai/authors/alley) · October 11, 2026

Imagine you could hit a button and spin up 10,000 consumers in a target demographic, just like you can spin up 10,000 cloud servers in a particular region today.

The consumers would be modeled after real consumer data, and an AI agent would be the interface. You could then test & re-test campaign ideas, ask questions on preferences, and get insight from the consumer on what would work better to entice them to buy.

Would it be perfect? Nope. Would it be pretty accurate? Yep. And would it be a huge step up from most shotgun approaches today? Most definitely.

You could *simulate* whatever customer demo you wanted, whatever *single* customer you wanted, and use AI to crunch the numbers on the best approach to get them to buy, across an infinite number of attempts, before presenting the winning one to the real consumer.

Let's make the case that #1 this is possible today and will happen, and #2 this is wonderfully terrible.

## You have an enormously rich digital footprint and it's big business.

There's ***a lot*** about you online, and you may not realize it. A good chunk of it is public data, too: property deeds, tax records, court filings, voter rolls, marriage & divorce records, professional licenses, and often DMV data.

![Example of public data available. Travis County property tax search.](https://oli14uru1ac8n1u4.public.blob.vercel-storage.com/media/b1d2dd5a-9600-4925-8908-190d9ab4d30c/1600.webp)
*Example of public data available. Travis County property tax search.*

Then, there's the enormous treasure of all the private data: purchase histories, warranty registrations, any and all subscriptions, contest entries, where you've signed up, where you've clicked, what you've bought, and often, what you've said, including things like search & browser history. And in this casino economy, real-time auction data and what you gamble on are within purview.

![Acxiom API](https://oli14uru1ac8n1u4.public.blob.vercel-storage.com/media/18278a09-5f1e-43bd-a081-077db6eb05ec/1600.webp)
*Acxiom is a large data broker. This is API documentation showing a partial list of what they track.*

Of course, then you have a phone in your pocket with GPS capabilities. Your location is being beamed out all of the time, often on purpose and by design, sometimes by accident. Your newer car is designed in the same way.

> **Related:** [FTC Takes Action Against General Motors for Sharing Drivers’ Precise Location and Driving Behavior Data Without Consent](https://www.ftc.gov/news-events/news/press-releases/2025/01/ftc-takes-action-against-general-motors-sharing-drivers-precise-location-driving-behavior-data) (Federal Trade Commission)
>
> The Federal Trade Commission is taking action against General Motors (GM) and OnStar over allegations they collected, used, and sold drivers’ precise geolocation data and driving behavior to data brokers.

And of course, let us not forget social media. Remember Facebook & Cambridge Analytica?

> **Related:** [Facebook–Cambridge Analytica data scandal](https://en.wikipedia.org/wiki/Facebook%E2%80%93Cambridge_Analytica_data_scandal) (en.wikipedia.org)
>
> In the 2010s, personal data belonging to millions of Facebook users was collected by British consulting firm Cambridge Analytica for political advertising without informed consent.

To be fair, sometimes this data isn't sold on purpose. But data breaches are a thing, where through hacks or social engineering bad actors will obtain all the private data on you, including passwords, and put it out for sale.

> **Related:** [Have I Been Pwned: Check if your email address has been exposed in a data breach](https://haveibeenpwned.com/) (Have I Been Pwned)
>
> Search tens of billions of breached records, monitor corporate domains via API, and get alerted when credentials are exposed. Trusted by security teams, MSSPs, and government agencies worldwide.

Brokers then get their hands on this data and work to ensure it's as accurate as possible. The more accurate, the more recent the data, the more valuable.

Part of the process includes enriching the data with inference about the consumer — attaching attributes like "likely diabetic," "new parent," "gun owner," "LGBTQ-interested." This inference gets supercharged with AI.

> **Related:** [Rockefeller: Data Broker Practices Raise Some Serious Consumer Protection Concerns - U.S. Senate Committee on Commerce, Science, & Transportation](https://www.commerce.senate.gov/press/dem/release/rockefeller-data-broker-practices-raise-some-serious-consumer-protection-concerns-2013-12/) (U.S. Senate Committee on Commerce, Science, & Transportation)
>
> WASHINGTON, D.C. — Chairman John D. (Jay) Rockefeller IV today gave an opening statement at the U.S. Senate Committee on Commerce, Science, and Transportation hearing titled, "What Information Do Data Brokers Have on Consumers, and How Do They Use It?" Below are his remarks as prepared for delivery:

This data then gets sold to marketers. If I want to sell a gold-plated AK-47 with a Pride flag on it, that's quite the specific audience. I can query and buy the data that I think would best fit the objective, based on how rich the data actually is. I can use it to find my people.

Other buyers of these kinds of digital profiles are credit bureaus, risk advisors (think insurance, legal, law enforcement), the government, phonebook sites, and more.

Your digital footprint, today, is used to perfectly target you for anything it thinks is relevant. Ever search for something online, only to get a non-stop firehose of ads for adjacent products? That's your data in action, not a conspiracy theory. It's efficient marketing from your rich data.

## AI can emulate characters based on a set of written instructions, with the more data the better.

There's a huge economy of "Her"-like companion AIs, and some that are targeted at kids. You can make an AI agent in the image of whatever you want, fine-tune the personality, and have it be your pal. It's designed to convince you it's a real companion, and the measure of its success would be in the LTV of a customer. The longer they stay in the service, and the longer they engage with the companion, the deeper the emotional dependence on the AI becomes, and the more the kayfabe drops to the subconscious.

> **Related:** [AI Companion Concerns Grow as Lawmakers Step In](https://hastalavista.ai/mind/ai-companion-concerns-grow-as-lawmakers-step-in-global-dating-insights)
>
> Lawmakers are moving to regulate AI companion chatbots amid reports of users forming dependencies and deaths linked to the apps, a push with the highest stakes for children who use them.
>
> *Human take:* AI companions are a mix of pro and con, like everything. But should we get our kids hooked on these early?

> **Related:** [AI Agents Simulate 1,052 Individuals’ Personalities with Impressive Accuracy | Stanford HAI](https://hai.stanford.edu/news/ai-agents-simulate-1052-individuals-personalities-with-impressive-accuracy) (hai.stanford.edu)
>
> Scholars hope these generative agents based on real-life interviews can solve society’s toughest problems.

> **Think about it**
>
> Imagine instead of a few inputs to flesh out your AI companion, you had social media posts to learn writing style. Imagine you had images to analyze to get a sense of their fashion — or even just all of their purchase history over time, to see how their styles evolved with time.
>
> Have a YouTube presence? Those can be "watched" by AI to evaluate speech, mimic intonation. The tech to analyze and emulate human speech is kind of old news, it's been out for a bit.
>
> You'll be able to tell if they use nicotine pouches, where they live (including over time, sometimes up to the minute), and intuit so, so much about them. Do they like movies? Which ones? Is their search & watch history peppered with clips of movie quotes?
>
> Now imagine their chat history with AI being linked with it. Shazam!

If you've worked with AI agents, especially 1-2 years ago, you know that generally, the more specific instructions you provide, the better results you get. The more context that is there, the more the AI can work with. That's when "prompt engineers" became a thing, and the thought was, if you get really good at being able to get AI to do something, that's a super valuable job.

But no, that was always just a gap that would quickly close. Now, you can be pretty sloppy and still get fantastic results. But, *context* is still enormously helpful.

If AI wanted to emulate *you*, it would need a lot of context. And all of that context is there, today, and part of a ~300B data economy.

## Today, you can build an AI agent to be *you*.

This is even part of the value proposition — "answer my emails for me in the same way I would," for example. "If the email needs me, let me know."

This is an efficiency gain. "Look at my finances and show me all subscriptions." That's a thing today, too, which also vaporizes a good chunk of the business models of companies like Rocket Money.

LLMs themselves are on a bedrock of next-word prediction: they ingest a ton of context data, then are trained to calculate the probability of the next word, or token.

There are entire companies that exist to attempt to guess the next purchase of a consumer, only they're operating with limited context. Think "You may also like" sections on websites, which map complementary product relationships with some rudimentary knowledge on the customer's purchase history. Amazon is killer at this because customers have been feeding it their purchase preferences (by using Amazon) for years.

You can use AI, then, to take your enormous history of data from these brokers, and turn on a "thinking" version of you. This thinking version of you can then be asked to review 10,000 AI-generated versions of a landing page, get "your" feedback, and see which one is most likely to result in a purchase, given all the context about you and your previous history.

Same for everything — which ad works the best, which video stops the scroll, which testimonial, and so on. Everything, anything, it's all the same.

The result is a future where everything you see is on the money: perfectly curated to you, well beyond where we are today. More accurate, more weird if that's your thing, with all variations in between.

Don't get me wrong, I actually think curated, personalized advertising is a good thing. It's a dirty thing, but the consumer experience is better when I'm being shown things that are relevant. If ads are going to exist, and they are, then I'd prefer to see one about cowboy boots and not a Pride edition gold-plated AK-47. No offense implied, I support the cause, but that's not a relevant product for me at this time.

But what does a world look like where everything is as close to "perfect" as we can make it? I think it may suck, but more in a soul-crushing way than a "bad" way.

See, when the models started to come out this year that were truly *great* at software development, the software developer human at the helm had to experience that revelation: this is better than I am. Or: this got really good, really fast.

> **Think about it**
>
> Two things are true at once: this is undeniably good, and it makes me feel bad.
>
> That's my worry here: we can make advertising undeniably good through infinite A/B testing with a simulated target consumer — or 10,000 of them for a consensus — and it will be wonderful but terrible at the same time.
>
> Maybe, though, that's just for those who were born in the "old way." Maybe this is how it just works when there's a big leap in tech that makes its way into the world, displacing some but creating opportunity for others.
>
> Maybe this is also a natural part of life, where inevitably there's some ontological shock when a part of your world view collapses. Maybe it's just me.
>
> Maybe those born into AI, the AI-natives, find this all normal and well and good, because they don't have the experience of the past, and maybe that's normal and OK. I remember the rise of the internet having been born into it, and it felt natural. Maybe older folks had difficulty adopting or accepting it, and now the tables are turned.
>
> The scale though... it just isn't the same.

This goes beyond marketing, of course, as there's many different types of campaigns out there, including political ones.

Imagine wanting to convert the hearts & minds of a particular demographic in America, then being able to simulate them based on their real data, and then test infinitely until you arrive at the perfect message and approach.

I'd like to imagine it would be less accurate than figuring out what they want to buy. But I'm not sure. And that may just be a gap to close.

> **Related:** [Software Developers Are Not Okay](https://hastalavista.ai/mind/software-developers-are-not-okay)
>
> Baldur Bjarnason examines the strain among software developers as AI tools reshape their work, a preview of pressures other skilled professions are likely to face next.
>
> *Human take:* Hear it from the horse's mouth when they understand cars are here: AI is better than you at many forms of human skill, and AI will only rapidly improve and cover more ground.