Are you a pre-cog marketer?

In Philip K. Dick’s “The Minority Report” (also a Tom Cruise movie), Dick imagines a future where criminals are arrested before they commit crimes. This is accomplished by humans plugged into machines (pre-cogs) who can see into the future by a few weeks and therefore tip-off the police before bad stuff goes down.

What if we, as marketers, could predict people’s desires and solve their problems before they happen? In psychology, they refer to this stage of pre-intent with the term “pre-contemplation,” the state-of-mind that occurs prior to knowing (But I’m a sci-fi fan so I gotta stick with pre-cog).

Granted, anticipating a someones needs is easier than predicting future crimes. But what’s a bit uncanny about our current moment, is that AI can do it too!

This means that ChatGPT can recognize a need, desire, or problem before its user does. This also means AI can suggest a solution or recommend a product before the user has considered searching for one.

In the same way that you might tell a friend that they should take a rest because they “look” tired, AI can gather signals and make recommendations through observations. I’ve experienced this myself in chats with AI, but I think that it’s going to become more and more common. ChatGPT can also “see” and “hear,” which opens up additional recommendation possibilities:

“Looks like your sink is leaking, would you like me to call a plumber?”

So how do businesses optimize their websites for what people DON’T type into a search engine like Google? How does do we do marketing in a pre-cog world?

Pre-cog marketing: targeting needs before they exist

The buyers journey is traditionally:

Awareness, Consideration, Decision, Retention, Advocacy

But what about what happens before “Awareness?”

Do you remember back in 2012 that Target made headlines for being able to tell when a shopper was pregnant before they knew themselves, simply based on their shopping habits. A father famously stormed into a Target store, angry about pregnancy-related coupons sent to his teenage daughter—only to apologize later when he discovered she actually was pregnant.

We’re getting better and better at predicting users online behaviors (or at least the companies who have access to the data are.)

Netflix, for example, analyzes viewing patterns to predict what shows you’ll enjoy, often more accurately than you could predict yourself.

Amazon’s recommendation engine famously drives 35% of their revenue by suggesting products you didn’t know you wanted.

And Spotify’s Discover Weekly creates playlists of music you’ll likely enjoy but haven’t heard yet.

These companies aren’t reading minds—they’re analyzing behavior patterns against vast datasets to identify correlations that even the customers themselves might miss.

Experience, Empathy, and Intuition

Tech giants like Facebook, Google, and Netflix collect hordes of data about us humans, and I’m sure it’s being used in all sorts of predictive ways to extract money from our wallets, but these Goliaths aren’t exactly gifting their data to marketers like you and me (and I don’t know if it would be a good thing if they did).

But we don’t necessarily need access to Google’s treasure troves of data to predict what people want and need. We already have the ability to use experience, empathy, and intuition to make pretty good predictions about what a given person might desire in a given situation (after all, this is how we did marketing before the internet).

Consider these more human “pre-cog” marketing examples:

• Before you even take a seat at the bar, the bartender mixes you the perfect drink based on the expression you are wearing when you walk-in
• A store owner notices your child’s anxious energy and keeps them occupied with a game, so you can finish your shopping
• A hotel manager decides to stock every room with phone chargers because he knows how easy and often visitors forget.

Anticipating needs isn’t new—but AI is adding a new layer.

LLMs: The new pre-cogs

We now have a new technology that, like humans, also has the ability to anticipate a user’s needs during the pre-cog stage (which is kinda nuts). And LLMs can do things that humans can’t. In some ways their ability to quickly parse large amounts of data may make them better at anticipating certain kinds of needs and desires then humans. And in many cases, they may redomend a product or service (it might even be your product or service).

Some examples of how this is playing out:

• A user mentions working from home to an AI assistant, which then suggests ergonomic office equipment before back pain becomes an issue
• Someone planning a trip to Iceland in ChatGPT receives recommendations for weatherproof clothing brands without explicitly asking
• A user discussing their new puppy with AI gets proactive suggestions about training resources and pet insurance options
• Someone mentioning their coffee tastes bitter receives suggestions for better brewing methods and specific coffee bean suppliers

New tactics for leveraging AI’s pre-cog abilities

Generative Engine Optimization is the term people are using to describe the act of optimizing your business so you can show up in ChatGPT and other AI tools. Some have questioned if GEO isn’t just new paint on an old building, because many of the strategies used in Search Engine Optimization (SEO) are transferable and can also improve your appearance in AI.

But I think this is a limited view, and it definitely lacks creativity.

Interacting with an LLM is not really a “search experience” like using Google. An LLM acts like an assistant, like another human. As we humans adapt to use LLMs more efficiently (just like we all once adapted our phrasing to make search engines work better for us), we will see new strategies emerge to help businesses get found online and through AI.

Here are a few emerging GEO strategies that go beyond traditional SEO:

• Creating narrative-rich content that demonstrates how your products and services could be super useful in various situations.
• Developing specialized industry glossaries that AI models can reference when discussing your field
• Building “conversational reputation” by engaging with AI tools and forum discussions in your area of expertise
• Crafting detailed comparative analyses that AI can reference when users ask about options in your category
• Creating decision trees and scenario-based content that mirrors how LLMs process decision-making
• Participating in knowledge base development for open-source AI models

Building a pre-cog marketing strategy

To capitalize on this shift towards predictive recomendations, businesses can:

1. Map the pre-contemplation triggers in your customer journey—what happens before they know they need you? AKA: TALK TO YOUR CUSTOMERS.
2. Create content addressing those triggers rather than just the active search phase
3. Build scenario-based training data that teaches AI when your solution is appropriate
4. Develop partnerships with complementary services that might be mentioned alongside your offering
5. Focus on trust signals that AI will recognize when determining what to recommend

The future of pre-cog marketing

I am not particularly encouraged by our current economic and political environment. Monopolies like Facebook and Google are exploiting small businesses and it makes me worry about the future. The rise of AI gatekeepers could potentially create yet another layer of intermediaries between businesses and their customers.

However, I hope that by being proactive, building community, sharing strategies, and by staying ahead and informed, we can be of some influence in how our world is evolving. We need to remain visible, relevant, and formidable. But I have hope.

Pre-contemplative or pre-cog marketing is actually a return to human-centered thinking and this is something small businesses excel at. Together we can build on some of our best human qualities like empathy and intuition and extend them with these new and powerful technologies.

Want to discuss more? Join me on slack. https://genengineoptimizers.com