How AI Is Reshaping Retail Media: The Difference Between “Algorithms” & Intentional Marketing

We’re entering a new era in retail media, one where AI isn’t just powering ad delivery, it’s actively shaping how consumers discover & interpret categories. & increasingly, the difference between good algorithms & intentional marketing systems is becoming impossible to ignore.

A recent example circulating in the industry illustrates this perfectly: a user typed “wellness” into two different retail platforms & received two very different experiences.

One platform, often cited as Target, responded with a broad, exploratory set of wellness-related categories: fitness, nutrition, mental health, sleep, self-care essentials, more. The experience felt like a discovery. It helped the shopper define what “wellness” could mean for them.

Another platform, by contrast, returned a much narrower interpretation: products whose titles explicitly contained the word “wellness.” Instead of expanding the shopper’s thinking, it constrained it to keyword matching. On the surface, both are “AI-driven” experiences. But in practice, they reflect two very different philosophies.

Algorithms vs Intentional Marketing Systems

Most retail media today still operates on a retrieval mindset:

• Match keywords

• Match product titles

• Optimize toward immediate conversion

• Prioritize what is easiest to score, not what is most helpful

  
  

This is algorithmic efficiency at its purest, but it’s also limited. By contrast, more advanced retail ecosystems are moving toward intentional marketing systems, where AI is used not just to respond, but to interpret intent. That shift changes everything.

Instead of asking:

“What products contain this keyword?”

The system starts asking:

“What is the user actually trying to accomplish?”

Why “Wellness” Is a Perfect Example

“Wellness” is not a product category. It’s a state of intent.

A shopper searching that term could be looking for:

• workout equipment

• supplements

• stress relief products

• skincare routines

• sleep improvement tools

• healthy meal options

A keyword-matching system flattens that nuance. It assumes “wellness” is a label, not a journey. An intent-aware system, however, recognizes that “wellness” is expansive & ambiguous & responds with structured exploration paths.

That’s the key difference:

• Algorithmic retail media = reactive

• Intentional retail media = interpretive

  
  

Why This Matters for Retail Media Networks

As AI becomes more embedded in retail media networks, the winners won’t just be the platforms with the best targeting, they’ll be the ones that understand meaning.

This impacts three major areas:

1. Discovery vs Conversion

If AI only optimizes for conversion, it risks skipping the discovery phase entirely. But discovery is often where brand preference is formed.

2. Category Creation

Intent-aware systems can effectively create new micro-categories in real time based on shopper behavior, rather than relying on static taxonomy.

3. Brand Equity

Brands benefit more when they are surfaced in contextually relevant ways, not just when they match keywords, but when they fit a broader intent narrative.

The Real Shift: From Keywords to Intent Graphs

What’s emerging now is a move away from keyword-based systems & toward what we can think of as intent graphs, AI models that map relationships between needs, behaviors, & product ecosystems.

In this model:

• “Wellness” is not a keyword

• It’s a node connected to dozens of sub-intents

• & AI decides which pathway to surface based on context, history, & behavioral signals

  
  

That’s a fundamentally different way of thinking about retail media.

Final Thought

The future of retail media won’t be decided by who has the most data, but by who knows how to interpret it with intention.

The gap between a system that “finds products with the right words” & one that “understands what the shopper is trying to do” is where the next generation of performance gains will come from.

& as AI continues to evolve, that gap is only going to widen.

-Malorie Ragsdale, MBA.

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