How to Build a Predictive Audience That Performs Across Elite Retail Media Networks in 2025

Let’s get tactical. Retail media networks are powerful. But only if you’re feeding them the right audience. That means not relying on out-of-the-box segments that every other brand is using. And not limiting your strategy to one retailer’s walled garden. If you want to grow across RMNs—Amazon, Walmart, Kroger, Instacart—and beyond, you need portable, predictive audiences that travel.

The good news? You don’t need to guess.

There’s a proven playbook for building audiences that perform across every platform. 

Step 1: Start With the Right Seed Audience

This is where most brands miss the mark. They either start with a CRM list that’s too broad, or a purchase history segment that’s too generic. Or worse, no seed audience at all, just “people who like snacks” or “moms aged 25–54.”

Here’s how to get it right. Your best-performing audience likely includes:

• High LTV customers
• Frequent purchasers
• Cross-category buyers
• Loyalty members with a high engagement score
• Recent purchasers (recency > relevance)

You want behavior-based, not just demographic-based.

Say you’re a frozen breakfast brand. Instead of just targeting “grocery shoppers,” you could define your seed audience as: People who purchased 2+ of your protein waffle SKUs in the last 60 days AND opened a recent promo email about a new flavor.That group gives you both purchase behavior and engagement signals. 

Perfect starting point.

Step 2: Enrich With External Predictive Signals

Now the real work begins. Your seed audience is valuable—but limited. It only shows what your customers did with you. To build a predictive model, you need to know what they’re doing everywhere else.

This is where enrichment comes in.

What to Layer In:

• Mobile location data: Where they shop beyond your brand
• App usage: What health, finance, or lifestyle apps they use
• Content consumption: What topics or creators they follow
• Household demographics: Income, family size, ZIP-level trends
• Retail affinity: Where else they buy (e.g. Target vs. Whole Foods)
• Purchase signals: Category-level buying behavior outside your SKU

Say you’re a non-dairy milk brand trying to expand into Kroger. Your existing Amazon data tells you your buyers are:

• 70% female, 25–45
• Subscribers to your 3-pack bundle
• Coastal metro ZIP codes

Now enrich that audience with Skydeo data, and you learn:

• They visit Trader Joe’s weekly
• They use recipe apps with vegan meal plans
• Many have loyalty cards at Kroger but haven’t bought your brand yet
• They’re price-conscious, but value sustainability claims
  

Suddenly you’ve got a real playbook.

Step 3: Build Lookalikes Based on Shared Behaviors

Now that you’ve enriched your audience, it’s time to scale. This isn’t just about cloning emails or targeting ZIP codes. It’s about finding patterns—and using them to build lookalike models that actually work.

A great lookalike model is trained on:

• Real behaviors (not just age/gender)
• Cross-channel activity
• Predictive traits (not just reactive ones)
  

Let’s say your predictive seed audience includes:

• Women who buy non-toxic cleaning products
• Also buy baby products
• Use budgeting and parenting apps
• Shop at Target and Costco

Now you can build lookalikes based on those behaviors and activate across:

• Amazon (product ads)
• Walmart Connect (household + baby category targeting)
• CTV (connected homes with toddlers)
• Meta (interest-based creative around sustainable parenting)
• Email (segmented promos by purchase recency)

These are not generic “green moms.”

They’re predictive segments tied to real shopper behavior.

Step 4: Activate Across Channels (Not Just RMNs)

This is where most marketers stop. They build a predictive audience—and then only run it inside one RMN. Big mistake. A good predictive audience should travel. That’s the whole point.

Once you’ve built a high-performing audience, activate it across:

• RMNs (Amazon, Walmart, Kroger, Instacart)
• CTV and programmatic (via platforms like The Trade Desk)
• Meta and TikTok (via custom audience uploads)
• Direct mail and email (via matchback or CRM activation)

Say you’re a DTC supplement brand launching in physical retail. Use your DTC subscriber list as a seed, enrich it with Skydeo, build lookalikes, and then:

• Target those audiences on Instacart when they add similar products to cart
• Show them mid-funnel content on CTV during workout shows
• Retarget engaged viewers with a shelf-availability ad for CVS
• Drive to a promo landing page tied to store-level availability

One audience. Four channels. One coordinated message.

That’s how performance scales.

Step 5: Measure What Matters (Hint: It’s Not Just ROAS)

Here’s what happens when you don’t own your audience strategy:

• Every RMN reports its own version of ROAS
• There’s no consistent audience overlap
• You have no idea what’s driving incremental lift
• Campaigns become one-offs, not a learning loop

Instead, build a measurement framework that tracks:

• Unified reach and frequency
• Incremental sales across retailers
• Cross-channel contribution
• CAC by segment or lookalike group
• Repurchase rates and LTV (when identity resolution is in place)

The goal isn’t to spend on RMNs.

It’s to build predictive growth engines that you control, optimize, and scale.

Audience is Everything

If you want to win across retail media networks, you can’t just optimize placements. You have to own the audience. That means knowing who your best customers are—not just inside one retailer, but across every platform they touch. It means turning behavior into insight, and insight into scalable, cross-channel execution.

And it means building a predictive engine that performs whether the ad shows up on Amazon, Instacart, CTV, or TikTok.

The best marketers aren’t guessing anymore. They’re building smarter predictive audiences—and making them work harder.

Want Help Building Your Predictive Audiences?

Skydeo gives you:

• Predictive enrichment for CRM, loyalty, and DTC lists
• Lookalike modeling based on 30,000+ behavioral traits
• Activation across RMNs, CTV, programmatic, and social
• Identity resolution for cross-channel coordination

– Try Skydeo SAM for free and start scaling smarter.

Learn More About Retail Media Networks:

Retail Media Networks Are Blowing Up—But Most Brands Are Only Getting Half the Value

The Hidden Cost of Retail Media Networks: Why First-Party Data Alone Isn’t Enough
Retail Media Networks Without Measurement Are Just Expensive Guessing