How Under Armour Turns Fitness Data into AI Recs

Why does Under Armour have a recommendation advantage most brands can only envy? Because it knows not just what its customers bought, but how they train. Its Connected Fitness platform turns workout data into product recommendations grounded in real behavior, not guesswork.

The approach: Under Armour’s Connected Fitness platform uses AI to recommend products based on workout data — suggesting cooling gear for warm climates, base layers for cold regions — driving personalized, context-aware sales.

Recommendations grounded in real behavior#

Most recommendation engines work from shopping signals: what you browsed and bought. Under Armour adds a richer layer — actual fitness activity. Through its Connected Fitness apps, it understands what sports a customer does, where and in what conditions they train, and how often. That lets it recommend products tied to genuine need: cooling apparel for someone running in heat, base layers for cold-weather training, gear matched to the customer’s actual sport.

This is recommendation grounded in life, not just clicks — and it’s far more persuasive, because the suggestion answers a real, demonstrated need.

How recommendation AI works#

Recommendation AI predicts what each customer wants from data. Under Armour’s edge is the kind of data: behavioral fitness signals that reveal need directly.

Three mechanics drive it. The engine reads activity data — sport, climate, frequency — to understand real needs. It matches products to context, recommending gear suited to the customer’s actual conditions and goals. And it personalizes deeply, combining fitness behavior with shopping history for relevance shopping data alone can’t reach.

Why first-party behavioral data is the moat#

The strategic lesson is the power of unique, first-party behavioral data. Anyone can recommend from purchase history; Under Armour can recommend from how you actually train, which competitors don’t see. That proprietary signal produces recommendations that feel uncannily relevant — and builds a relationship (track your training, get gear that fits it) that’s hard to replicate. The data you uniquely own is the foundation of recommendations no one else can make.

What this means for your store#

You may not have a fitness platform, but you likely have unique data you’re underusing:

Identify the first-party behavioral data only you have — usage, preferences, context — and feed it into recommendations.
Match products to demonstrated need, not just past purchases.
Build experiences that generate proprietary data, deepening both relevance and the relationship.

The recommendations competitors can’t make come from the data only you have. Use it.

Bring recommendation AI to your store with CartAmplify#

CartAmplify brings data-driven recommendation AI to any store — Shopify, dropshipping, or marketplace. Turn the signals only you have into recommendations that feel made for each customer.

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Approach cited from publicly reported Under Armour Connected Fitness practices. Results vary by catalog, traffic, and implementation.