# Showing different lookbooks by browsing interest on a fashion storefront

Asked by Carolina Vidal on 2026-07-07. Tags: shopify, hydrogen, personalization, fashion, cql.

Hola! First the merchandising brief, then the question.

Our brand sells dresses, sneakers, and accessories. The merchandising team wants
the homepage lookbook to follow what each shopper actually browses: someone deep
in the sneaker collections should come back to a sneaker lookbook, someone
browsing dresses gets the dresses edit, and so on.

We got a Dynamic Yield quote that started at 35k a year plus weeks of onboarding,
which is not realistic for us right now. We are on Hydrogen with the Croct SDK
already tracking events. How is this kind of interest-driven content modeled
with the events we already have?

## 2 answers

### Answer from Rosa Delgado (2026-07-07)

This maps pretty directly to interest audiences, and you likely need zero new
tracking code.

Product, collection, and search views are auto-tracked by the Hydrogen SDK,
and those events feed the interest signals on the profile. So a shopper who
keeps opening sneaker PDPs and the sneakers collection builds up that interest
automatically.

Interest conditions are built into CQL:

```cql
user has shown interest in ["shoes", "clothes"]
```

You would define one audience per interest group (sneakers, dresses,
accessories) using conditions like that, adapted to your catalog.

For the content side, the lookbook is one slot. You create an experience per
audience, each serving its own lookbook variant, all managed from the
dashboard. When merchandising wants to change the sneaker edit for the new
season, that is a content change, not a deploy.

### Answer from Ben O. (2026-07-09)

Ran a very similar setup for a footwear client. Two practical notes:

Decide what the default lookbook is for shoppers with no interest signal yet,
because first-time visitors land before any browsing history exists. We used
the seasonal hero edit as the slot default.

Also give the audiences some overlap thought. A shopper can show interest in
both dresses and sneakers, and when multiple experiences match the same slot,
priority decides which one wins. Rank them deliberately instead of leaving the
order to chance.