Data Dive can break keyword/search data down to the variation level (color, size, etc.), revealing which specific variants actually drive a listing's sales.
Best-selling listings typically have one "hero" variation that absorbs the bulk of traffic and ad spend. Once shoppers land on the listing via that hero variant, a portion convert to buying the other, lower-demand variations instead — the hero acts as the entry point for the whole listing, not just for itself.
High search volume for a given variation does not automatically justify launching that variant. It has to be evaluated on whether it can become (or piggyback off) a hero variation, not as a standalone opportunity.
Data Dive aggregates search terms and volume at the variation level (e.g. "blue toiletry bag"), showing which color/size variants each competitor ranks for and how much of their sales or traffic ties to a specific variation. Checking this before launch clarifies which variants are worth carrying, and underlies the hero-variation pattern above: best-selling listings typically concentrate ad spend and ranking effort into one generic, low-cost hero variation, then convert shoppers to other variants once they land on the page, rather than spreading traffic evenly across all variants.
The hero variation isn't just the variant with the best individual keyword demand — it's a deliberate loss-leader role: a single cheap, generic-colored SKU chosen specifically to absorb traffic and ad spend for the whole multi-variant listing. Buyers land on the page via the hero variation's ads and search ranking, then convert to pricier or less-common variants once they're already on the listing. The hero variation's job is to be the cheapest entry point that gets clicks, not necessarily the highest-margin or best-selling variant itself.