intentCurrent: from search signals to sourcing decisions
intentCurrent is a research direction, not a product yet — exploring whether shopper demand signals can support better restocking and sourcing decisions.
Status: research direction. intentCurrent is not available and has no launch date. This post describes the question we are working on, not results.
The question
Merchants decide what to stock long before they know what will sell. Meanwhile, shoppers tell stores what they want every day — in what they search for, how they filter, what they click, and what they cannot find.
intentCurrent explores whether those signals can be turned into sourcing and restocking recommendations that sit closer to real demand — with the goal of less excess inventory and fewer shoppers leaving empty-handed.
How it would connect
- Shopper — search & discover. Shoppers look for products, apply filters and show what they care about.
- intentSearch — understand demand signals. Search behaviour gives merchants a clearer view of shopping demand.
- intentCurrent — support restocking. Demand signals, together with store performance, become the basis for sourcing recommendations.
Open problems we are studying
- Signal quality. Which search behaviours actually reflect purchase intent, and which are noise?
- Unmet demand. How to read no-result and low-result searches as demand for products a store does not carry yet.
- From signal to decision. How to combine demand signals with sales history so a recommendation is useful to a merchant, not just a chart.
- Evaluation. How to tell, before acting, whether a recommendation would have been better than what the merchant would have done anyway.
We will publish what we find — including what does not work — here on the Lab. Interested in piloting or collaborating? Write to contact@intentsea.com.