Attribution

What is attribution?

Attribution is the process of working out which orders and revenue were actually influenced by a tool like Flockr, as opposed to which would have happened anyway. Flockr ships with attribution built in, so commercial impact is measured from real shopper sessions rather than taken on faith.

How does Flockr's attribution work?

It uses a two-group, session-level model. One group is sessions where a shopper clicked a product while a Flockr message was visible on a browse surface — a listing page, search, or recommendation. The other is every other session in the period. The two groups’ order rates are compared, the difference is reported as conversion rate lift, and it is monetised as incremental revenue. Bot sessions are excluded from both.

What is the product-scoped constraint?

For an order to count towards the Flockr group, the product purchased has to be the same one the shopper clicked while a Flockr message was visible. A session that clicked product A on a Flockr-visible listing and then bought product B does not count. This stops the model from claiming every purchase in the group as Flockr-influenced, and it is one of the things that keeps the figure conservative.

Is Flockr's attribution causal?

No, and it is careful not to claim to be. The model is observational, not a randomised experiment: the Flockr group self-selects by clicking, so it is higher-engagement than average, and some of the measured lift reflects that intent rather than Flockr itself. The product-scoped constraint reduces this but does not remove it. The honest reading is that the reported lift is an upper bound on the true effect — a commercial-grade estimate that is directionally reliable and good for tracking change over time, not the equivalent of an A/B test result.