Experiments & attribution: prove a sort lifts sales

A better sort should mean more sales — but “should” isn’t proof. QSortby lets you test a sort against your current order and measure what it actually earned, so you ship the version the data supports instead of a hunch. This is the honest answer to “which sort maximizes conversion value”: you don’t guess, you run the experiment.

Two ways QSortby shows lift

• Per collection — the Activity tab. Every collection’s Activity tab compares click-through before and after QSortby took over and shows the uplift, plus a run-history log. It’s the quickest read for a single collection.
• Best Sellers block & For You feed — Experiments. For the storefront feeds, the Experiments page runs a live A/B test between your current order and a new sort, and reports the full funnel with a significance verdict. That’s what the rest of this guide covers.

Run an A/B experiment

Left menu → Experiments → start a new experiment. Choose the surface to test — the Best Sellers block or the For You feed — and the sort you want to try. QSortby then serves two versions side by side:

• Control (A) — your current order.
• Variant (B) — the sort you’re testing.

Visitors are split deterministically: the same shopper always sees the same version for the life of the test, so the comparison stays clean.

Read the funnel

For each version, QSortby tracks the whole path from the storefront:

1. Impressions — how often the feed was seen.
2. Click-through rate (CTR) — clicks into a product from the feed.
3. Add-to-cart — the step before purchase.
4. Influenced revenue — orders attributed back to the feed a shopper engaged with.

Comparing A and B across these tells you not just whether more people clicked, but whether the sort moved shoppers all the way to a purchase.

Let significance call the winner

A version can look ahead by chance when traffic is low. QSortby waits until each version has enough impressions, then reports a statistical-significance verdict — how confident it is that the leader is genuinely better, not noise. Ship the variant once it’s a significant winner; keep running if it’s still too close to call.

Attribution: the revenue a sort influenced

Left menu → Attribution shows the orders a QSortby feed helped drive, with the influenced revenue behind them — broken down by surface, variant and the position a product was shown in. It’s the money view that sits underneath the experiment funnel.

A simple workflow

1. Pick a collection or feed you want to improve.
2. Try a signal that fits it — see the How QSortby ranks guides — e.g. Best converting or Trending.
3. Run it as an experiment against your current order.
4. Wait for significance, read CTR → add-to-cart → influenced revenue.
5. Ship the winner; then test the next idea. Small, proven steps compound.