Data EnrichmentMeasuring impact

A/B testing enriched content

The most convincing case for enriched content is a controlled split test on your own feed. This playbook walks through running one with the tools already in your Feedonomics account. You own the test and the analysis; this is the method.

Before you start

You’ll need your paid media data connected and your products tagged, since group segmentation relies on custom-label reporting in Google Ads — see Analytics onboarding and Measuring impact in Analytics. If you’re not ready for a full split test, the simpler baseline-and-holdout approach in Proving enrichment works is a reasonable first step.

The method at a glance

Diagram of the split test: test products are hashed per product and split fifty-fifty into a control group with original content and a test group with enriched content. The group is written to a custom label in the export, and Google Ads reporting compares CTR, conversion rate, and ROAS per group over two to four weeks.
One stable hash splits the products; one custom label makes the two groups comparable in Google Ads. Same market, same weeks, one variable.
1

Form a hypothesis

One variable, one expected outcome: “Enriched titles will improve CTR on our Google Shopping traffic.” Titles are the classic first test — they’re the highest-impact field.

2

Select your test products

Big enough for statistical significance, similar enough to isolate the variable. One healthy category beats a random scatter across your whole catalog.

3

Split 50/50

Assign each product a random group with transformers: generate a stable hash per product, then split on it — half to Control (A, original content), half to Test (B, enriched content). Keep variants of the same product in the same group so a single item group never straddles both arms.

4

Label the groups

Write the group assignment to a custom label in your export so you can segment by it in Google Ads reporting.

5

Run for 2–4 weeks

Track CTR, conversion rate, and ROAS per group per week. Don’t call it early — wait for significance.

6

Decide and repeat

Winner ships to the full catalog. Then move to the next hypothesis: descriptions are the natural second test after titles.

Caveats that save tests

  • Mind seasonality. Slow weeks depress everything; sale weeks inflate ROAS. Note anything unusual in the window.
  • Analyze Shopping campaigns, not Performance Max. PMax blends surfaces at the campaign level and will muddy your read.
  • Freeze campaign settings. Don’t change budgets or ROAS targets mid-test — you’d be testing two things at once.
  • Check your conversion tracking is revenue-based before you start, or ROAS comparisons are meaningless.
This is not Google Experiments

Google’s native Experiments feature tests campaign settings. This playbook tests feed data. They’re complementary — just don’t run both on the same traffic at the same time and expect a clean read.

After the test

A winning test tells you which field to enrich next, and in what order. Titles first, then descriptions, then the detail fields — Where enriched fields go shows what’s available per channel. To expand a winner across your catalog, run a larger batch with the same config: see Re-running enrichments.