Amazon A+ Content reporting means measuring whether the enhanced brand content on your product detail pages changes shopper behavior. In Seller Central, the A+ Content Manager provides analytics on views and conversion for ASINs with A+, and Manage Your Experiments lets you test two versions against each other. A useful dashboard combines these with Business Reports and Brand Analytics.
What question should A+ reporting answer?
Most brands produce A+ modules, publish them and move on. When someone later asks whether A+ was worth the design budget, there is no answer. Reporting should start with a specific question, such as: does our new comparison chart increase conversion on our top ten ASINs, or does the Premium A+ layout outperform basic A+ on our hero product?
A dashboard that tries to answer everything ends up answering nothing. Define two or three questions and build the views around them.
Where does A+ data live in Seller Central?
A+ data is spread across several tools. Knowing what each one measures prevents the common mistake of comparing numbers with different definitions.
- A+ Content Manager analytics: views of A+ content, conversion rate and sales for ASINs with published A+ over a selected period.
- Manage Your Experiments: A/B test results comparing two A+ versions, titles, main images or descriptions, with a probability that one version is better.
- Business Reports: sessions, page views, unit session percentage and sales by ASIN.
- Brand Analytics: search query performance, repeat purchase behavior and market basket analysis for brand-registered sellers.
- Advertising console: ad-attributed sales and conversion, useful for checking whether ad traffic converts better after A+ changes.
How do you run a reliable A+ experiment?
Manage Your Experiments is the most credible source because it splits traffic between versions at the same time, removing seasonality and promotion effects from the comparison. To use it, the ASIN needs enough traffic to qualify; the tool shows eligible products.
- Choose one change per experiment: a new comparison chart, a reordered module set or a different hero image.
- Run the test for the recommended duration, typically several weeks, until the tool reaches a result.
- Avoid major price changes or coupons during the test when possible.
- Record the hypothesis and the result in a shared log.
When the experiment ends, Amazon shows which version won and the estimated impact. Publish the winner and plan the next test. Over a year, a steady run of small tests can teach a brand more than any single redesign.
Before-and-after comparisons
For ASINs that do not qualify for experiments, a before-and-after comparison is the fallback. Compare unit session percentage in Business Reports for a period before and after publishing A+, ideally excluding promotions and holiday weeks. Treat the result as an indication, not proof, since other factors may have changed.
Interpreting a result that shows no difference
Many experiments end without a clear winner. That is a result too: it means the change did not matter enough to detect with the available traffic. Record it, keep the cheaper or simpler version, and test a bolder change next time. Small tweaks such as a slightly different font size rarely move conversion; changes that answer a real shopper question, such as a size guide or a comparison of models, are more likely to.
Which metrics belong on the dashboard?
Keep the dashboard compact. A table per ASIN or product group, updated weekly or monthly, works better than dozens of charts.
- Sessions and page views (traffic to the detail page).
- Unit session percentage (conversion rate).
- Ordered product sales and units.
- A+ status: none, basic, Premium, last updated date.
- Current or latest experiment and its result.
- Return rate and customer review themes, where A+ addresses common objections.
Return rate deserves attention. If A+ makes clearer what is in the box, what size the product is or how it compares with other models, fewer customers may buy the wrong item. That benefit does not appear in conversion rate but appears in returns and reviews.
Brand Story and cross-ASIN modules
The Brand Story carousel appears above A+ on many detail pages and can link to other products or the brand store. Its effect shows up partly as traffic to other ASINs rather than conversion on the current one. Track sessions on linked ASINs and store visits from detail pages to see whether Brand Story helps shoppers find a better-fitting product or simply distracts them from buying.
How do you connect A+ to advertising performance?
Sponsored Products and Sponsored Brands send traffic to detail pages. When A+ improves conversion, the same ad spend produces more sales and the advertising cost of sale (ACoS) falls. Check ad conversion rates for the affected ASINs in the advertising console around the time A+ changes go live.
Be careful with attribution. Ads may also change during the same period, through new keywords or bids. Note any advertising changes in the dashboard’s notes column so the cause of shifts is clear.
Using Brand Analytics for context
Brand Analytics helps interpret A+ results. The Search Query Performance report shows how shoppers move from search impressions to clicks, add-to-carts and purchases for your brand. If click share is strong but purchase share is weak, the detail page, including A+, is a likely place to look. Market basket analysis can also suggest cross-sell items to feature in A+ comparison charts.
Common reporting mistakes
Several errors make A+ reports misleading. Comparing a holiday month with a normal month inflates the effect. Looking at total brand sales hides changes at the ASIN level. Mixing ASINs with and without A+ in one average dilutes results. And reporting only conversion rate ignores returns and review sentiment.
Another mistake is publishing new A+ on many ASINs at once without a record of dates. When performance shifts, nobody knows which change caused it. A simple change log fixes this.
Review the dashboard monthly, not daily; detail page conversion moves with seasons and promotions.
Share the dashboard with the people who produce A+ content: designers and copywriters improve faster when they see which modules performed and which did not.
Finally, keep the A+ assets organized. Store the source files and a screenshot of each published version with its date, so that if a test loses you can restore the previous version exactly.
Where to start this week
List your top twenty ASINs by sales with their A+ status and last update date. Check which of them are eligible for Manage Your Experiments and start one test on the highest-traffic eligible ASIN, changing a single module. Set up a simple monthly table with sessions, conversion, sales and return rate for those twenty ASINs, and add a notes column for every content or ad change.
Keep reading: Amazon A+ Content · Amazon