Analytics overview

FDX Analytics is where you see how your product data performs — on your site, in paid channels, and with AI engines. One dashboard, under Reports in the FDX navigation, with a shared date range and per-report filters.

If you haven’t connected your data sources yet, start with Analytics onboarding.

Why analytics matters

Enrichment and feed work cost real money, and analytics is where that spend turns into an answer. Enriched products’ clicks, conversion, and ROAS sit next to their own history — or next to the products you haven’t enriched yet — so when someone asks what the investment returned, you have a number instead of “the copy reads better.”

It also makes changing a live feed a safe thing to do. Most merchants know their titles could be better and leave them alone anyway, because touching a feed that’s driving revenue feels dangerous. With a baseline, a tagged segment, and a comparison period, you can roll a change out to one product group, watch it for a couple of weeks, and expand or retreat based on what the numbers did — not on nerve.

Some of what analytics shows you exists nowhere else. ChatGPT and Perplexity don’t send you reports, so the AEO report and the AI/LLM traffic channel are often the only place you’ll see which AI engines are reading your pages, which products they reference, and when their users arrive at your store. Treat it as an early visibility signal rather than attributed revenue — but it’s the difference between assuming AI matters and watching it show up.

And because enrichment usage is metered, analytics is how you spend the allotment well. When the reports show titles moved CTR in one category and nothing happened in another, the next batch plans itself: double down where the numbers moved, investigate where they didn’t. Each run makes the next one smarter.

The dashboard at a glance

Every view is a comparison. The date-range picker at the top pairs your selected period with a comparison period (for example, this year to date against the same span last year), and every metric on the page shows its change against that baseline.

Overview metrics summarize performance across all channels: total sessions, orders, revenue, conversion rate, and revenue per visit.

Below that, the dashboard is organized into three report areas:

Filters

Two levels of filtering:

• Dashboard-wide — the date range and its comparison period apply to everything on the page.
• Per report — each report has its own filters. Site Traffic filters by UTM source, UTM medium, UTM campaign, and page type; Paid Media filters by product, campaign, ad group, and custom labels (up to five).

The AEO report

The newest surface: how AI engines interact with your site. The report tracks total LLM requests, URL loads, image loads, and bot crawls, broken down by AI platform — ChatGPT, Perplexity, Gemini, Copilot, and Claude.

Two views are worth knowing:

• LLM channel performance — per-platform activity, including the specific bot names you’ll see (for example Claude-User, anthropic-ai, Perplexity-User), request volume, crawls, and pages indexed.
• URL performance by LLM — which of your URLs each AI platform is referencing, ranked by total references. This is where you see which product pages AI engines actually use.

Ask instead of digging

Everything on the dashboard can also be reached conversationally — ask the Feedonomics Companion a question in plain language instead of navigating the reports.

Measuring enrichment specifically

If you’re here to prove FDX Enrichment worked, the enrichment docs cover that workflow — required tagging, comparison methods, and which report answers which question: Measuring impact in Analytics.