Metrics to Retire and What to Track Instead

The original article from Search Engine Land is [here](https://searchengineland.com/stop-reporting-traffic-464083) For consumer brands selling on Amazon, this matters even more: AI discovery happens upstream, while conversion often happens on Amazon. So you need a measurement stack that connects AI visibility → buyer intent → Amazon outcomes. Metrics to retire (or demote hard) 1) Keyword rankings as the main KPI Rankings still help, but they don’t tell you if you’re being recommended in AI answers. AI can summarise the category without ever “rewarding” your #3 position. 2) Top-of-funnel organic traffic volume Traffic is easy to celebrate and hard to cash. Search Engine Land pushes the idea that visibility and outcomes matter more than raw visits in a zero-click, AI-heavy world. 3) Vanity impressions + CTR Useful as diagnostics, weak as business metrics. They don’t tell you if shoppers are choosing you. 4) “Generic AI visibility” scores with no receipts If a tool can’t show which prompts, which answer, whether you were cited/mentioned, it’s not something you can operate. 5) “SEO traffic” as the north star For Amazon-first brands, the scoreboard is: Amazon sessions, conversion, contribution margin, review velocity. Everything else is supporting signal. Modern metrics to track (what actually moves revenue) Search Engine Land’s guidance on AI-era measurement keeps circling the same pillars: track brand presence in AI answers, citations, and visibility across AI platforms. Here’s how to translate that into an Amazon-brand dashboard. 1) Prompt monitoring (your new “rank tracker”) Create a monthly “prompt set” of 25–50 real buyer questions, like: “best [category] for [use case]” “[ingredient/material] safe for [audience]?” “[your brand] vs [competitor]” “what size [product] should I buy?” “does [product] work with [compatibility]?” Track: are you included, and where? 2) Brand mention rate in AI answers Out of your prompt set, what % of answers mention your brand by name? Track: mention rate overall + mention rate for high-intent prompts (comparison, best-for, compatibility). 3) Citation rate (when AI provides sources) When citations/links are shown, how often does your site get referenced? Search Engine Land highlights citations as a key AI-era visibility signal and has published analysis on AI citations across industries. Track: citation rate and which pages get cited. 4) Recommendation inclusion rate (AI “shortlist share”) For “best of” prompts, log whether you show up in the shortlist and how often you’re top 1–3. Track: shortlist share by category segment (e.g., “for sensitive skin,” “budget,” “premium,” “travel”). 5) Higher-intent engagement that leads to Amazon outcomes Don’t just measure sessions. Measure behaviour that predicts conversion: - Clicks to Amazon (use Amazon Attribution where possible) - Storefront visits - Branded search lift on Amazon (proxy for demand creation) - PDP conversion rate and review velocity trends This is how you connect “AI visibility” to money. Bottom line Retire the metrics that reward noise. Track what AI actually rewards: presence in answers, citations, and recommendation share. Then tie it back to Amazon conversion signals. That’s the new scoreboard.