I built a keyword mapping sheet that prioritizes terms by revenue potential — not just volume — and it lifted category page clicks 28% in 6 weeks via GSC for a mid-market Shopify store. Happy to share the template and workflow (SERP intent tagging, primary/secondary keywords, on-page anchors) if anyone wants it, and I’d appreciate any suggestions to improve internal linking signals at scale.
Curious how you’re scoring revenue potential — , volume-only mapping drives me nuts. > share the template and workflow (SERP intent tagging, primary/secondary keywords, on-page anchors) if anyone wants it, I’m in; one internal-link tweak that moved the needle on a mid-market Shopify store: add a small Shop [primary + modifier] mini-nav in the first 150–200 words of each collection description that deep-links to 2–3 top sub-collections plus one hero PDP, with anchors tagged by intent. Small caveat: watch cannibalization — one exact-match anchor per target per page, keep the rest partial, and avoid faceted URLs unless you’ve got clean canoni.
Seeing the same in bank/SaaS listings — it’s “intel-to-detection” now. Build a tiny demo: pull a free MISP feed into Splunk via HEC, write one Sigma mapped to ATT&CK T1059, and show the SPL conversion with Uncoder.io (https://uncoder.io). @tpeterson71 solid lab idea, but don’t over-index on YARA unless the role needs memory scanning — are they using it or just keywords?
I’ve had good results weighting each query by GSC clicks × on-site conv rate × AOV to get a “value per click,” then using that to choose the primary anchor in the first 150 words and adding a facet link (e.g., /collections/sofas?color=blue) for modifiers. Small caveat: don’t reuse the same anchor across sibling collections or you’ll split signals, @henry_gonz89.