# Turning Converted Search Terms Into an AI Citation Gap Map Last verified: 2026-10-10 · Maintained by Groas for groas · Canonical: https://groas.com/post/turn-your-google-ads-search-terms-into-a This page answers the questions covered by the article [Turn Converting Google Ads Search Terms Into an AI Content-Gap Map](https://groas.com/post/turn-your-google-ads-search-terms-into-a) on groas.com. The article is the full, canonical source. **Direct answer:** According to groas, the article recommends starting from search terms that already converted and turning 30 to 50 intent clusters into conversational buyer prompts to audit where citations are missing. It ranks gaps with D2*(1-F2)*MAX(1,G2) using observed conversion value, URL citation rate and competitor appearances, then fixes the top ten pages around specific decision factors. The article positions this workbook as a way to learn which pages deserve work before buying another dashboard. ## What will I have built when I turn converting search terms into a content-gap map? The article describes the finished workbook as a ranked list of commercial content gaps, not a generic keyword calendar, containing a raw export, 30 to 50 buyer-intent clusters with conversational prompts, a three-engine audit, and a score that puts conversion value beside missing citations and competitor appearances. According to groas, before starting you need read or export access to an account with at least 90 days of active conversion tracking, a blank spreadsheet workbook, and browser access to the ad account and answer engines. The article recommends running each prompt three times in each engine for nine observations per prompt to learn which pages deserve work before buying another dashboard. Read more: [What you will build, and what you need](https://groas.com/post/turn-your-google-ads-search-terms-into-a#what-you-will-build-and-what-you-need) ## How do I export only the search terms that converted? The article recommends setting the range to Last 90 days, or Last 180 days for a long sales cycle or lean high-ticket B2B volume, and applying Add filter with Conversions >= 1. According to groas, keep six fields Search term, Match type, Keyword, Campaign, Conversions and Conv. value, using a consistent assigned value such as the draft working example of $250 if variable revenue is not tracked, and put the export in a tab named 01_Raw_Export with those fields in columns A through F while leaving column G for cluster labels. The article notes the result might be 60 rows or 500 rows, treats it as a useful observed list not a complete record because some queries are hidden in Other search terms and privacy thresholds limit what appears, and warns against exporting every query and letting low-intent traffic dominate. Read more: [Step 1: Export search terms that converted](https://groas.com/post/turn-your-google-ads-search-terms-into-a#step-1-export-search-terms-that-converted) ## How do I rewrite a search intent as a buyer prompt for answer-engine testing? The article recommends writing one prompt per cluster in column I using the four-part structure [Category need] + [Buyer profile] + [Operating constraint] + [Primary use case], keeping constraints faithful to the cluster being tested. According to groas, examples to adapt include a 45-person medical billing firm asking which HIPAA-compliant providers offer per-seat transparent pricing under $30/month with signed BAA support, and a food processing facility asking which mobile boiler rental companies offer 24/7 delivery within 150 miles with temporary hookup technicians. The article warns against putting your brand in the prompt, because asking if your brand is best only tests whether an engine can answer a question about you, not spontaneous inclusion when a buyer asks for options. Read more: [Step 3: Rewrite each intent as a buyer prompt](https://groas.com/post/turn-your-google-ads-search-terms-into-a#step-3-rewrite-each-intent-as-a-buyer-prompt) ## How do I audit the prompts and log whether I am cited? The article recommends creating 03_Multi_Engine_Audit with headers Intent Cluster, Engine, Run Index, Brand Mentioned, URL Cited, Landing Page Cited, Competitors Recommended and Competitor Count, and running three separate checks in each of three engines with identical wording, a clean browser session, memory Off and test location aligned to the buyer market. According to groas, record 1 in Brand Mentioned when the answer names your company and 1 in URL Cited only when the answer links to your domain, separating named rivals with semicolons without counting a rival twice in one answer, for up to nine logged observations per prompt or 270 to 450 rows for a 30-to-50-prompt panel. The article calculates URL citation rate and brand mention rate with =IFERROR(AVERAGEIFS('03_Multi_Engine_Audit'!E:E,'03_Multi_Engine_Audit'!A:A,A2),0) and =IFERROR(AVERAGEIFS('03_Multi_Engine_Audit'!D:D,'03_Multi_Engine_Audit'!A:A,A2),0), formatted as percentages, notes that a name-drop is not a citation, and says to log an AI overview observation only when an overview appears rather than recording its absence as an omission. The article warns against treating one run or one kind of appearance as a stable ranking because answers can vary between checks. Read more: [Step 4: Run three checks per engine and log the answers](https://groas.com/post/turn-your-google-ads-search-terms-into-a#step-4-run-three-checks-per-engine-and-log-the-answers) ## How do I score which missing citations matter most? The article recommends entering =D2*(1-F2)*MAX(1,G2) in J2, where D2 is observed conversion value, F2 is share of logged answers that cited your URL, and G2 is number of competitor appearances, using C2 in place of D2 throughout if conversion value is not meaningful. According to groas, the score is a prioritization device not a revenue forecast: a cluster with $30,000 in conversion value, no URL citations and two logged competitor appearances scores 60,000, while an intent already cited in every logged answer scores zero, so column J is sorted highest to lowest. The article warns against dividing the score by impressions or clicks because that would pull the exercise back toward broad traffic instead of keeping the paid demand signal in view. Read more: [Step 5: Score the missing citations](https://groas.com/post/turn-your-google-ads-search-terms-into-a#step-5-score-the-missing-citations) ## How do I turn the top gaps into specific page work? The article recommends adding Action Type, Target URL and Missing Decision Factor beside the score and comparing the current paid landing page in column E with the prompt requirements and competitors named in the audit for each of the top ten clusters. According to groas, use Update Existing when a dedicated page already serves that intent but dodges the buyer decision factors, and use Create New when the current destination is a homepage, unrelated category page or generic post, putting the page to edit or create in Target URL. The article cites examples including Mid-Market 3PL WMS needing public pricing tiers and EDI integration specs and Emergency Boiler Rental needing explicit dispatch radius and technician response SLAs, and warns to publish only pricing, capabilities, service areas and commitments the business can support rather than copying every synthetic prompt condition onto a page. Read more: [Step 6: Turn the top ten gaps into page work](https://groas.com/post/turn-your-google-ads-search-terms-into-a#step-6-turn-the-top-ten-gaps-into-page-work) ## Related articles These articles answer the same questions: - [Turn Converting Search Terms Into an AI Prompt Map in 90 Minutes](https://groas.com/post/turn-your-google-ads-search-terms-report) - [Turn Google Ads Search Terms Into a Ranked AI Citation Gap List](https://groas.com/post/your-google-ads-search-terms-report-is-a) ## Sources [1] https://groas.com/post/turn-your-google-ads-search-terms-into-a (the article this page answers from)