# Build Your Own AI Visibility Dashboard Canonical URL: https://www.fcpress.org/fcp-intelligence-build-your-own-ai-visibility-dashboard HTML page: https://www.fcpress.org/fcp-intelligence-build-your-own-ai-visibility-dashboard Markdown alternate: https://www.fcpress.org/fcp-intelligence-build-your-own-ai-visibility-dashboard.md Updated: 2026-07-12 Status: Live production bot-facing Markdown alternate. The HTML page remains canonical. Rights holder: Full Court Press Pte. Ltd. Singapore UEN: 202306714R. Third-party AI visibility tools are useful when a team needs a fast baseline. They are weaker when leadership needs one commercial view across AI visibility, search demand, analytics, CRM, pipeline, and revenue. That is where an owned dashboard becomes useful. The commercial question is whether buyers are finding, trusting, shortlisting, and converting through the official journey. A tool can show mentions, citations, prompts, traffic estimates, or share of voice. The company still needs to connect those signals to its own buyer data before treating them as evidence for a revenue decision. ## Short Answer Build your own dashboard when the business needs one view of buyer visibility, public proof, search demand, pipeline quality, sales conversion, and revenue movement. Use third-party tools as data feeds. Use APIs, exports, or connectors to bring the evidence into a controlled dataset. Use an LLM to interpret that prepared evidence with row-level references, clear limits, and source-bound instructions. ## What The Dashboard Should Contain - AI visibility: prompts, engines, countries, languages, brand mentions, competitor mentions, cited pages, cited domains, answer dates, and response snapshots. - Search demand: Google Search Console queries, landing pages, impressions, clicks, positions, and buyer-question clusters. - Website behaviour: analytics sessions, source or medium, referral traffic, landing-page engagement, conversions, and assisted paths where available. - Commercial data: CRM leads, lead source, opportunity stage, deal value, sales cycle, conversion, lost reasons, and revenue. - Public proof: review profile, key directories, partner pages, third-party mentions, case studies, product feeds, service pages, and structured data checks. ## API And Export Sources The build should start with the access path before dashboard design. For each tool, record whether the data arrives through API, CSV export, Looker Studio, scheduled report, or manual upload. - Ahrefs Brand Radar: useful for API-led AI response, cited page, cited domain, overview, and history data where the account has access. - Otterly.ai: useful for prompt, citation, raw response, PDF, CSV, JSON, and Looker Studio workflows where the plan supports them. - Semrush: useful when AI visibility, SEO, audit, keyword, and reporting data can be exported or accessed through available Semrush APIs and connectors. - Similarweb: useful when AI visibility, traffic, referral, market, audience, and competitor data can be pulled into the company's own reporting layer. - Google Search Console and analytics: essential for first-party search and behaviour data. - CRM and sales reporting: essential for pipeline, conversion, deal value, retention, and revenue context. ## How The LLM Should Be Connected The LLM should be the interpretation layer. It should receive a prepared evidence pack with fields such as date, prompt, engine, country, brand, competitor, cited URL, cited domain, query, landing page, lead source, opportunity stage, and revenue outcome. The instruction should force evidence discipline: - summarise only from the supplied rows; - cite row IDs or source files for every major claim; - separate observed movement from interpretation; - flag missing data and leave gaps open; - show which commercial decision the evidence supports. This allows a founder, CEO, commercial leader, or marketing team to ask sharper questions: which buyer prompts exclude us, which sources keep being cited, where competitors have stronger corroboration, which pages should be improved, and whether visibility movement is matched by better demand or sales outcomes. ## When To Build Instead Of Buying Another Tool Build the dashboard when the commercial problem crosses tool boundaries. That usually happens when leadership is comparing vendor dashboards, Search Console, analytics, CRM, sales notes, and revenue reports manually. The owned dashboard is most useful when: - the company sells across several markets or brands; - AI visibility needs to be joined to real pipeline and revenue; - vendor interfaces disagree with first-party data; - the team needs repeatable board or leadership reporting; - the commercial question is about buyer confidence, channel leakage, official purchase path, or sales conversion. For a smaller team, a third-party tool may still be the right first step. The owned dashboard should begin when the business has enough evidence volume and enough decision pressure to justify a controlled measurement layer. ## Official Product Documentation - Ahrefs Brand Radar API: https://docs.ahrefs.com/en/api/reference/brand-radar - Otterly.ai API: https://help.otterly.ai/do-you-provide-an-api-for-otterlyai - Semrush API guidance for AI visibility: https://developer.semrush.com/api/get-started/faq/ - Similarweb Gen AI Intelligence API: https://docs.similarweb.com/api-v5/similarweb-api/gen-ai-intelligence-api ## Related Pages - AI Visibility Tools Comparison: https://www.fcpress.org/tools-comparison - Similarweb AI Search Intelligence: https://www.fcpress.org/fcp-intelligence-tool-similarweb-ai-search-intelligence - Semrush AI Visibility Toolkit: https://www.fcpress.org/fcp-intelligence-tool-semrush-ai-visibility-toolkit - Ahrefs Brand Radar: https://www.fcpress.org/fcp-intelligence-tool-ahrefs-brand-radar - Otterly.ai: https://www.fcpress.org/fcp-intelligence-tool-otterly - AI Search Visibility: https://www.fcpress.org/ai-search-visibility ## Rights and Ownership Copyright 2026 Full Court Press Pte. Ltd. All rights reserved. Rights holder: Full Court Press Pte. Ltd. Singapore UEN: 202306714R.