AEO Platform for Daeda
About
A platform that tracks how Daeda Tech shows up in AI search - which queries surface us, the sentiment around those mentions, and which competitors get returned alongside us.
What It Tracks
- Visibility: whether Daeda Tech appears in answers from ChatGPT, Perplexity, Claude, and other agentic search.
- Sentiment: how we're framed when we do appear - positive, neutral, dismissive.
- Competitive set: which HubSpot ecosystem players get surfaced for the same queries.
The feedback loop into the rest of the marketing systems - tells the AEO Framework what's working, tells the Content Pipeline what gaps need filling.
Tech Stack
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Related Projects
Site Growth
Migrated daeda.tech from Webflow to Astro, ran a conversion-focused redesign, and shipped a full SEO and AEO (Answer Engine Optimisation) sprint across the rebuilt site and its docs. ## Migration Moved off Webflow onto Astro so the site, docs, blog, and apps catalogue all live in one repo and ship through the same pipeline. ## Redesign - Clear flow from landing to product to book a demo. - Templated deep-dive layout for product pages. - Animations so each product shows itself in action. - Internal linking, hubs, and comparison pages for SEO depth. ## SEO + AEO Sprint Audited the marketing site and 94-page docs container, then shipped: - Sitemap and structured data (TechArticle, HowTo, BreadcrumbList, FAQ schemas). - Title and description rewrites, H1 cleanup, thin-page fixes. - Marketing-to-docs cross-linking that didn't exist before. ## Results The chart above tells the story. Flat for the first ten months, then a clear inflection upward after the migration and SEO sprint shipped. Lifetime (Jan 2025 to May 2026): - 398 total clicks - 40.4k total impressions - Average position: 9.4 The 3-month window covering the sprint itself: - Clicks: 18 → 67 (+272%) - Impressions: 1.56k → 4.47k (+186%) - Avg position: 27.8 → 12.1
AEO Framework
Optimising Daeda Tech's marketing and docs sites for Answer Engine Optimisation - making content discoverable and easily parsable by LLM-based search (ChatGPT, Perplexity, Claude, etc.). ## What This Covers - Structured data (TechArticle, HowTo, BreadcrumbList, FAQ schemas) across marketing pages and the 94-page docs container. - Content shaped for the questions agentic search actually asks, not just the keywords ranking sites traditionally chase. - Internal linking hubs and comparison pages that give LLM crawlers a clear semantic graph to walk. Currently figuring out how AI loops fit in - generating schema variants, gap-mapping site coverage against real LLM queries.