Automate Share of Voice Tracking for Hotels in AI Search

Marketing teams at hotel groups currently rely on tools like SEMrush and Ahrefs for visibility metrics. These platforms are built for a world of ten blue links. They track keyword rankings and backlinks, which are becoming secondary signals in an AI-driven search landscape. They cannot reliably parse the unstructured, conversational text of a generative AI response to tell you if your hotel was mentioned favorably, neutrally, or not at all.

Consider a marketing manager for a boutique hotel chain. They want to know if their properties are recommended for queries like 'best hotels in miami for families' or 'romantic getaways near Seattle'. Their current process involves a team member manually typing these queries into Google SGE and Perplexity once a week and recording the results in a spreadsheet. This data is instantly stale, as AI answers are dynamic and can change with every query. This manual process cannot scale to track hundreds of keywords or a half-dozen competitors.

The structural problem is that traditional SEO tools are architected to scrape and analyze static HTML SERPs. Their data models are based on discrete, ranked positions. An AI-generated answer is a single, fluid block of text. These tools lack the natural language processing capabilities to identify your brand, your competitors, and the sources the AI cited within that block of text. They show you a URL's rank, not your brand's prominence within the answer itself.

Syntora's approach begins with adapting the existing AEO pipeline to your specific market. The first step is a discovery call to define the scope: which 500+ keywords represent your target guest personas, who are your top five competitors, and which AI search engines matter most. This defines the query set and the parsing logic.

We would reconfigure our pipeline's four stages for this task. Stage 1 (Queue Builder) would load your keyword and competitor list. Stage 2 (Generate) becomes a 'Query' stage, using APIs like the Brave Search API to systematically ask each keyword to multiple AI engines. Stage 3 (Validate) becomes an 'Analyze' stage, using a Claude API call to parse the text response, identify brand mentions, extract citations, and classify sentiment. All results, including the full text of the AI response, are stored in a Supabase database.

The delivered system is a private dashboard that provides a real-time view of your share of voice. You can filter by keyword, competitor, and date range to see how your visibility is trending. Because the system is built with Python and FastAPI, it's lightweight and can run for under $50/month. You receive the full source code and a runbook, giving you a proprietary market intelligence asset, not another monthly SaaS subscription.