Building a Competitor Citation Tracking Dashboard
Create a dashboard to track competitor citations in Llama.
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This guide is part of Trakkr's AI visibility library, then routes readers into product coverage, pricing, category benchmarks, and API access.
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- Editorial
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- March 13, 2026
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- Public
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Llama doesn't just generate responses - it cites sources. When users ask about your industry, Llama might cite your competitors 80% of the time while mentioning you never. You can't see this happening unless you're systematically tracking it. Building a dashboard lets you monitor which competitors dominate Llama's citations, what triggers their mentions, and where your opportunities lie.
The Problem
Most brands track competitor mentions in search results or social media, but ignore AI citations. Llama's source selection determines who looks authoritative to millions of users. When you miss this data, competitors build citation advantages you can't see coming.
The Solution
A competitor citation dashboard automates tracking who gets cited for industry queries in Llama. You'll query relevant topics daily, extract citation data, and visualize trends. This reveals which competitors own mindshare in AI responses and shows you exactly what content types Llama favors.
Map your competitive landscape for tracking
List 5-10 direct competitors and note their primary domains. Include both obvious rivals and companies that target adjacent markets. Add key industry publications and thought leaders - Llama often cites these alongside brands. Create a master list with competitor names and their main web properties.
Build your query dataset
Create 20-50 queries covering your industry topics: product comparisons, how-to questions, industry trends, and buying guides. Include both broad terms ('best project management software') and specific pain points ('how to track remote team productivity'). Test each query in Llama to ensure it generates citations.
Set up automated Llama querying
Use Llama's API or automate browser interactions to run your queries daily. Parse responses to extract citations, noting the source URL, position in response, and context around each mention. Store results in a database with timestamp, query, competitor, and citation details.
Create citation frequency tracking
Build charts showing citation frequency per competitor over time. Track both absolute mentions and citation position (first cited vs. mentioned later). Calculate each competitor's 'share of voice' across all your queries. This reveals who dominates AI mindshare in your space.
Analyze citation context and triggers
Tag each citation with context: pricing discussions, feature comparisons, user reviews, or thought leadership. Identify which query types trigger each competitor most often. Some might dominate 'best of' lists while others get cited for technical deep-dives.
Monitor citation source quality
Track which websites Llama cites for each competitor. High-authority sites like industry publications carry more weight than blog posts. Create scores based on source domain authority and citation frequency to identify competitors with the strongest citation profiles.
Set up competitive alerts and reports
Configure alerts for sudden citation changes: new competitors appearing, established players dropping off, or dramatic shifts in mention frequency. Generate weekly reports showing citation trends, top-performing competitors, and emerging threats in AI visibility.
Frequently Asked Questions
How often should I query Llama for citation tracking?
Daily for core queries, weekly for broader industry terms. Llama's responses don't change hourly, but daily tracking catches new citations quickly and builds enough data for reliable trend analysis.
What's a good citation frequency benchmark?
Aim for 20-30% citation rate across your industry queries if you're an established player. New companies might start at 5-10%. Market leaders often achieve 40-50% citation rates for their primary topics.
Should I track indirect competitors too?
Yes, especially adjacent solution providers. Llama often suggests alternatives users hadn't considered. A project management tool might compete with note-taking apps or communication platforms in AI responses.
How do I handle Llama's response variations?
Run each query multiple times and track the range of responses. Some queries have consistent citations while others vary significantly. Focus your analysis on stable patterns rather than one-off mentions.
What citation data should I track?
Source URL, position in response, context around mention, query that triggered it, timestamp, and any quoted text. This gives you enough data to identify what content types and topics drive citations for each competitor.