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The detail view for a single topic in your project. You land here from any topic row on the dashboard. The dashboard shows the topic at a glance. This page shows what’s actually driving it.

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What you see

The header has the topic name, your visibility on it (e.g., “3.3% visibility across 150 responses”), and a Log Content Update button. Logging a content update here ties it to any Workstream that contains this topic, so a ship date becomes a pin on the workstream trend chart and feeds the citation-lag and coverage-shift attribution. A prompt-set filter sits above the content, same shape as the one on the main dashboard.

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AI recommendation

Right under the header. A short paragraph of plain prose: what’s working on this topic, what isn’t, what to do next, with specific platforms and source domains named.

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Where the recommendation comes from

For the topic in view, OpenLens assembles a structured snapshot:
  • Your brand’s visibility and average position on the topic.
  • Per-platform breakdown: your score vs the best competitor on each active AI platform.
  • Every tracked competitor’s overall score on the topic.
  • The top 5 most-cited domains for this topic across all prompts.
  • The top 5 sentiment-analysis themes for this topic (your average sentiment on each theme vs the best competitor’s). These are the themes from the Sentiment Analysis matrix below, not from the prompt-attribute filter.
That snapshot goes to Claude Haiku 4.5 with one instruction: write a 2 to 3 sentence actionable insight for a marketing executive, lead with the most important finding, name specific platforms and sources, direct, no hedging, no bullet points. Max 512 output tokens. The model returns one paragraph. That’s what shows at the top of the page. The same generator backs the /api/insights/topic endpoint. What you see on this page and what you fetch via API are the same paragraph for the same run. The recommendation regenerates on every visit against the latest usable run. If the run hasn’t completed or there’s no data yet, the recommendation block is empty.

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Visibility trend

Line chart of your visibility on this topic over time. One marker per completed run. Use it to spot real movement vs single-run noise.

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Position by Platform

A brand-by-platform matrix. Rows are tracked brands (you + competitors), columns are the active AI platforms, cells show per-platform visibility % on this topic. The Overall column on the right aggregates across platforms. Read your row to spot platforms where you’re invisible. The columns answer the inverse question: which brand owns each platform on this topic.

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Engine insights

One block per active AI platform. Each shows the platform’s average citations per response on this topic plus a one-line summary of source-mix behaviour (“Heavily favors Third Party sources (88.4%)”). Same shape as the Engine Patterns section in the report, scoped to this single topic.

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Sentiment Analysis

A matrix of themes Claude extracted from the raw responses on this topic, with the sentiment each brand attracted on each theme (positive, negative, neutral). The themes are pulled out of the response text itself — features, capabilities, complaints, anything the model talked about — not the prompt-attribute filter from Prompt attributes. Different concept, despite the similar word. The presentation is dense and most users skim it. This view is on the roadmap for an overhaul.

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Sources cited by AI

Top cited domains for the prompts in this topic. Domain, citation count, and which platforms cited it. Same data as the dashboard’s AI Sources tab, filtered to this single topic.

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Raw AI responses

Expandable list of every individual platform response for the prompts in this topic. Click into a response to see the full text the model returned and the citations attached. This is the ground truth. Every metric on the page rolls up from these responses.