Competitor Gap Analysis

Navigate to Prompt Analytics and select the Visibility Score tab. Set your date range to at least the past 30 days to ensure you have statistically significant data. Shorter timeframes can show false patterns due to AI response variability.

Click the Export button in the top right corner and select 'Full competitive analysis' as your export type. This will include all prompts, competitor mentions, citation sources, and sentiment scores. The export generates a CSV that you can open in any spreadsheet application.

Once exported, sort the data by 'Competitor Share' in descending order. This surfaces the prompts where competitors are getting the most recommendations relative to your brand. Pay special attention to prompts where your share is below 20% - these represent the biggest opportunities.

For each high-priority prompt from step 2, click through to the prompt detail view in Lightsage. Scroll to the 'Competitor Citations' section to see which specific pages AI platforms cite when recommending your competitors. These citations reveal what content AI considers authoritative.

Visit each cited page and analyze its structure. Pay attention to: the page title and H1, how the content is organized with headers, whether it includes comparison tables or feature matrices, the presence of code examples or tutorials, and how directly it answers the prompt's implicit question.

Document common patterns across winning competitor pages. You'll often find that cited pages share characteristics: they're comprehensive (2000+ words), they use clear hierarchical structure, they include specific examples, and they directly address user intent. This becomes your content template.

For each prioritized gap, create a content brief using the competitor citation analysis from step 3. Your brief should specify: target prompt(s), competitor pages to beat, required sections and topics to cover, word count target, key differentiators to highlight, and internal linking requirements.

Assign ownership and deadlines. Gap analysis is only valuable if it leads to action. Create a shared tracker with content owners, due dates, and publication milestones. Aim to close your top 5 gaps within 30 days - AI models update their knowledge over time, and consistent improvement compounds.

Build a measurement loop back into Lightsage. After publishing new or updated content, create a saved view for the target prompts and set up weekly monitoring. You should see citation changes within 2-4 weeks for most AI platforms. If you don't see improvement after 6 weeks, the content may need further optimization.