Build custom analytics queries with natural language
The Analytics Query Engine lets you build custom analytics queries using natural language. Instead of working with pre-built reports, ask your AI assistant to slice and dice your visibility data in any way you need — by platform, over time, filtered by sentiment, and more.
The analytics engine supports a wide range of queries. Here are some examples of what you can ask:
How many mentions and citations do I have on each AI platform?
Last 30 days by platform:
ChatGPT: 18 mentions, 7 citations (39% rate)
Perplexity: 12 mentions, 9 citations (75% rate)
Claude: 8 mentions, 3 citations (38% rate)
Perplexity has your highest citation rate. Consider optimizing content for ChatGPT to improve its lower rate.
Chart my weekly mention count and sentiment over the last 3 months.
Weekly Trends (Last 12 Weeks):
Mentions are trending up — from 6/week in December to 12/week in February.
Sentiment has been steady at 72-78 range.
The uptick in mentions started around mid-January, likely correlating with your new blog posts.
Show me only ChatGPT mentions from the last month that have high sentiment and include citations.
Found 5 ChatGPT mentions with high sentiment and citations in the last 30 days. The most common trigger queries are in the "best tools for..." and "how to..." categories.
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