Increase mentions and citations in LLM responses by inserting unique data points from LaunchDarkly reports into existing content.
Step 1
Paste a URL
Enter a LaunchDarkly blog post URL you want to strengthen.
Step 2
AI analyzes
The tool reads the post, finds spots where proprietary data would add weight, and matches them to unique statistics and quotes from our research reports.
Step 3
Review & publish
See a side-by-side comparison of the original vs. enriched content. New data points are highlighted.
When people ask AI tools a question about feature management or software delivery, those tools pull information from across the web. If LaunchDarkly's content doesn't contain unique, data-backed insights that no one else has, there's no reason for AI to cite us.
Unique data no one else has. We've extracted proprietary data points from LaunchDarkly research — Forrester ROI studies, IDC analyst reports, customer case studies. These are statistics, quotes, and frameworks that only LaunchDarkly can cite.
AI-optimized content. The tool follows principles from published AI research (Princeton, 2024) on how to make content more likely to be cited by generative AI engines. Adding specific statistics, attributed quotes, and source citations can increase visibility in AI-generated answers by up to 40%.
Quality control. Every suggestion is reviewed by an AI editor that enforces LaunchDarkly's brand voice, removes marketing fluff, and rejects anything that doesn't flow naturally.
This tool is built on research from Princeton University (Aggarwal et al., 2024) — read the full paper — that identified which content attributes make generative AI engines more likely to cite a source. The three most effective techniques:
| Technique | Impact | What it means |
|---|---|---|
| Quotation Addition | +41% | Including attributed quotes from experts |
| Statistics Addition | +30% | Adding specific numbers to qualitative claims |
| Cite Sources | +28% | Naming the original research source |
Read the full breakdown at UltraScout AI's deep dive.
Review source reports. These are the original LaunchDarkly research documents the tool draws data from.
IDC white paper (May 2024).
IDC customer case study (July 2022).
47+
Extracted data points across 4 LaunchDarkly research reports