Case Study -

Software testing & code quality

57% share of voice in developer tools AI answers

60% AI visibility

Appears in 3 of 5 buyer prompts

57% share of voice

Majority of category mentions

~2 average position

Top of answer when cited

Project

Software testing & code quality

Specialized platform competing in an enterprise-dominated category.

Goal

Increase visibility across AI-generated recommendations and strengthen category leadership.

Timeline

~3 months

Starting point

Large enterprise vendors dominated category awareness despite the company's focused solution for developers and QA teams.

client feedback
SEO Manager

"We've seen steady improvements in AI-generated recommendations over the engagement."

Impact

The goal: Earn visibility in an enterprise-dominated category

Software testing and code quality is a category largely controlled by established enterprise vendors with greater scale and brand recognition.

The objective was to strengthen visibility across AI-generated recommendations and increase representation in category-level conversations.

The solution: Increase visibility where AI gets its information

We examined the sources, citations, and content patterns shaping AI-generated recommendations within the software testing category.

This helped identify:

  • The publications most frequently referenced by AI systems
  • Citation gaps competitors were overlooking
  • Opportunities to increase visibility across trusted industry resources

The company then secured 70+ targeted placements across developer publications, QA resources, comparison pages, and industry websites.

The result: Owning the majority of category mentions

The company captured 57% share of voice and appeared in 60% of tracked buyer prompts.

Despite competing against substantially larger vendors, it earned the majority of category mentions in AI-generated answers and established itself as one of the most visible brands in the market.

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