How Fernwork tripled its Share of Answer on category prompts

The challenge

Fernwork sells shift scheduling software to restaurants, clinics and retailers with 5 to 200 locations. Its search traffic was healthy, and it held a top-three position on the major software review sites. Yet sales kept hearing the same thing on first calls: buyers had built their shortlist with an AI assistant, and Fernwork often wasn’t on it.

The team had no way to see those answers at scale, or to tell which pages, if any, the engines were drawing on.

What they did

Fernwork set up Prompt Tracking for 240 prompts across six engines, grouped into category, problem, comparison and brand prompts. Citation Sources showed that most category answers drew on four roundup articles and two forum threads, none of which covered Fernwork’s multi-location features. The team built its plan around those six pages.

• Rewrote its comparison pages with plain-language summaries and pricing tables engines could quote

• Sent updated product details to the authors of the three most-cited roundups, two of whom added Fernwork

• Answered recurring scheduling questions in the forum threads engines cited most often, with employees clearly identified

• Reviewed Answer Diff every Monday to see which changes moved which answers

The result

In five months, Fernwork’s Share of Answer on category prompts rose from 9% to 31%. It is now recommended in more than half of ChatGPT and Perplexity answers about multi-location scheduling. On first calls, 38% of new prospects say they first heard of Fernwork through an AI assistant, up from 11%.

The marketing team now reviews Share of Answer next to pipeline in its weekly meeting, and sales uses Answer Diff to prepare for competitive deals.