Prefer

Prefer is a marketing tool that tracks and win brand mentions across ChatGPT, Gemini and AI search. Prefer is an answer engine optimization platform that tracks how ChatGPT, Gemini, Google AI Overviews and Perplexity describe a brand, benchmarks competitors and citations, and queues ranked fixes and content drafts to win more AI recommendations.

Prefer is an answer engine optimization (AEO) platform that shows how AI engines such as ChatGPT, Gemini, Google AI Overviews and Perplexity talk about a brand, then points to what should be published or fixed to change the result. It targets marketing and growth teams who have watched buyers shift from classic search to conversational answers and want a measurable way to be the product those engines recommend. The product is organised as a stack of six connected areas. Prompts tracks the real questions buyers ask and reports an answer rate for each one, including how many sampled answers name the brand and its average position. Answer Engine Insights scores visibility, sentiment and share of voice across engines, regions and personas. Competition compares share of voice head to head so it is clear who wins each prompt. Sources and Citations lists the pages and domains that engines cite, and flags where the brand is absent from them. Action Center turns the findings into a ranked queue of fixes, and Content Automation produces briefs and drafts built from citation data. In practice a team starts with a free AI Visibility Audit or AEO report, which requires no signup according to the homepage, and then moves into ongoing tracking. The sample dashboards show tasks such as allowing AI crawlers in robots.txt, adding schema markup, publishing an llms.txt file and getting listed on review sites, each scored by expected impact and some marked for an AI agent to carry out. Drafts carry an AEO content score and a checklist of topics that still need coverage. Among alternatives, Prefer sits between pure monitoring dashboards and general SEO suites. Its emphasis is on closing the loop from measurement to action, with fix queues and content generation attached to the tracking data. Teams that only want a rank report may find the scope broader than needed, while those running content and technical work for AI search get a single workspace for both. The homepage cites a 4.7 rating on G2 and lists early-access teams from several software companies.