Share of voice, everywhere the decision happens

Your share of the three conversations that decide a purchase: the recommendations AI assistants give when customers ask, the social posts and comments that frame the category, and the reviews on Amazon, Walmart and retail sites. Each is reported against every rival, with position and sentiment for the AI answers.

Digital twins are simulated shoppers built from the real consumer language in your category, the same calibrated synthetic panels we benchmark against human results at 90%+ correlation. The same question gets a different answer for a budget-minded parent than for an ingredient-focused athlete, so we ask each question as the twins of your shopper segments, in each market you sell in, rather than as one generic logged-out user. The twin that asked then scores the fix.

A brief and a launch check. The reasons behind each answer and the pains in the reviews it cites are ranked as unmet needs, which is where your next concept starts. Concepts and claims are screened by the digital twins and against the assistants before real respondents see them. And before a launch, you learn whether the assistants will recommend the new product on day one and what it needs to be named.

A fixed, tagged panel of customer questions goes to each assistant three times a week, with live web search on so answers reflect what the assistant can read today. We record every brand recommended, its position and the sentiment of its portrayal, and report your share as a range, since AI answers vary run to run.

We query each assistant with its live web search enabled and compare a sample of answers against the consumer interface each week, so you can see how far the two diverge for your category.

We pull the unprompted posts, comments and reviews in your category, the same signal base behind our consumer insight research, and score each brand’s share of mentions and the themes attached to it.

Every finding. Our team reads the sources behind each number, removes what does not belong, and writes the conclusion, so you get an answer you can defend rather than a dashboard to interpret.

A brand tracker measures what people say about you in one channel. A visibility tool counts mentions for a generic user, once a day, and stops at the citation. Share of Voice puts the AI answers, the social conversation and the reviews side by side, asks as your shoppers’ digital twins, explains why each moves, and tests the fix before you ship. It sits beside your brand tracker and covers what the tracker cannot see.

ChatGPT, Gemini, Claude, Perplexity, Grok and Google AI Overviews, on the models customers use, with live web search on. For software and developer products we also run Claude Code and Codex on real tasks and record what they build with. Each assistant gets the same fixed panel of questions so results compare week to week, and a sample is checked against the consumer interface so you can see how far the two diverge.

Yes. Any brand customers ask an AI assistant about: beauty, sports, retail, health, travel, financial services and more. The questions are built for your category.

Tracking is a monthly plan per product, with Brand and Enterprise plans for teams tracking many products and markets, and a free tier for one product. Projects, studies and tests are paid from prepaid credit packs; the AI Recommendation Project starts at $12,000. Plans and prices are on the pricing page.

One scan, four outputs. Brand and insights teams get the tracker and the slide for leadership. Innovation teams get the unmet needs behind each answer, ranked as a brief, and a pre-launch read on whether the assistants will recommend a new product on day one. Product managers get the feature and claim gap list and the listing audit. The CEO gets one number, its trend, and what a share point is worth.

We size it with the same opportunity sizing model used in the sprint: your share of the answer against category demand and the conversion the assistants drive, so the slide carries a dollar figure, not a percentage.

Yes. The Simporter MCP server connects to any MCP client with a personal token, so your team can run a scan, pull this week’s share and read the why without leaving the tool they work in. Weekly alerts can post to a Teams or Slack channel.