AI Visibility ROI & Opportunity Cost Calculator
Enter your average contract value and your AI Share of Voice. The calculator sizes the revenue you are leaving in answers where an assistant names someone else, plus the share of it drifting to competitors through wrong or stale descriptions of your company.
Updated: September 2026
The opportunity cost of low AI visibility is the number of buyer questions per month where an assistant names a competitor instead of you, multiplied by your close rate and your average contract value. At a $24,000 ACV, 400 monthly buyer questions, a 12 percent close rate, and a gap of 32 points between current and target Share of Voice, that is roughly $368,640 of annual pipeline going to whoever the model names instead.
Size your gap
Everything runs in your browser. Nothing is saved or sent anywhere.
First-year contract value of one new customer.
How many buying conversations your category generates monthly. Default is a conservative mid-market starting point.
Share of AI answers that name you today. Leave at zero if you have never been named.
Where you intend to be. Category leaders in tracked sets sit between 40 and 60 percent.
Of the buyers who reach you after an assistant named you, the share that becomes a customer.
This is a sizing model built from your inputs, not measured revenue. Replace the estimates with scan data before treating any figure as a forecast.
What hallucination drift is, and why it costs more than absence
Not being named is a missed impression. Hallucination drift is worse: the assistant answers confidently and gets you wrong. An outdated price, the wrong category, a capability you shipped last year described as missing, a competitor presented as the obvious pick for your exact use case. The buyer leaves the conversation with a firm, incorrect belief, and nothing on your site is in that conversation to correct it.
The calculator splits your gap into two lines for that reason. Plain absence is recoverable by showing up. Drift has to be corrected at the source the model is reading, which is usually a third-party page, not one of yours.
What this calculator cannot tell you
- It does not measure your pipeline. It multiplies the numbers you typed. Change one input and the answer changes with it.
- It does not know your real Share of Voice. That requires running a fixed prompt set across ChatGPT, Claude, Gemini, and Perplexity several times and counting how often you are named.
- It does not prove causation. A visibility lift that lands in the same month as a revenue lift is a correlation until a stable baseline and repeated scans say otherwise.
- It does not assume every missed answer converts. That is what the close-rate input is for. Keep it honest.
Replacing the estimates with measured numbers
Three of the five inputs stop being guesses after one scan. Monroya runs your buyer question set across all four assistants, counts how often you are named, tags each question by buying stage, and shows which sources the models cited instead of you. Current Share of Voice becomes measured, target becomes the observed leader's number in your category, and prompt volume becomes the tracked set rather than an estimate.
$79/mo vs. the alternatives.
Loaded cost. Output: ~4 posts/month, no AI visibility measurement.
Quarterly deliverables. You wait on someone else's calendar.
4-provider scans, buyer-journey matrix, 15 tracked prompts, 15 drafts. Ship this week.
Monroya replaces the measurement layer and most of the prioritization work. You still need someone to ship the changes — Monroya tells them what and gives them the first draft.
Frequently asked questions
- What is AI Share of Voice?
- The share of AI answers to your buyer questions in which your company is named at all. If ten buyer questions are asked across ChatGPT, Claude, Gemini, and Perplexity and you are named in three of the answers, your AI Share of Voice is 30 percent. It is measured against a fixed prompt set, not against search volume.
- Where do I get the monthly prompt volume to enter?
- Start with the number of buying conversations your category realistically generates each month: pipeline volume, demo requests, or the count of buyer questions your sales team hears repeatedly. The calculator is a sizing model, so an honest estimate is enough. A Monroya scan replaces the estimate with the tracked prompt set your buyers actually ask.
- How accurate is this estimate?
- It is directional, not measured. It multiplies your inputs; it does not observe your pipeline. Treat the output as the size of the problem worth investigating, then replace every input with a measured number before putting it in a board deck.
- What is hallucination drift and what does it cost?
- Hallucination drift is when an assistant answers a question about your category with wrong, stale, or competitor-favoring information about you: an outdated price, the wrong category placement, a feature you shipped two years ago described as missing, or a competitor named as the obvious pick. It costs more than absence, because the buyer leaves with a confident wrong belief rather than no belief.
- How long before a Share of Voice lift shows up?
- Retrieval-driven gains, where a model reads a new or corrected source live, typically appear within days to a few weeks. Gains inside a model's trained knowledge arrive on refresh cycles measured in months. Judge the trend over a quarter rather than week to week.
- Does this calculator store what I enter?
- No. Everything is calculated in your browser. Nothing is sent to a server, saved, or associated with you, and no signup is required to use it.
Related reading
- What is Share of Model— The metric this calculator is built on
- How to improve Share of Model— The six-step method for closing the gap
- 2026 AI Visibility Benchmark— Where 60 measured companies actually landed