Shoppers are asking ChatGPT, Claude, and Perplexity what to buy instead of Googling it. There's no page 2 in an AI answer — your brand is either recommended, or it's invisible while competitors take the sale.
Run a free 60-second check See a sample report$25–49/mo prompt trackers cap your prompts, under-sample (one run per prompt = statistical noise), and hand you a number with no plan attached. Watching a score is not the same as moving it.
The serious tools gate citation-source analysis — the actual action lever — behind enterprise tiers, and the real cost is the team you hire to act on the data.
Before you commit to monitoring anything, you need to know: how bad is it, what's it costing, and what exactly do we do about it? That's a one-time audit, not a subscription.
~20 real buyer questions across discovery, comparison, purchase, and trust stages — built for your category, with purchase-intent prompts weighted 1.5× because they're closest to money.
AI answers are non-deterministic. Every prompt runs 3×, and we report a consistency score. Any tool showing single-run results is selling you noise — we say this out loud because honesty about variance is the differentiator.
One model answers your buyers' questions naturally (uncontaminated). A second model extracts every brand, its position, sentiment, and the third-party sources the answer leaned on.
The fix for invisibility is almost always presence on the specific sources engines cite. You get that source list — it's your PR hit-list, not an enterprise add-on.
Share of voice is a vanity metric. We translate visibility into a dollar figure — with every assumption printed so you can challenge the model instead of distrusting it.
P1 (14 days), P2 (30 days), P3 (60 days) — derived from your findings, not a generic checklist. The deliverable is the prescription, not the score.
Use them — later. They're monitoring layers: great once you know what to watch. But monitoring a visibility score you haven't diagnosed is theater. ShelfSpace is the diagnosis + prescription that tells you whether monitoring is even worth paying for yet, and what to fix first. Many clients graduate to a monitoring tool after the audit; we'll recommend one in your report.
More meaningful than most tools' ongoing tracking, honestly. AI answers vary run-to-run, so we sample every prompt 3× and report consistency alongside visibility. Cheap trackers run each prompt once and chart the noise. We'd rather show you fewer, honest numbers.
Monthly revenue × the share of purchase journeys starting in an AI assistant × (1 − your visibility score). Every input is printed in the report. It's a linear, conservative model — the point is direction and magnitude, not false precision. Challenge the assumptions on the walkthrough call; that conversation is part of the product.
A written report (see the sample): visibility score, share of voice vs competitors, funnel-stage breakdown, prompt-by-prompt verdicts, the citation-gap source list, the revenue model, and a P1/P2/P3 action plan — plus a 30-minute call to walk through it.
The audit runs on frontier-model assistants representative of how ChatGPT-class engines answer shopping questions. The findings — which competitors own the shelf, which sources get cited — generalize across engines because they draw on the same public web. Multi-engine panels are available for the re-test if your category warrants it.
A performance-marketing operator with 5+ years running paid acquisition and SEO for DTC ecommerce brands, now applying the same measurement discipline to the AI-answers channel. Built solo, in public. You'll get the founder on your walkthrough call, not an account manager.