Omni Impact for commerce & retail
Get named when the shortlist forms.
Product research now starts with a question and ends with three or four product names, chosen and described by a model. Omni Impact tells you whether yours is one of them, how it is described, and what to publish when it is missing.
Half
of shoppers say they have asked an AI what to buy.
Consideration used to run through a search page and a category grid. It now runs through one answer that names a handful of products and explains why. Retailers whose product pages, specs and reviews the models can retrieve and trust get named in that answer; everyone else loses the shopper before the shelf. The selection is measurable, and it moves.
Industry research on AI-assisted shopping. Not an Omni Impact benchmark.
Share of Voice
Rankings
Q · What’s the best trail running shoe for wide feet under $160?
Recent AI mentions
“If you need width, the Cairnfoot Vantage is the easy pick — a true wide last and a 6 mm drop that holds on loose descents, at $145.”
ChatGPT · Buying guide · 1h ago
What teams achieve
What retail brands achieve with Omni Impact.
From the first best-of question to the last comparison before checkout, the whole buying path is monitored, measured and improved.
Cover the whole product question
Shoppers ask for the best shoe under $150, then whether it runs narrow, then how it compares to the pair a friend owns. Your question set covers all three shapes — best-of, sizing, head-to-head — with your brand name left out of every organic prompt, so what comes back is the shortlist a real shopper was handed.
Catch the wrong spec early
Every answer is read for sentiment, framing, prominence and certainty: durable or disposable, premium or overpriced, recommended outright or hedged. When a model attaches a stale price band or a discontinued spec to your product, anomaly alerts surface it the same day.
Earn the roundup citation
Product answers lean hard on roundups, buying guides and review sites. Citation vs retrieval shows which of those domains the models actually pulled for your category, and ranked findings arrive as generated fixes — product schema, comparison content — aimed at earning the next citation.
On the platform
The loop, tuned for retail.
The same instrument — monitoring, measurement, ranked fixes — pointed at the questions shoppers ask before they buy.
Monitor
Every buying question, on a schedule.
Your shoppers’ real questions — best-of lists, sizing, head-to-head comparisons — run against nine AI models with your brand name left out of every organic prompt. Absence is not a blank; it is a recorded signal you can watch move.
- Nine models, including ChatGPT, Claude, Gemini and Perplexity
- Organic share of voice across best-of, sizing and comparison prompts
- Mention tiers from top pick down to not mentioned
Improve
Fixes that publish straight to the storefront.
Findings arrive as generated fixes — product and FAQ schema for your PDPs, answer-shaped sizing and comparison content for your guides — publishable through twenty integrations with a before-image on every write.
- 29-signal website audit against the AEO playbook
- Generated JSON-LD and content matched to your stack, Shopify included
- Two-step confirmation and one-click revert on every publish
Questions