For consumer goods brands
The AI answer layer for consumer goods brands
Shoppers ask an AI which product to buy before they reach a shelf or a product page. LBOX measures what the engines say about your brand, finds where a retailer or a review site is answering for you, and builds the evidence that changes it.
Measured across
Perplexity
Gemini
Google AI
Claude
Copilot
Meta
DeepSeekGrok... and moreEvery one of them is competing for the same answer. One name comes back when a buyer asks.
What makes consumer goods brands different
Not general marketing advice. These are the constraints your category actually operates under.
The retailer owns your answer, not you.
Ask an engine about your category and it cites Amazon, Walmart and Target listings long before your own site. The description a shopper reads is the one a marketplace wrote, assembled from a feed you may not have updated in a year.
Your range collapses into one recommendation.
Size, flavour, pack count and formulation are the whole point of your assortment. Engines flatten them into a single suggested product, and it is frequently the wrong SKU, discontinued, or the one with the thinnest margin.
Reviewers are the cited authority.
Consumer Reports, Good Housekeeping, Reddit threads and roundup articles are what the engines quote when asked what is worth buying. None of them is yours, and most of your category never checks which ones get repeated.
Retail media does not reach this.
Sponsored placement buys the shelf and the search results page. It does not buy a sentence in an answer, because the engine is not selling that position to anyone.
What you get back
The console, measuring a consumer goods brands company against the questions its buyers ask. Every brand named, every domain cited, every engine separately.
A worked example on an illustrative company, shown to display the console. Your own numbers come from measuring your questions through the engines’ own APIs.
See which product the engines actually recommend
Visibility and share of voice on the unbranded questions shoppers ask, measured per engine. Not a list you supplied.
- Ranked against the brands the engines actually named
- See where an engine reads your page without naming you
You against the field, engine by engine
unbranded questions| Brand | Gemini | AI Overviews | OpenAI | Perplexity | Claude | ChatGPT |
|---|---|---|---|---|---|---|
| Calderwood Co | 34% | 31% | 29% | 24% | 16% | 36% |
| Meridian Home | 28% | 26% | 24% | 21% | 13% | 29% |
| Harbour & Vineyou | 29% | 18% | 26% | 19% | 11% | 4% |
| Tidewater Goods | 17% | 14% | 12% | 15% | 8% | 13% |
| Foxglove Supply | 10% | 7% | 6% | 9% | 4% | 8% |
Turn what the answers get wrong into work that ships
Findings arrive as a worklist sorted by who can act: what LBOX writes, what needs brand approval, what needs your feed or your web team.
- Scored against your category, not a generic SEO checklist
- Nothing publishes without your sign off
The worklist
Prove the change, season after season
Every measurement is stored, so the line lengthens each cycle and the movement you paid for is on the record.
- The same questions, asked again and checked
- Sources broken out per model, per page
Visibility over time
every measured runKnow when the models come to read your product pages
Crawler activity captured at the edge, so you can see which models fetch your product and ingredient pages, and how often they return.
- Every model, every page, logged over time
- Robots and content signals kept current
Crawler activity
hits by model, last 30 daysWhere you disappear as the shopper gets closer to buying
Presence falls away as intent rises. The comparison and where-to-buy questions are the ones that convert, and the ones most brands lose to a marketplace.
- Visibility split by where the question sits in the journey
- Names the stage that costs you the sale
Visibility by buying stage
where you show up in the journeyThe sources the engines trust in consumer goods
Marketplaces, reviewers and Reddit decide what the engines repeat about your products. Almost none of it is yours, which is exactly why it can be changed.
- Owned versus earned, so you know what to build and what to earn
- Every citation traced to the answer it supported
Which domains the engines cite
856 citationsThe consumer goods brands program
Everything below is included. Measured through the engines’ own APIs, so the same questions can be asked again and the result checked.
- Measure what every major AI engine says about your brand and products today, through the engines own APIs
- The shopper questions your category is actually asked, mapped by product, need and occasion
- Where a retailer, a marketplace or a reviewer is answering in your place
- Which SKU the engines recommend, and whether it is the one you want recommended
- Which sources the engines cite for your category, and which of those you control
- Product and evidence pages built so the engines can read your range correctly
- Re-measurement on the same questions, so the change is provable rather than asserted
What this does not show: what any individual user saw. LBOX measures what the engines answer through their own APIs, which is repeatable and checkable. It is not a record of any one person’s session, and it does not predict revenue.