Buy Vizit if you need to know which product image converts and why — it measures imagery but never makes any, so pair it with something that generates the assets and fills the attributes it doesn't touch.
Vizit and Anglera solve different halves of the problem — this page is about the seam between them.
Every tool in this market sells you one act and calls it the whole play. The useful question isn't whether Vizit is good at its act — it's what happens to the other two.
Mine every spec from every source.
Every value traced to a document you can open. The catalog is only as honest as what it was built from.
Aim the catalog at the buyer who actually buys.
Grounded data still loses if it answers questions nobody asked. Alignment is what turns specs into conversion.
Product data is a practice, not a project.
Markets move, suppliers reissue, buyers change what they ask for. A catalog that is right in March is wrong by August unless something is watching.
Scored against public documentation. Grouped by the three acts — so you can see which ones Vizit leaves on your desk.
Reads images for visual cues, not spec documents
PDFs, spec tables, drawings, manuals, images, sites
Scores existing imagery; proposes no new attributes
Proposes fields your schema never had
Visual analytics only; no attribute value normalization
Normalizes and governs allowed values, versioned
Category benchmarks for scoring; no SKU classification
Auto-classifies; channel and marketplace mapping
Explains score drivers via visual cues; no value citations
Every value cites its source doc and page
Audience Lens scores same image per consumer segment
B2B specifier and B2C shopper enriched differently
Behavioral image data and competitor benchmarks feed recommendations
Reviews, search, competitor rails, social — fed back
Imagery only; no titles, descriptions, or bullets
Original copy per persona and channel
Scores and reorders existing images; generates none
Generates studio-grade imagery for photoless SKUs
Always-on monitoring; automated monthly benchmark updates
Re-enriches on its own after go-live
Vizit Score is the core product; tracks over time
Scored against your standards; nothing publishes below bar
Salsify app reorders PDP carousel; no attribute writeback
Writes back to PIM, ERP, warehouse, commerce
Salsify app integration; no public API docs found
API, webhooks, and MCP servers
Software recommends; brand's team creates the content
Anglera owns the work; review is a guardrail
“Buyer signals” is the emptiest phrase in this category, so here is the literal thing. Each of these is an observation from a live market, the gap it exposes, and the field that gets created as a result.
“Handle hits the wall when you open it” shows up across the 2- and 3-star reviews on a brass ball valve — and in the return reasons behind it.
Clearance is why the product came back, and no field anywhere describes it.
Handle Clearance (fully open)Millimetres, measured from valve centreline“left hand thread” is searched steadily on your own site and returns zero results — while you stock 240 left-hand-threaded SKUs.
You have the products. You do not have the attribute, so search cannot find them.
Thread DirectionRight-hand (RH) · Left-hand (LH)Contractors comparing compressors argue about noise in decibels months before any RFQ mentions it.
The dB rating is sitting in the supplier PDF. It is not a field, so it is not a filter.
Sound Level (dB)dB(A) at 1 m, integerFour of six competitors let a buyer filter welders by duty cycle. Your category has no such field.
Buyers who filter on duty cycle never see your catalog at all.
Duty Cycle% at rated amperage (e.g. 60% @ 200 A)Page 4 of the datasheet has “Ambient operating range −20 °C to +60 °C” in a table nobody ever mapped.
The data arrived years ago and died in a PDF because no field was waiting for it.
Ambient Operating RangeMin/max °C pairListings bounce for a missing Country of Origin that is printed on the packaging and in the customs paperwork.
A required field for the channel that was never required by the PIM.
Country of OriginISO 3166-1 alpha-2Every enrichment tool on the market takes your schema as a given and fills the blanks in it. That ceiling is invisible: your catalog can hit 100% complete and still be missing the attribute that loses the sale — because completeness is measured against a schema someone drew years ago.
3/4 in0.75"3/4"19mm3/4 inchDN200.75 in (DN20)Six suppliers, six spellings, one physical size. Filters only work once they agree.
BlkblackBLACK MATTEMatte BlkRAL 9005Black — MatteFree text makes a colour filter useless. A governed value makes it a facet.
SS316316 StainlessStainless Steel 316A4 StainlessStainless Steel — 316 / A4Same alloy, four vocabularies, plus a trade name. Buyers search all of them.
Vizit is a Boston-based visual AI platform that predicts how product imagery will perform in ecommerce. Its patented models scan a stated 15,000+ visual cues per image and apply "Audience Lens" scoring — trained on online behavioral data rather than surveys — to predict how a given consumer demographic responds. Products include Vizit Score, PDP Visual Grader, always-on Content Effectiveness Monitoring, and a Conversion Optimizer app for Salsify that automatically reorders PDP carousel imagery. Publicly named customers include L'Oréal, Mars, Kimberly-Clark and Ghirardelli; it raised a $25M Series B led by Industry Ventures in October 2024.
Pricing: Not publicly disclosed. Vizit publishes no pricing page or tiers; all paths route to a demo request. The only public signal is a G2 reviewer noting that cost made it hard to justify as a global rollout across multiple markets, which points to enterprise contracts scaled by market or catalog scope. Treat any figure as unverified until quoted.
Vizit websiteCPG and brand teams with a full creative pipeline already producing imagery, who need audience-specific evidence on which asset converts and how to order the PDP carousel.
We'd rather tell you here than in month three of an implementation.
Capability verdicts reviewed against Vizit's public documentation on July 14, 2026. Vendors ship quickly — if something here is out of date, tell us and we'll correct it.
Bring one category. We'll run Schema Foundry against it and show you the fields your schema doesn't have yet — on your own SKUs, in 30 minutes.
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