// COMMERCE INTELLIGENCE
Visual Search: Turn Your Customers' Cameras into a Sales Channel.
Walls of text in search bars are the biggest hurdle for mobile buyers. With Xanevo's Visual Search solution, your customers find products through a simple photo, precise, fast, and without painful term-searching. You don't need to rebuild your system, we attach visual search as a performance layer on your existing architecture.
More than just image recognition.
01
How it works
How AI understands images
02
Business value
ROI from visual search
03
Integration
Connection to SAP, Dynamics, and co.
How does visual search improve conversion rate?
Visual search massively reduces time-to-product by eliminating the cognitive load of text search. Instead of searching for the right technical term for a spare part or style, the customer photographs the object and gets matching hits. Technically, both product images and search images turn into image vectors (numerical representations) that get matched via pattern matching against the vectors of your product catalog (golden records). The cleaner the PIM data, the higher the hit rate. The result: fewer search abandonments, higher mobile conversion, reduced user friction.
// COMPARISON
Text search vs. visual search
Aspect
Classic text search
Xanevo Visual Search
Input
User must know technical term
A photo is enough
Mobile UX
Typing work, high bounce rate
Camera tap, low friction
Style search accuracy
Low (words fail)
High (form, color, pattern)
Spare part search
Frustrating without article number
Photo of the broken part is enough
Database
Product names plus tags
PIM attributes plus image vectors
// PRODUCT MODULES
Three modules for image recognition, business value, and integration
Module 1: How it works, From photo to hit
The customer image is converted in real time into a vector that numerically describes visual features (form, color, pattern, category). This vector gets matched against the pre-indexed vectors of your product catalog. The nearest hits land in the result list, sorted by similarity. Under the hood this runs on established embedding models, no vendor lock-in.
Module 2: Business value, ROI through mobile excellence
Mobile search abandonments cost your shop conversions daily. Visual search reduces time-to-product specifically on the device with the highest friction. For complex assortments (spare parts, fashion, home accessories) conversion lifts in the double-digit range are realistic. ROI sits not in the feature, it sits in the lost sales that no longer get lost.
Module 3: Integration, Performance layer instead of rebuild
We attach visual search as an API layer to your existing shop and PIM architecture. No migration, no frontend rebuilds. Through the Legacy-to-AI Bridge we pull PIM data, index it as vectors, and deliver hits back via API. Frontend performance stays untouched because vector search runs on dedicated compute.
// FAQ
Three questions e-commerce managers and CTOs ask
Our AI workflows can optimize image data before matching (background cleanup, normalization), but high-quality golden records in the PIM dramatically increase hit accuracy. Before rollout we run a short data quality assessment that shows where optimization pays off.
Through our Legacy-to-AI Bridge we connect the search engine without deep changes to the core system. SAP stays the source of product data, image vectors sit alongside in an optimized vector store. Typical implementation takes 4 to 8 weeks to first productive search.
Yes, Xanevo uses frameworks that store or process no personal data in search images. The customer image gets used for vector calculation and then discarded, only the anonymous search query is stored for performance analytics.
// VISUAL SEARCH
See Visual Search live in your assortment
Give us an excerpt of your product images. In 2 weeks we build you a live demo with your own data so you can concretely check how good the hits are in your category. Pseudonymized, no upfront costs.