Buyer problem
Teams cannot price, forecast, recommend, or compare products confidently when the underlying product data is incomplete or disconnected.
Product intelligence
Available nowKnow your products, enrich weak data, and build the foundation for better decisions.
Zerqano helps teams understand product context, competitor positioning, and relationship signals so downstream pricing, stocking, and recommendation decisions start from stronger product truth.
app.zerqano.com/product
LIVE
Product Relationships
8 products10 connections
Cross-sell insight
Customers buying Wireless Earbuds Pro also buy Phone Case Ultra 82% of the time. Consider bundling for a 14% revenue lift.
Visual walkthrough
What this workflow looks like inside the product.
Start with the primary module for this solution, then view how it connects to command and inventory context.
app.zerqano.com/product
LIVE
Product Relationships
8 products10 connections
Cross-sell insight
Customers buying Wireless Earbuds Pro also buy Phone Case Ultra 82% of the time. Consider bundling for a 14% revenue lift.
app.zerqano.com/command-center
LIVE
Command Center
Condensed live preview
Monthly Revenue
$0
+12.4%
Stock Health
0.0%
3 alerts
Top action
SKU-4821 — Below safety stock
SKU-4821 — Below safety stock
Procurement
Vendor lead time changed +3 days
Inventory
Open Command CenterGenerate PO
zerqano.com/product-intelligence-main
LIVE
Product Relationships
8 products10 connections
Cross-sell insight
Customers buying Wireless Earbuds Pro also buy Phone Case Ultra 82% of the time. Consider bundling for a 14% revenue lift.
What product intelligence software looks like in the current product.
Problem framing
Why this workflow breaks today.
Product context is still scattered across catalog exports, competitor sheets, and one-off enrichment work.
Merchandising, catalog operations, pricing, and commercial teams managing broad product assortments.
Product data is incomplete when decisions are made
Missing attributes, weak descriptions, and inconsistent structure make planning and pricing work much harder than it should be.
Competitor context sits outside the operating loop
Commercial teams often track competitor pricing and product overlap in separate files that never flow back into daily decisions.
Recommendation quality depends on product truth
Cross-sell, pricing, and website recommendations weaken quickly when the item graph is thin or inconsistent.
Current proof
What exists now
- - Map product context into a shared operating layer instead of separate files and tabs.
- - Support competitor-aware pricing and assortment review with connected product context.
- - Strengthen relationship, cross-sell, and recommendation workflows with better item understanding.
- - Connect enriched product truth to pricing, demand, and recommendation decisions.
Operational proof
- - Supports product uploads, relationship mapping, and competitor-aware pricing workflows.
- - Acts as the backbone for cross-sell intelligence and future-facing recommendation experiences.
- - Keeps product context attached to commercial and operational decisions instead of isolating it in back-office cleanup.
Trust and explainability
- - Product context is not hidden behind a single black-box score. Teams can review the product, the relationship signals, and the downstream effect.
- - Competitor-aware and relationship-aware decisions stay attached to the route where they will actually be used.
- - The product layer compounds value because stronger item truth improves pricing, forecasting, and recommendation quality together.
Connected system
This workflow gets stronger because it is connected to the rest of Zerqano.
01
Upload or connect catalog and enrichment inputs.
02
Review product context, gaps, and related-item signals.
03
Route the improved product truth into pricing, cross-sell, and planning workflows.
04
Keep the item graph connected as downstream decisions evolve.
Where it expands next
Expands into stronger competitor mapping, richer enrichment loops, upsell recommendations, and customer-facing recommendation delivery.
Connected modules
Related solution pages
Pricing intelligence
Pricing Intelligence Software
Turn pricing from a disconnected spreadsheet debate into a governed operating workflow with margin context.
Cross-sell intelligence
Cross-sell Intelligence Software
Use relationship-aware intelligence to increase basket value and improve assortment decisions with better product pairing context.
Demand intelligence
Demand Intelligence Software
Use forecast-backed demand signals to guide inventory, procurement, and pricing decisions with less guesswork.
FAQ
Questions teams ask during evaluation.
Get answers about how Zerqano handles product intelligence software and the workflows that connect to it.
No. The point is not passive storage. Zerqano uses product intelligence as a working layer for pricing, recommendation, and planning decisions.