Search and product discovery remain key drivers of conversion rate and revenue per visitor. Ensuring these experiences are powered by high-quality signals is critical.
Not all signals are equal, and offline revenue is a crucial one.
For many commerce organizations, the data powering their AI reflects only a fraction of how customers actually buy. Online purchase signals flow into models cleanly, but the rest, in-store transactions, EDI orders, and sales-rep-entered purchases- has largely gone uncaptured.
The result is AI that reflects only a partial view of customer demand, no matter how well-tuned the models are.
Shoppers move fluidly between channels, browsing online and purchasing in-store, or visiting a physical location before completing a purchase through a procurement system. Delivering relevant experiences across these journeys requires AI.
And AI is only as good as the data behind it.
Untapped Signals in AI Search and Product Discovery
Coveo’s customers are complex businesses. They are large omnichannel retailers, B2B distributors, and brands operating across multiple channels. For many of them, offline transactions often represent the majority of revenue.
In practice, “offline” can mean different things:
- Retail: in-store purchases
- B2B: EDI purchase orders, punchout transactions, or sales rep–entered orders
These are not edge cases, they are core to how business gets done.
Yet there’s an untapped layer of signal that could meaningfully boost the performance of AI-powered search and discovery: the offline behavior that most models have never seen.
Customers have attempted to fill this gap, but these approaches typically create unnecessary complexity for implementations.
They’re workarounds rather than solutions.
Introducing Offline Purchase Ingestion
Coveo Offline Purchase Ingestion, currently in Early Access for CYQ2 2026, is a secure API for sending standardized offline purchase data into Coveo.
Whether purchases come from in-store POS systems, EDI orders, or ERP-managed transactions, they can be ingested in batches, validated against a standard schema, and made available alongside online purchase data.
In short, this gives Coveo AI a more complete view of total purchase behavior which helps to improve recommendation accuracy, product popularity signals, and catalog coverage, while driving higher revenue per visitor for omnichannel and B2B customers.
What This Unlocks for Your AI
Once offline purchases are incorporated into Coveo, they strengthen the signals that power your AI across the platform.
Better popularity signals across your full catalog
When AI only sees online transactions, its understanding of demand is inherently partial. Incorporating offline purchases provides a more representative view of product popularity improving rankings and discovery experiences.
Expanded catalog coverage
Products primarily purchased offline often lack sufficient online signals to be recommended effectively. By including offline purchase data, these products become part of the recommendable catalog —increasing coverage and surfacing previously underrepresented items.
Stronger cross-sell and upsell insights
Offline transactions reveal which products are purchased together, making Coveo’s AI-powered recommendations and cart strategies more effective across the full range of customer buying behavior.
Who This Is For
Offline Purchase Ingestion is designed for Coveo Commerce customers who operate significant offline channels alongside their online storefront and can export purchase data from systems such as POS, ERP, or data warehouses.
Demand is already strong among large retailers and B2B distributors operating across physical stores and other offline channels.
If a meaningful portion of your revenue flows through channels that haven’t been previously captured, this feature is built for you.
Speak to your Coveo account team about joining the early access program.