Omnichannel

How fragmented retail data is quietly driving lost sales

As retailers look for ways to improve margins without compromising customer experience, operational data collaboration is becoming a critical competitive differentiator.

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August 4, 2026 by Grant Smith — General Manager, Fintech - SBT Division

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Despite generating more data than ever before, retailers across the industry rely on incomplete and disconnected data that quietly drives missed sales opportunities and diminishes customer experience. Data has long been treated as a competitive asset to protect rather than a shared resource with suppliers to optimize performance. Against the current economic backdrop of rising inflation and higher gas prices, that mindset is quietly costing both retailers and suppliers millions.

In many cases, operational data is fragmented, inaccurate, and difficult for retailers and suppliers to use collaboratively. This is particularly true for direct store delivery (DSD) and scan-based trading (SBT) categories. Critical data, such as sell-through rates and real-time inventory levels, are either delayed, limited, withheld entirely, or simply non-existent for DSD and SBT inventory. Sometimes this is a symptom of the data volume and complexity of managing such a large dataset. Other times, it's viewed as too valuable to share with partners, particularly in wholesale inventory models.

While sales data is more ubiquitous and standard in many retail-supplier relationships, visibility into what's on the shelf, for how long, and at what quantities is often limited. Poor visibility creates out-of-stocks and missed sales. Collaboration proves an effective strategy for optimizing inventory and eliminating customer friction.

In one example, an apparel company kept shipping product to several retail locations where no sales were recorded. Exception reporting flagged this anomaly, leading to the discovery that the product was collecting dust in the back of the store rather than being merchandised. By collaborating on verified store-level data, the apparel company worked directly with the retailer to ensure the product was merchandised and scanned, improving product availability and retail sales performance for both parties.

Accurate demand forecasting, consistent product availability, and effective pricing strategies depend on shared operational visibility. The insights derived from this approach are a path to cost savings and recovering missed sales. It's a strategy that ensures high-demand products are on the shelf and low-demand product quantities are adjusted accordingly. Most of these insights are found at the micro-level: a small inventory discrepancy typically attributed to shrinkage, which, when combined across a national store footprint, totals millions in potentially lost sales. Identifying these small anomalies is only possible when the data is shared, verified, and actionable.

Better visibility improves product availability

For retailers, the customer impact is immediate. Product availability remains a critical competitive advantage for brick-and-mortar retailers. Consumers expect quick access to products, and an empty shelf is a lost transaction that often compounds into an abandoned basket. Retailers typically identify out-of-stocks only after sales have already been lost and customer loyalty has been subsequently tarnished. This adds up quickly when multiplied across thousands of categories and hundreds of stores.

A large flower producer and wholesaler illustrates the value of shared operational visibility. During major holiday events, retail partners frequently reported stockouts after customers had already encountered empty displays and complained about product availability. By leveraging sales data to identify high-performing locations and demand patterns, the wholesaler was able to anticipate replenishment needs before inventory was depleted. Rather than waiting for stores to sell out or retailers to request additional product, the company used near real-time sales insights to proactively replenish inventory. This approach reduced out-of-stocks during peak demand periods, improved product availability, and improved customer experience.

Timely visibility into point-of-sale and DSD data helps suppliers prioritize stock replenishment and respond to inventory needs. Maintaining the stock of a high-demand product benefits retailers and suppliers alike, and collaborative insights motivate replenishment. A propane company, for example, uses the previous weekend's sales data from national retail partners to identify high-demand locations and prioritize replenishment before the next weekend, which is a peak purchasing period. For their retail partners, this approach has supported a 10-20% annual sales lift for the product category.

Reconciling pricing and promotion errors

Pricing and promotion failures create immediate customer friction while quietly eroding retailer margins.

Price book discrepancies are often a symptom of fragmented or mismatched data. A promotion that appears on the shelf but fails at checkout immediately undermines customer confidence. Identifying these occurrences becomes much more effective with shared insight into inventory sales and availability.

What effective retail data collaboration looks like

This isn't about collecting more data. Most retailers and suppliers already have the information needed to collaborate strategically, but each side only sees part of the operational picture. Retailers have sales data. Suppliers have data on delivered inventory. Individually, those datasets provide limited visibility. Combined and validated, they create a single source of truth with a clearer view of inventory performance, customer demand, and operational gaps that both sides can act on.

But this data is only valuable when it is verified, standardized, and actionable. Managing this across a network of suppliers, categories, and store locations adds significant complexity. The organizations seeing the strongest results are prioritizing data accuracy, standardization, and real-time visibility. Emphasis is placed on creating a reliable operational foundation that helps retailers and suppliers respond faster and make better decisions together.

As retailers look for ways to improve margins without compromising customer experience, operational data collaboration is becoming a critical competitive differentiator. Treating data as proprietary rather than a collaborative opportunity is becoming a liability. Retailers that can turn fragmented data into shared, actionable visibility with their supply partners will be better positioned to get the right products on the right shelves at the right prices and at the right time. Ultimately, shared visibility reduces friction, optimizes inventory, and enables both sides to respond faster to consumer demand.

About Grant Smith

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