Retail data partnership

Find where retail profit is leaking.

Sales can look strong while returns, stockouts, markdowns and delivery issues quietly erode the result. DataDive works with your leaders to connect the data behind those losses, show where to act, and measure whether the changes work.

Start with one commercial measure.Get a useful connected view in weeks, then improve it with your team.
RETAIL OPPORTUNITY MAPCONNECTED VIEW
Where could the next improvement come from?
AvailabilityStock on shelf
ReturnsAfter the sale
MarkdownsPrice + range
FulfilmentDelivery promise
One view across sales, stock, returns and operations
Choose where to start

One retail performance question. Many signals behind it.

Each issue crosses systems and teams. Select a lever to see how a data partnership helps turn it into a measurable improvement.

STOCK AVAILABILITY

Keep the products customers want available.

See demand, stock and sell-through together by product and location. Your teams can spot lost-sales risk earlier and make replenishment decisions with one set of numbers.

The measure to moveStockout rateTrack by product, store and week against your own baseline.

DataDive’s role: Consolidate POS, ecommerce and inventory data; agree on a stockout measure; make the weekly changes visible.

Gartner research puts returns fraud at nearly 14% of U.S. retail returns and finds that over half of retailers still use manual review for return claims. Connected sales, returns and fulfilment reporting gives teams a clearer place to start.

What working together looks like

From disconnected reports to a weekly improvement rhythm.

You bring the commercial priorities and the people who can act. DataDive brings the data integration, reporting and measurement discipline.

01Consolidate

Join the relevant POS, ecommerce, returns, inventory, fulfilment and finance data.

02See the leak

Use clear reporting to find the products, locations, channels or processes behind the measure.

03Act and track

Review changes with your team each week and see whether the agreed metric moves.

Move in weeks, not months

A first useful view, then a cycle of improvement.

We scope the first phase around one priority measure and accessible data sources. Once the view is working, your team can test a change and see what happened.

A first-view aim of 2–4 weeks depends on source access, data quality and scope. We agree a realistic schedule before work begins.
Week 1Agree the metric and baseline
Weeks 1–2Connect the critical sources
Weeks 2–4Review the first performance view
ThenTrack decisions and their impact
AI as the next layer

Better forecasts begin with a better retail picture.

Once sales, product, stock and return information is consistent, AI can help explore demand patterns or group return feedback. We would start with a specific business task and keep the trading team in control of the decision.

Your first opportunity

Where is performance slipping in your business?

Tell us the measure you want to move. We’ll discuss the data behind it and a focused first phase.

Discuss my retail opportunity Your priority is added to the enquiry form and can be edited there.