Retail · Illustrative case study

How a multi-location retailer can connect promotions to store sales

A retailer spends across search, social and email but sees platform reports separately from stock, loyalty behaviour and store sales.

The decision problem

Activity is visible. Commercial contribution is not.

Campaign reports optimise for clicks and attributed online actions while much of the revenue occurs in stores.

Promotions may continue even when advertised stock is constrained or unevenly distributed across locations.

Email, paid media, loyalty and point-of-sale data use different customer and product definitions.

Evidence to connect

The smallest useful information set.

  • Campaign spend, creative, audience and geography
  • Product, promotion, margin and store-level sales
  • Stock availability and replenishment constraints
  • Consent-based loyalty behaviour and repeat purchase patterns
The practical plan

Move from scattered signals to accountable action.

01

Define a campaign ledger

Create one record of campaigns, dates, products, locations, audiences, spend and intended commercial outcomes.

02

Connect stock and sales context

Compare campaign activity with product availability and store outcomes so marketing is not evaluated in isolation.

03

Build comparable location views

Use consistent definitions while retaining the local factors that affect performance, such as catchment, range and trading conditions.

04

Run controlled improvements

Test selected promotions or audiences against a baseline and record the decision, assumption and result.

Measurement framework

Signals that support a better decision.

  • Sales and margin movement during defined promotion windows
  • Cost per new or reactivated customer where matching is appropriate
  • Stock-out exposure during promoted periods
  • Repeat purchase and customer-segment response
  • Incremental evidence from controlled location or audience tests

Evidence standard: these measures describe what should be tested. They are not performance claims. Any real result would require an agreed baseline, reliable data, sufficient observation and the client's permission to publish.

Apply it to your business

Start with your evidence—not assumptions.

We will map the real customer journey, decision gaps and smallest useful first project.

Discuss your situation