Two stores can receive the exact same footfall and post very different sales results. The difference almost always sits in what happens between the door and the till — and reading that gap is the focus of this retail analytics course. Rather than opening with definitions, the programme starts where retail managers actually get stuck: comparable stores, comparable traffic, inconsistent results.

Offered by Arab British Fellowship Training Academy, the course connects footfall, conversion rate, basket analysis, transaction reporting and sales-per-square-metre into a single interpretive framework, instead of treating each metric as its own report. Participants learn to ask which number is actually driving underperformance in a given store, rather than reacting to a drop in total revenue without knowing why it happened.

A significant part of the programme is dedicated to dashboards — not as a design exercise, but as a discipline for deciding which numbers deserve a manager's attention and which are noise. Participants also work with product and category performance data to identify where merchandising or assortment changes could unlock additional revenue.

The course is part of the Retail Management Courses category and is built for commercial, not purely technical, decision-making — the goal is faster, better-supported calls on merchandising, staffing and store investment.

By the end of this course, participants will be able to:

• Separate footfall problems from conversion problems when a store underperforms.
• Use basket analysis to identify products bought together and act on cross-selling opportunities.
• Read sales data alongside transaction reports to explain trends, not just report them.
• Apply sales-per-square-metre to compare productivity and spot underused retail space.
• Interpret product and category performance to inform assortment and placement decisions.
• Compare stores fairly, accounting for footfall, size and local conditions rather than raw revenue alone.
• Build dashboards that surface decision-useful information instead of excessive data.
• Turn analytical findings into commercial action across merchandising, staffing and store planning.

Target Audience

• Retail and store managers who need to interpret performance data, not just report it upward.
• Retail sales managers comparing teams, locations and campaigns.
• Merchandising professionals using basket and product data for assortment decisions.
• Retail operations and area/regional managers monitoring multiple locations.
• Commercial managers evaluating revenue opportunities and productivity.
• Business intelligence and reporting professionals connecting outputs to management decisions.
• Professionals preparing to move into retail leadership roles.

Module 1: From Numbers to Decisions — Why Retail Analytics Matters

• How different data sources build one complete performance picture.
• Turning analytical findings into management decisions, not just reports.

Module 2: Footfall Meets Conversion — The Traffic-to-Sales Funnel

• Reading footfall and conversion rate together to locate the real problem.
• Distinguishing a traffic problem from a conversion problem.

Module 3: Inside the Basket — Analysing What Customers Buy Together

• Identifying product combinations and transaction relationships.
• Turning basket findings into cross-selling and merchandising action.

Module 4: Reading Sales Data and Transaction Reports Together

• Recognising trends, anomalies and period-over-period comparisons.
• Using transaction-level detail to explain what sales totals cannot.

Module 5: Productivity per Square Metre — Making Space Pay

• Comparing revenue against selling space across locations.
• Identifying underused areas and space-allocation opportunities.

Module 6: Product and Category Performance

• Where revenue and margin actually come from within the assortment.
• Informing placement, promotion and range decisions with performance data.

Module 7: Comparing Stores Fairly — Benchmarking Across Locations

• Adjusting comparisons for footfall, size and local market conditions.
• Using benchmarks to direct management attention where it is needed.

Module 8: Spotting Trends Before They Become Problems

• Early indicators of declining performance across stores or categories.
• Building a habit of proactive rather than reactive review.

Module 9: Dashboards That Drive Decisions

• Designing dashboards around decision-useful information.
• Avoiding data overload that buries the signal that matters.

Module 10: Turning Analysis into Commercial Action

• Connecting analytics to merchandising, staffing and store-level decisions.
• Establishing a routine for monitoring and acting on retail performance.