Business Performance Analyst

Selecta is the largest provider of unattended self-serve coffee and convenience food in Europe, leading the way in vending solutions and specialist coffee services.

Selecta operates across 16 countries within Europe, serving 12 million people every day. Within the UK, we deliver a national service trusted by circa 3,500 businesses to provide digital-first vending solutions across workplaces, schools, universities, hospitals, transport hubs, and other high-traffic environments.

As a 24/7 food and drinks distribution and technology-led powerhouse, Selecta provides millions of moments of joy to end consumers across Europe. Our solutions include digital vending machines, coffee machines, smart fridges, snack markets, and other unattended retail formats.

The Business Performance Analyst provides dedicated analytical support to the Commercial & Operational Excellence Lead, using machine-level, product-level, transactional and operational data to identify where performance can be improved across the machine estate, and to translate those opportunities into practical, implementable actions.

Areas of focus include machine productivity, product and range performance, planogram optimisation, consumer pricing and price/volume optimisation, gross margin, product availability, wastage, service productivity and visit efficiency, and the design and measurement of performance trials.

This is not a reporting-only role. The successful candidate will be curious and commercially minded, comfortable investigating why performance differs between machines, products, locations, customers and operational models, and confident using SQL to access and shape their own data rather than depending on BI for every question.

• Analyse machine-level performance, sales per machine, vends, average selling price and availability, to identify opportunities to improve sales, gross margin and profitability.
• Proactively interrogate machine, product and operational data to surface improvement opportunities, rather than relying solely on predefined requests.
• Identify high- and low-performing machines, locations and customer segments, and investigate the drivers behind the differences.
• Benchmark apparently similar machines and sites to understand why performance differs, and identify ways to improve the economics of underperforming locations.

• Analyse product-level sales, rate of sale, selling price, cost and gross margin by SKU, machine, site and category.
• Combine sales history with machine capacity, facings, expected demand, service frequency and target fill to determine the optimal range, facings and fill for individual sites or groups of similar sites.
• Identify products occupying capacity that could generate more revenue or gross profit if reallocated, and slow-moving lines that should be reduced, replaced or removed.
• Support increasingly data-led planograms, analyse the impact of changes after implementation, and refine recommendations based on actual results.

• Analyse selling price, sales volume, product cost and gross margin at SKU, machine and site level.
• Identify products where pricing may be restricting volume and total gross profit, and products where a price increase is possible with limited volume impact.
• Develop hypotheses on consumer price elasticity, and design and analyse controlled pricing trials against appropriate control groups.
• Evaluate the interaction between price, volume, mix and margin, and recommend actions based on total financial opportunity rather than margin percentage alone.

• Identify opportunities to improve gross margin through product mix, range,…