Manage assortment with balanced breadth and depth per category
An effective assortment balances breadth (number of categories) with depth (variants per category) based on positioning and available floor space. Destination categories (traffic drivers) require high depth to satisfy specialist customers; convenience categories can have reduced depth. Review the assortment seasonally using sell-through data to eliminate low-rotation SKUs and free space for new lines.
Implement cycle counts instead of a single annual physical inventory
Annual inventory counts are costly, disruptive, and produce accurate data only once a year. Cycle counts subdivide inventory into segments and count a portion each day or week, ensuring every SKU is verified multiple times a year with minimal operational impact. High-value or high-risk SKUs are counted more frequently. The result is continuously accurate inventory at lower operating costs.
Use real-time sell-out data for automated replenishment
Replenishment based on static sales forecasts or manual orders introduces both stockouts and overstock. An automated replenishment system based on real-time sell-out (POS → purchasing system integration) calculates the reorder point for each SKU based on supplier lead time, demand variability, and target safety stock. It reduces manual purchasing workload and improves shelf availability.
Segment customers by CLV and purchase behaviour to personalise communications
Not all customers have the same value. Segmenting by CLV (high, medium, low), purchase frequency (VIP, regular, dormant, one-shot), and preferred categories allows personalised marketing communications: exclusive offers for VIPs, re-purchase incentives for dormant customers, relevant cross-sell based on purchase categories. Personalisation increases email open rates and promotion conversion rates.
Design the returns policy as a competitive lever, not just a cost to minimise
An easy, free, no-questions-asked return policy reduces the purchase barrier, especially in fashion and electronics where perceived risk is high. The repurchase rate of customers who returned with a positive experience is often higher than that of customers who never returned. Analysing return data by SKU and channel identifies quality or product description problems generating returns, allowing root-cause action rather than restricting policy.
Integrate the e-commerce website with real-time per-store inventory
Showing in-store product availability for a specific store on the e-commerce site is a high-impact feature: it reduces wasted store visits, builds trust, and enables BOPIS/Click & Collect. It requires real-time integration between each store's POS system and the e-commerce platform, with a "available" threshold that incorporates a buffer to reduce broken promises.
Measure space productivity by category and store
Every square metre of store space has a cost (rent, utilities). Measuring revenue and margin per square metre per category allows allocating space to the most profitable products. Categories with low space productivity are candidates for space reduction or replacement with better-performing categories. This analysis should be updated seasonally and integrated with category management data.
Apply progressive markdowns based on sell-through data to optimise seasonal revenue
A 50% markdown from day one of the sale season is suboptimal and leaves revenue on the table. Progressive markdowns (e.g. -20% → -30% → -40% → -50%) calibrated to weekly sell-through rates maximise total season revenue: price-sensitive customers wait for larger discounts while non-price-sensitive customers buy at smaller discounts. Markdown optimisation algorithms calculate the optimal depth and timing for each SKU.
Train store staff on recognising anomalous behaviours (loss prevention)
Staff training has the best ROI of any loss prevention measure. Immediately reporting items missing from the shelf without a corresponding sale, monitoring high-risk areas, correctly applying goods-in procedures with delivery note verification, and applying returns policies with receipt verification: these daily procedures reduce both external theft and the administrative errors that generate inventory discrepancies.
Define clear supply chain KPIs with suppliers and monitor them systematically
Supply chain performance depends on supplier quality: delivery delays, order compliance errors (quantity, SKU), and defective products directly impact shelf availability and operating costs. Contractually defining KPIs (fill rate, lead time, order compliance rate, quality) and monitoring them with periodic scorecards enables identifying problematic suppliers and initiating improvement plans before performance impacts sales.
Use traffic heatmaps to optimise store layout and product displays
Analysing customer flow in-store via Wi-Fi, sensors, or video analytics identifies high- and low-traffic areas, "hidden" products that receive little footfall, and customer preferred routes. Promotional displays and high-margin products should be positioned in high-traffic areas. Complementary products (cross-sell) should be adjacent. Data-driven optimisation outperforms visual merchandisers' empirical intuitions.
Build a customer data collection programme that respects GDPR and generates mutual value
Customer data collection - through the loyalty programme, online checkout, app registration - must be based on explicit consent (GDPR Art. 6), limited to data necessary for the service (data minimisation), and generate perceived value for the customer (personalisation, relevant offers, exclusive services). A consent management system integrated into the retail CRM enables honouring customer preferences across all channels.