5 Key Ways Retailers Can Boost Margins by taking ownership of and leveraging their data


In today's fast-paced retail environment, businesses must continually innovate to stay ahead of the competition. One of the most effective ways to accomplish this is by leveraging data to optimise operations and increase profits. This white paper will explore five key strategies that retailers can use to harness the power of their data, supported by real-world case studies. By strategically leveraging data, retailers can create a competitive edge and improve their margins.

1. Personalisation: Increasing Customer Loyalty and Sales

Personalisation is essential for creating a unique and tailored shopping experience that drives customer loyalty and sales. By using consumer data, retailers can customise their offerings based on individual preferences and behaviours. For instance, Amazon uses personalisation to suggest products based on a customer's browsing history, resulting in a 29% increase in sales. Retailers can also leverage data to create personalised marketing campaigns, targeting specific consumer segments with tailored promotions and offers.

Case Study: Sephora, a leading cosmetics retailer, leveraged data to create a personalised digital experience for its customers. Through the use of AI-driven product recommendations and targeted marketing, Sephora experienced a significant increase in customer engagement and conversion rates.

2. Inventory Optimisation: Reducing Stockouts and Overstocking

Effective inventory management is crucial for maintaining optimal stock levels and minimising costs. Analysing sales data can help retailers optimise their inventory, reducing stockouts and overstocking. For example, Walmart reduced its out-of-stock inventory by 16% after implementing a new inventory management system, resulting in $3 billion in additional sales. Retailers can also use data to identify slow-moving products and take proactive measures to minimise losses.

Case Study: H&M, a fast-fashion retailer, used data analytics to optimise its inventory levels and reduce markdowns. By identifying and addressing stock imbalances, H&M increased its gross margin and reduced its inventory holding costs.

3. Pricing Optimisation: Maximising Revenue and Responding to Demand

Data-driven pricing strategies enable retailers to identify price points that maximise revenue and respond to changes in demand. By analysing sales data, retailers can implement dynamic pricing models to capitalise on real-time market trends. Best Buy increased its online sales by 89% during the 2019 holiday season by using data analytics to adjust its pricing strategy. Retailers can also use data to identify and respond to competitor pricing, ensuring they remain competitive in the market.

Case Study: Zara, a global fashion retailer, used data-driven pricing to respond to changing market conditions and customer preferences. By constantly monitoring and adjusting its prices, Zara successfully maintained its competitive edge and increased its market share.

4. Supply Chain Optimisation: Reducing Costs and Increasing Efficiency

Optimising the supply chain is critical for reducing costs and increasing efficiency in retail operations. Data analytics can help retailers identify inefficiencies, improve forecasting, and streamline processes. PepsiCo used data analytics to reduce transportation costs by 30% and inventory costs by 20%, leading to a 190 basis points increase in operating margin. Retailers can also use data to improve supplier relationships and negotiate better terms, further reducing costs and improving profitability.

Case Study: Starbucks leveraged data analytics to optimise its supply chain by improving demand forecasting and reducing waste. Through data-driven insights, Starbucks significantly reduced its supply chain costs and improved its overall operational efficiency.

5. Data Monetisation: Unlocking the Value of Retail Data

Data monetisation presents a significant opportunity for retailers to unlock the value of their data, generating additional revenue streams while also benefiting their partners and suppliers. By offering valuable insights and analytics services, retailers can monetise their data, fostering collaboration and driving mutual success.

Case Study: Kroger, a leading US grocery retailer, successfully monetised its data through its analytics subsidiary, 84.51°. By providing suppliers with valuable consumer insights, Kroger generated $140 million in revenue in 2019, contributing to the company's overall operating margin increase. This mutually beneficial relationship not only allowed Kroger to capitalise on its data but also helped suppliers improve their operations, product offerings, and marketing strategies.

In order to effectively monetise data, retailers must ensure the accuracy, security, and privacy of their data, complying with all relevant regulations and ethical considerations. Retailers should also invest in the necessary data analytics infrastructure and develop a clear strategy for data monetisation, identifying key partners, and determining the types of insights that will be most valuable to them.

By embracing data monetisation, retailers can generate new revenue streams, strengthen partnerships, and reinforce their position as key players in the data-driven retail landscape.


In today's highly competitive retail landscape, leveraging data is crucial for businesses seeking to optimise operations, increase efficiency, and boost profits. This white paper has explored five key strategies that retailers can employ to harness the power of their data: personalisation, inventory optimisation, pricing optimisation, supply chain optimisation, and data monetisation. Supported by real-world case studies, these strategies have demonstrated their effectiveness in driving growth, improving margins, and creating a competitive advantage.

To truly capitalise on the potential of data-driven decision-making, retailers must invest in robust data analytics tools, foster a data-driven culture, and continuously refine their strategies based on insights gleaned from their data. By embracing these data-driven approaches, retailers can not only enhance their operations and financial performance but also deliver exceptional customer experiences, fostering long-term loyalty and success in the ever-evolving retail landscape.