How data is transforming retail decisions
Data and analytics are revolutionising the retail industry. Retailers are collecting vast amounts of data and using it to gain insights that inform key business decisions. From supply chain management to marketing campaigns, data is transforming operations and strategy across the sector.
The rise of big data in retail
Retailers today have access to huge amounts of structured and unstructured data from various sources. This includes transaction data, customer profiles, web traffic, social media activity, mobile data, and more. Collectively known as “big data”, this wealth of information offers unprecedented visibility into customer behaviour and market trends when analysed properly. Retailers are investing in data infrastructure and analytics tools like Retail Express to help process big data into actionable insights.
Optimising supply chains and inventory
One of the biggest applications of retail analytics is around optimising supply chain management. Retailers are using historical sales data and demand forecasting algorithms to gain insights into optimal inventory levels. This helps retailers avoid overstocking while still meeting customer demand. Data helps predict peaks in demand during promotions or holidays so stores can be stocked accordingly. Retailers are also using analytics to optimise distribution networks and minimise logistics costs.
Personalising marketing campaigns
Customer data enables retailers to segment shoppers and tailor marketing campaigns to their interests and purchasing habits. Retailers create detailed customer profiles by collecting data across channels including in-store purchases, website activity, mobile apps, and more. These profiles allow retailers to personalise promotions, product recommendations, and advertising through email, apps, social media and more. Targeted campaigns improve conversion rates and customer loyalty.
Optimising pricing and promotions
Data is enabling retailers to be more strategic and precise when it comes to pricing and promotions. Basket analysis reveals insight into customer price sensitivity for certain products. Retailers use this to optimise pricing strategies across product categories. Sales data also helps retailers measure the true impact of promotions on buying behaviour. This allows them to plan promotions that genuinely drive sales rather than just discount prices.
Enhancing in-store experiences
In-store analytics, based on security camera feeds and sensors, provides data to improve the in-store experience. Retailers analyse store traffic patterns and dwell times to optimise store layouts and merchandise displays. Data also enables staff scheduling optimisation to have the right employees in store when customer traffic is highest. Some retailers use video analytics to measure customer demographics, emotions, and engagement with displays. This provides insight into improving in-store experiences.
The future of data-driven retail
As technology evolves, retailers will have access to even more data to derive actionable insights from. For example, Internet of Things sensors will provide real-time visibility into products and supply chains. Predictive analytics and machine learning will enable increasingly accurate demand forecasting and customer insight. Data will be pivotal in creating hyper-personalised, seamless shopping experiences across channels. The retailers that best leverage data analytics will have a competitive edge in the marketplace. Though data offers many benefits, retailers must also ensure proper data governance and security as they advance their analytics capabilities.