How Retailers Can Survive & Thrive using Data Analytics

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Understanding customer data can help retailers in a variety of ways. Data can be used to track customer behaviour, determine which products are selling well, and identify areas for improvement online and in store.

Data is becoming increasingly important for retailers as the industry becomes more competitive. To provide a better shopping experience and stay ahead of their competitors, retailers must harvest information about what their customers want and need. In this article, Andrew Bithell explores how digitally savvy retailers are using cloud-based, cross-functional data sets and analytics to transform retail through highly targeted optimisation across the entire operation. 

Collaborative Business Intelligence

There has always been a need for retailers to understand and respond to changes in customer behaviour, but today’s customer activity is more nuanced than ever before. In 2023, the rising cost of living is impacting how people shop. Increasing prices lead to an increasing range of product types, which makes some retailers – and some categories – more susceptible to recessionary conditions.

As retailers become increasingly digitally empowered, they are exploring more advanced Machine Learning (ML) and Artificial Intelligence (AI) techniques to take a more refined approach to peak season forecasting.

Advanced analytical tools provide a chance to rethink every aspect of a retailer’s operations. Today, retailers can analyse pricing decisions at SKU level in granular detail, not only to reduce warehouse stock and to optimise supply chains, but also to improve customer experience, achieve sustainability goals, and increase margin. And, as a result, the customer experience and retail performance are being transformed as a result of that insight.

Cloud-Based Analytics

From reducing infrastructure and storage costs to enabling real-time access to inventory and operational data, cloud services benefit the retail industry in a variety of ways:

  • Traceability of stocks and insight: Overstocking or understocking, which affects business profitability, is the ultimate budget headache. Cloud helps to solve this problem by tracking inventories at all stages without the restrictions of traditional systems.
  • Remote Warehouse Management: Migrating to cloud software allows businesses to have offsite access to all inventory locations, live inventory volume, location of delivery centres, and more.
  • Managing Supply Chain in Cloud: Tracking inventory manually takes a lot of human time, but with inventory in the cloud, inventory management, order placements, and requisition are automated.
  • POS updates: Real-time Inventory updates from back-office system to POS (integration between POS & back-office).

In addition to leveraging the extraordinary wealth of data generated by real-time supply chains and customer behaviour, organisations are also harnessing the power of the cloud to combine and analyse diverse information resources quickly. Insight is no longer limited to a specific business area – such as the warehouse or point of sale. With powerful analytics tools, a retailer can now understand the business, not only at store or category level, but down to the individual customer experience.

Priorities and optimization

Customer behavioural data is fuelling ever more accurate predictions and forecasts. By leveraging analytics tools, peak season is no longer just about maximising (often discounted) sales, but utilising the additional customer traffic to address a key business challenge.

This cross-business insight is allowing retailers to ask more complex questions. To minimise the cost of storing aged stock, is it more cost-effective to sell off additional stock? Does the stock’s inherent value ensure that despite the cost of storage, the margin will hold up for a while?

In most retail operations, logistics is the priority, with advanced analytics being used to optimise the transportation of containers into the UK and then to stores in the most sustainable and effective way possible. Strategic planning is being driven by data to better forecast demand, plan inventory requirements, estimate logistics needs, and automate processes.

The use of analytics also allows retailers to entice shoppers in a different way, whether that is to use offers to bring shoppers into stores and expose them to different product lines or to take a more intelligent approach to localisation. Customer expectations are now being set by those retailers using data to be more exciting and create a more compelling offer.

And, profitability is being safeguarded. For retailers, dynamically updating pricing for the most optimal sales and revenue targets requires monitoring multiple rapidly changing variables, such as the pricing offered by competitors and consumer demand for select products.

Conclusion

With the right skills and correct inference from retailers, data analytics can transform the entire peak season event in a way that reflects each retailer’s specific business. It doesn’t matter if it’s increasing customer loyalty or boosting brand image by delivering customer satisfaction, or reducing costs by cutting wastage and improving productivity, data analytics are essential to transforming retailers’ profitability.