Retail Analytics Solution

Maximize results with advanced analytics for retail

The retail industry is in the midst of unprecedented transformation. Competition from new digital channels, the emergence of large and niche e-commerce players, and a new generation of savvy customers with ever-changing tastes and preferences and an expectation of personalized retail experiences are just some of the challenges retailers have to grapple with.

Retailers also have something they did not have until a few years ago – an abundance of valuable and granular data about their business at a store and item level, about their competitors and about their customers. Ultimately, for retailers it is about getting the basics right – accurately predicting what their customers want and giving them the right products, at the right place, time and price. Retailers who can do this well will succeed, and retail analytics is a powerful tool to help companies achieve this goal.

Analytic Edge’s end-to-end Retail Analytics solution that brings together data from across a retailer’s business to generate actionable insights on various aspects of retail marketing and sales planning and execution.

Assortment Optimization and Shelf Space Allocation – This allows retailers to optimally plan their shelf space and product inventory – historically amongst their most valuable assets. Analytics can estimate the sales and profit impacts of different planograms and store layouts which can then be implemented at a store cluster level or even an individual store level to maximize results.

Customer-Driven Marketing – This uses data from loyalty cards, credit card and other sources to analyse customers’ shopping behaviours, purchase patterns and needs at an individual level. Retailers can then target them with products and offers they are most likely to respond to.

Demand Forecasting – Forecasting demand in retail is significantly more complex than in many other industries due to the thousands of different products and SKUs, multiple stores across regions, changing customer trends and preferences, and the impact of seasonal changes and special events such as holidays and festive seasons. The forecasting solution leverages cutting-edge statistical techniques to deliver an accurate forecast of demand and sales down to the store or even item level over an extended period.

Localization and Clustering – In the retail industry, customers’ demand for products and their response to product assortments, store layouts, pricing and promotions usually vary by region and by the demographic and behavioural attributes of customers. The localization and clustering solution provides insights that allows retailers to tailor multiple aspects of retailing to similar clusters of stores in order to maximize sales, profits and overall customer experience.

Marketing Mix Modeling – This allows retail marketers to determine which marketing vehicles provide the greatest sales impact and how they must optimally allocate their marketing and promotional spends across the numerous channels available today – TV, print or radio advertising; digital and social advertising, search engine marketing, sponsorships and more.

Pricing Optimization – This leverages analytics on point-of-sales data and seasonal sales data at the store level to recommend the optimal pricing of products over their entire lifecycle in order to maximize sales.

Product Recommendation – Retailers today offer a very large assortment of products across multiple categories, especially on their online channels where physical space is not a constraint. Customers must navigate through hundreds or thousands of choices in physical or online stores to find products they may be interested in. Often this means customers will end up not seeing a product they may have liked. The product recommendation solution uses analytics to recommend relevant products to customers based on “collaborative filtering” (what other customers who bought a product are also buying) or other recommendation techniques. This allows retailers to proactively put the right products in front of the right customers at the right time, thereby not just increasing sales but significantly improving the personalized shopping experience for customers.

Test and Learn – Retailers constantly try new innovations and tweaks in their stores to achieve improved results. However, for large and medium sized retailers, rolling out such changes across their entire chain can be a costly proposition fraught with risk. Test and Learn allows retailers to experiment with changes in a small random sample of stores and observe the results before deciding whether or not to implement them across all their locations.

Retail Analytics Solution Benefits

  • Optimize shelf space and inventory
  • Target customers with personalized offers
  • Tailor store clusters to customer preferences
  • Maximize marketing ROI
  • Dynamically optimize pricing over product lifecycles
  • Make intelligent product recommendations
  • Try store innovations risk-free