Retail Analytics: Key to augmenting shelf life

The retail sector is a significant contributor to a country’s economy. In 2010, retail consumption accounted for two-thirds of the U.S. gross domestic product at $4.35 trillion. In the UK, retail sales were over £293 billion, according to the British Retail Consortium.

The retail industry has seen upheaval with the global economic crisis and intensely competitive environment, where margins are slimming down and customer loyalty is constantly fluctuating. It is critical for retailers to obtain insights to decide how much and what merchandize to stock, how to operate, and which customers they should fight to retain so that they can move ahead in the competition.

Until about 20 years ago, many retailers thought location was everything. Not anymore! Location, while important, is only one of the criteria from a customer’s perspective.

Here’s where analytics come in. Retailers now understand that they cannot be everything for everyone and are searching for ways to derive more customer intelligence, marketing savvy and operational insight from their overflowing databases. They must define their customer base and then do everything for that group.

Retailers can achieve true competitive advantage with retail analytics technology by using an enterprise-wide approach that involves crossing product, customer and functional boundaries. Here are a few examples:

  • “Market-basket analysis” helps assess links and patterns in the mix of choices/responses that a customer makes. It establishes a correlation between seemingly varied products that a customer chooses. A derivative is “brand switching,” which identifies triggers of switching from one brand to another.
  • “Loyalty analytics” helps mine transactions of customers and recognize trigger events. A leading retailer in the U.S. has two million different offers for customers; no two people get the same coupons. Imagine the complexity of the analytics needed here! Loyalty analytics also helps target competitors’ customers.
  • “Pricing analytics” helps companies understand the most attractive price for that customer. Retailing is no longer simply about sales and discounts. Retailers need to understand who their primary customer is and what price s/he is willing to pay for each product.
  • ”Forecasting” helps retailers understand volumes likely to be sold and when. Analytics can help correlate sales figures with macroeconomic factors such as labor, stock market variation, employment data, weather conditions, currency fluctuation, oil market data and so on.
  • “Supply chain and inventory optimization” helps retailers optimize their inventories. This is particularly helpful for perishable or seasonal products.
  • “Promotion analytics” helps retailers understand which promotional campaigns are profitable and which aids them in designing future promotion campaigns.
  • “Psycho-demographic segmentation” divides the market into groups that share common characteristics to accurate and time-based market response propensity models.
  • “Web analytics” offers retailers an insight into how customers are talking about them on various social media platforms by mining thousands of lines of text data and determining patterns in them.

Tata Consultancy Services (TCS) offers a wide range of offerings around customer analytics in the retail space. Our offerings are end-to-end involving all aspects of customer buying, satisfaction, loyalty and customer value. No longer is retail just about buying and selling — analytics is helping not only address the right customer but also predict buying behavior in the future.

Kiran’s Profile:
Kiran is a analytics professional working on the Retail and CPG industry domains. His team provides analytic solutions in direct marketing, loyalty analytics, customer analytics, pricing, segmentation, space optimization and predictive modeling solutions to retailers. Kiran has over 12 years of experience and analytics, BI and consulting in companies such as Symphony-IRI, SuperValu and Tata Consultancy Services.

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