An interesting article in Economic times
Suchitra and her friends are among the regulars at the Shopper’s Stop store at Inorbit Mall, Mumbai. More often than not during her shopping jaunts, if she opted for an ethnic ensemble, she’d make the trip upstairs to the first floor, to pick out a pair of shoes to go with it. One day, when she walked into the store, she was pleasantly surprised to find that the foot-wear section had been moved to the level below, right next to the Indian wear section She hadn’t planned to buy anything that day, but that’s exactly what she ended up doing. Ethnicwear, shoes, the works.
To Suchitra, it seemed just a coincidence that the footwear section happened to have been moved just where she wanted it. But coincidence, it wasn’t. Rather, the move was the result of an adjacency analysis conducted by Shopper’s Stop, which after sifting through 24 months of customer data, found a pattern wherein it was found that women who buy ethnicwear (salwar-kameez-dupatta) tended to buy footwear as well. Based on this insight, Shoppers Stop moved its footwear section from the first floor to the ground floor where the ethnicwear section was located. Soon enough it found, that this translated into a 25% growth in sales.
Welcome to the world of analytics. Providing retailers valuable insights to decide on where to operate, what to stock, which customers they should try and retain, how to communicate to them and even how to minimise own-store cannibalisation. That’s analytics, the gospel which is increasingly playing a more critical role in the retail business in India.
Most retailers today have revved up on using analytics inside their stores. Shopper’s Stop, for instance, has used analytics to start an internal programme called ‘First Insight’, which leverages its ‘First Citizen’ loyalty database. This has a nine-year historical track of every stock keeping unit (SKU) every First Citizen consumer ever bought from ther retail chain, and in that, reflects the actual buying behaviour of the Indian consumer.
“To benefit from this data we work on models such as analysis of buying behaviour to support merchandise planning,” says Vinay Bhatia, VP - marketing & loyalty, Shopper’s Stop, who also manages the analytics team.
Analytics is being used in the retail sector in three broad areas — studying customers, analysis of transactional data and for predictive modelling. In the first instance, retailers try and track their prime customers, their locations, their lifestyle, socio-economic background and even their level of maturity as buyers. Transactional data throws light on areas like layout planning and adjacencies, where merchandise is moved from one area in the store to another to maximise sales.
The third area is probably the toughest and yet extremely critical — predictive modelling. Using this, retailers can get an idea of how customers’ upgrade their purchase behaviour, categories they might be interested in the future as per changes in lifestyle and where to set up future stores depending on the future lifestyle of consumers in a catchment area. “Retail analytics are very important to ensure the ‘right product, at the right time in the right store’. We have used retail analytics to optimise our supply chain as well,” says Rakesh Biyani, CEO (retail), Future Group. Number Gazing
PRIOR TO opening a Shoppers Stop store at South City Mall in Kolkata, the company studied the buying patterns of ‘First Citizens’ residing in South Kolkata and shopping at the Elgin Road Forum store. This indicated that these customers were shopping for accessories more frequently as compared to apparel. Based on this insight, Shoppers Stop dedicated a much larger space to the beauty section at the new store. “To target better, we have also classified our database into segments — value, premium and bridge-to-luxury shoppers (BTL), and groups based on cultural and occupational affinity,” adds Bhatia.
Like Shopper’s Stop and the Future Group, most retailers can’t stress enough on the importance of analytics in the days to come. Analytics is also a tool likely to be used by retailers to expand their network in the coming time. Therefore, a scientific assessment of the catchment is a departure from the manic retail expansion spree witnessed couple of years back in the market. Says Spencer’s Retail head (consumer insight and consumer intelligence) Pankaj Mishra: “In our future expansion, we would do more of primary research to understand market potential value of the catchment areas. Such analysis helps us in deciding where to open, which format to go for and how many stores to open. Consumption expenditure analysis, category-wise analysis, market potential value analysis are also some of the research exercises undertaken before a robust expansion strategy is drawn up.”
According to Biyani, by monitoring demand rate at stores, the group has been able to push sales in many cases by up to 300%. “Close monitoring on point of sales data coupled with quicker review of the reorder points helped us achieve a new level of consistent sales. Analytics is also playing a
more important role in future store planning,” says Biyani.
Even as there’s bullishness all around, Himanshu Chakrawarti, COO, Landmark Retail says usage of analytics is still at its infancy. “Analytics in Indian retail is still largely limited to studying consumers and transactions. In contrast, sectors like banking in India have matured more in using analytics and even using predictive modelling. But the heartening thing is that Indian retailers have understood the importance of analytics and are now inv e s t i n g significantly,” says C h a k r a w a r t i . Landmark, the book-music-gifts retail chain of the Tata Group has set up an internal team for analytics, which is trying to understand issues like cannibalisation when opening new stores, identifying best locations depending on the address of its regular customers, pinning down consumers who may drop out due to changes in buying habits and come up with strategies to entice them with offers and changes in merchandise.
At Spencer’s, the thrust on analytics recently got all the more stronger, when the retailer used such data analysis to improve sales in some of its low-performing stores. It studied lapses, regular and occasional customers to understand pain points of the stores and the purchase drivers of consumers in those catchment areas. “From the research, we could draw up turnaround strategies for the stores and have seen a success rate of almost 98%,” claims Mishra. For Spencer’s, it may be studying under performing stores, but for Shoppers Stop it’s about dissecting the 1.5 million First Citizen members, identifying BTL and luxury product buyers and then woo them for repeat purchases. “The BTL and luxury segment is growing at over 60% and the frequency of these customers’ visits is significantly higher than normal customers — about three times the industry benchmark. So, rather than communicating to the entire base of First Citizen members for a BTL brand communication, we now target offer, schemes and new launches to this segment.” says Bhatia.
Though use of analytics has begun in right earnest, retailers in India know it will be a while before the players can harness the full potential. So from using analytics to understand consumers shopping trends and category adjacencies, the process is also useful in targetted pricing, merchandise and consumer promotions as well. Like the retail growth story, usage of analytics will also undergo its own learning curve.
