Companies don’t decide how customer centric they are, they cannot rate themselves on this. In today’s age of the customer, it’s your wife or my daughter who decides how customer centric a particular brand is. And yet when corporate executives talk about customer relationship management (CRM), most eyes just glaze over. CRM has been around for the longest time, from just an efficiency improvement tool it has morphed into a customer experience multiplier, if used correctly. CRM is a customer information based strategy that can help retailers deeply personalise their offerings and become far more relevant to customers. So at its heart, CRM needs access to data and means to convert that data to actionable information.
Retailers and consumer-packaged-goods (CPG) companies have long had access to vast amounts of transaction data: every day Hypermarkets, Grocery stores and Supermarkets capture information about every SKU sold to every customer at every store. This is very powerful data and not every retailer is able to convert this into value added information. Strong CRM programs and data savvy retailers are able to convert this Big data into Big insights that power a very diffrentiated customer experience.
Worldwide, the retail grocery sector has become a battleground, with even non-grocery players (Amazon.com and peapod.com to name a few) in the fray, wanting a part of the food dollar. With Amazon launching AmazonFresh, there is potential for disrupting existing grocery models. Wal-Mart’s intention to grow its e-commerce business is very clear with its jet acquisition last year. Wal-Mart also earmarked an $11 billion budget for 2017 most of which would be used in Digital initiatives.
After years of building bigger stores to stock more products, the thinking today is more about realizing that future success might come from going smaller and closer to the customer. Supermarkets and hypermarkets are still important, but consumers are increasingly relying on smaller formats such as traditional stores and kiosks, which fulfill their needs for convenience and speed.
Meanwhile, Amazon continues to ramp up its grocery business and expand its AmazonFresh online grocery business.
Today, consumers have a range of shopping choices at their disposal, at the POS or with the click of a mouse or tap of a touch screen. And as the consumer shops using any or all of these choices, she leaves behind tonnes of digial data that can be leveraged for improving business. So how do you leverage this large treasure trove of data? And how will it impact the grocery store of the future?
Most retailers can process their huge repositories of transaction data. A customer purchasing pampers silently reveals to the retailer that she has a young child; her habits may also confirm she is vegetarian. Knowing how often a customer buys Heinz Ketchup or Maggi noodles over a one year period, a retailer can estimate when the customer may be running low and needs a “top up”. So transaction data can help in enriching both “customer knowledge” and “Personalised action”.
Today the data availability is also expanding rapidly. Data can be gathered using a wide variety of sensors and devices, including smartphones, Bluetooth beacons, counting systems, active RFID tags, and even ambient condition sensors for moisture, weather, and temperature. The most advanced analytics systems can import data streams from these types of sources with business information systems, merging store employee information, POS transactions, loyalty, and subscription data. Also a huge amount of data exists in unstructured form like the textual data of the website content, customer buying habits, social data, customer queries and complaints and so on. Advances in analytics allow us to now mine this rich source of data for developing insights that can be useful for business profitability.
By combining these data streams and many others, retailers can now have visibility into all customer/brand touchpoints, creating a truly better omnichannel experience by leveraging a more complete picture of the shopping journey.
And yet, how do retailers execute such a transformation. Often the devil lies in the detail. At its core, retail is about the product. Analytics can be the basis for challenging the category managers’ accepted wisdom and for pushing them to develop ambitious and differentiated category plans. The goal would be to create category plans powered by consumer insights.Data can help better understand customers’ shopping behavior at each stage of the “Customer journey.” Companies can monitor customer conversations about a product on social media, including why they purchased it, what products they like and dislike, and what would triger them to buy again. Companies can use these analytics to help explain which products in an assortment are substitutable and which are complementary.
Another area analytics can help in, is deciphering the success of sales promotions. Most promotional items don’t actually grow category sales or increase store profits. And if promotions fail to attract profitable new customers, they actually end up losing money for retailers. Analytics can help build a framework for sucesful promotions and then use it to create incremental profit.
To make this happen retailers will need to be able to create a solid single view of their customers using all the data they have about them. Secondly, they need the capability to convert the Big data into Big insights. Third and most critical, they must combine deep analytical talent with algorithms that help their internal merchandising teanms to buy and stock better. And finally, management needs to create an organisation wide change program so that the insights actually yield improved business decisions and translate those into effective storefront action.
The article has been pen down by Ajay Kelkar, COO and Co-Founder, Hansa Cequity