“Retail apocalypse” is the word that was in news entire last year. Gigantic retailers like Toys “R” us, RadioShack, and Gander Mountain filed bankruptcy. In the year 2017 approximately 7,000 stores closed down, according to FGRT, which is more than 200% in 2016. Some of the sick stores are the retail chains which are dying off fast and have closure plans that date out to 2020. The retail apocalypse was inevitable. Companies did not identify and make changes which were a dire requirement – in response to growing trends of data management and customer experience.
So now with only 13% of total retail online, of which 44% goes to Amazon and closure of retail outlets; where do people shop now, and why?
Customers were apt enough to move on to Best Buy, Target & Walmart. Without Toys R Us in the race, Walmart and Target’s toy businesses in Q4 is likely to soar. Retailers who understood the value of data generated remained unaffected in the retail apocalypse. These retailers used customer data to customize the customer experience, for better target marketing and even notify their shoppers about the availability or new arrivals of their products/goods.
It may sound contradictory, but the retail industry is on the rise. Due to agile retailers, which were ready to change; retail sales globally by year end 2020 is expected to reach $28 trillion.
Digital evolution in Retail
Retail industry is evolving and so are other industries. Today organizations are trying to transform from a company-centered strategy where brand defines the product; and running a race to become customer-centered where personalization, innovation and convenience are thumb rules. Digital business models, for both the industry and consumers, leading the way in this transformation include:
- Services economy: Few years back, what customers expected the retailer to provide is now actually predicted and provided by the brands. On ordering a product online, initially consumers expected the online retailer to deliver it at their convenient time – however; today retailers ask the customer to specify a time when they would want the goods to be delivered.
- Replenishment and on-demand economies: It is all about goods being delivered to customers even before they want or need them. Instacart is a classic example. More and more retail consumers are inclined towards using sensor based digital services which pre-emptively identify their needs without human intervention.
- Subscription economy: It is not a new thing or concept for next gen retail customers. Their required products are automatically delivered regularly. Dollar Shave Club has proved that it can be done seamlessly.
- Personalization economy: Stitch Fix is a prominent example of personalization economy where products are customized to an individual’s likes and dislikes. And not only this, goods are delivered one time or by subscription too. All these features have opened up doors for consumers to use a subscription for clothing. Consumer’s previous purchase data is used by experts to predict what they will like, and accordingly they select and deliver items.
- Sharing economy: Rent the Runway says, why buy when you can rent? There is a completely new economy that is developing which enables consumers to use a product for an occasion and return it. 5 out of 10 consumers across USA have rental subscriptions for clothing, renting an item for a stand-alone occasion and returning it after use – instead of purchasing the costly products.
What do all these business models have in common? It is the data. Retailers use data about customer likes and needs. They also leverage what customers want on a regular basis, and how often they want it. They use the data to predict what all goods/products are about to get over or expire. They have adapted to business driven data models to keep pace with evolving business processes and customer experience.
Conventional retail tactics
Brand overhauls and acquisitions are been practiced for decades, however, the gains from these can’t result in people buying more products and increased sales, hence profits. So now the challenge for traditional retailers is how to take that leap, before competition snatches away their sales and customer’s loyalty. There are numerous reports and surveys available which portray the fact that brands, sitting on heaps of data about their customers, their purchasing habits, product sales and current processes – are incapable of leveraging it to improve, test and come up with data driven business models.
So then what should the retailers do?
Automation
Why shopping in retail stores is still the same what it used to be 25 years ago? Why the customers are still required to search for on floor employees for help, face instances of out-of-stock items, and walk the products to their cars? Why the checkout process is not completely automated? Though, data management experts are all set with solutions to be implemented to address these challenges; retailers are running towards AR experiences and stores of the future concepts. Instead, they should be solving the challenges of brick and mortar environment. Amazon is working in a steam rolling mode to resolve such identified problems; from Amazon Go to Surveillance camera powered checkout. Retailers failing to catch up with it – are more likely to witness apocalyptic effects of the retail industry.
But, retail industry is reviving and flourishing
While retailers may consider the expected spike of $28 trillion by year end 2020, it’s more likely that it is a brief respite before the apocalypse hits back. Below mentioned facts compel you to think so:
- 15% of organizations effectively deliver relevant and reliable customer experience
- 3% companies were able to act on all of the customer data that they collected
- 21% said they can act on so very little of that data
- 94% of retail organizations, though are using data and analytics effectively, only 53% of them found it to be really important for their digital transformation.
Conclusion
Average company tenure on the S&P 500 Index in the year 1977, was 37 years. It is expected to melt down to 12 by year 2027. So at this churn rate, nearly half of the companies now on the S&P Index will be replaced in next 10 years due to complex combination of technology shifts and economic shocks, but mostly it would be the companies which miss out on adapting to change.
Slow adoption by some retailers is a sort of encouragement for several new and/or more agile retailers to exploit advanced analytics and acquire customers, retain them and reap profitable results. Will these slow retailers use this short time opportunity to turn the wheel of fortune, or will they continue struggling with data and practice strategies that surely don’t work.