The Thanksgiving Shopping Storm and What It Means For U.S. Retail Stores This Season
While U.S. retailers are rushing to join the digital league, the Thanksgiving shopping season will serve a verdict on the future of offline stores. A large number of stores stand a narrow chance to understand the gaps in their retail strategies before they perish.
Five days ahead of the Black Friday, J. Crew had announced its plans to shut down around 6% of its stores by the end of January 2018. This was an extension of its original plan to shut down around 19 stores, a decision inspired by the accelerating losses. While the sales dipped by 9% over Q3 2016, the Q3 2017 saw the sales volume go down to 12%.
Read the complete announcement from J. Crew here: https://americaclosed.com/retailer-j-crew-shut-39-stores-q3-sales/
The chief operating officer, Mike Nicholson explained these shutdowns as the company’s plan to move over from being the “traditional retailer” to a “digital-first seller”. As the offline buying trend takes a nosedive in the U.S., retailers continue tolose sales volumeand revenue to digital platforms. They are now left with only two choices—either bring home innovativeretail strategies to pose an equivalent competition to theironline contemporaries or expand into the digital space, as in J. Crew’s case.
Stores face the challenge of ‘Perform or Perish’
According to the latest survey by the National Retail Federation, online purchases were to dominate the net sales completed at the traditional brick-and-mortar stores with a straight edge of 59% during the recent Black Friday. This is plainly because consumers found it easier to shop-on-the-go in their busy schedules. The unremitting drop in sales volume at offline stores was now more of a worry for the retail industry than ever.
Get the complete report from National Retail Federation: https://nrf.com/media/press-releases/more-164-million-consumers-plan-shop-over-thanksgiving-weekend-and-cyber-monday
As of now, the descending demand figures have left them with little choice other than expanding their operations across digital platforms. If retail businesses in U.S. failed to close customers this festive season, it could be the last season of business for most of them altogether. Therefore, it is a situation of perform or perish for a large group of stores. At major risk are the ones who have not focused upon customer-centric merchandising, discounts, promotions, and services.
A ray of hope that remained
To date, there exists asignificant population with a personal bias for the “touch-and-feel” assurance before a purchase. Out of the 115 millions who were expected to be shopping this Black Friday, offline stores stood a fair chance to host a good share of these buyers.
When buyers walked in this season to enjoy their Black Friday sale season, U.S. retailers were expected to be armed with three highly optimized tactics, which would give them the required edge over both online and offline contemporaries—select merchandise, adequate inventory, and attractive pricing. They were required to ensure thatthe stocks are enough, the staff manages to serve up tasteful service, and that they have managed to price items across categories shrewdly. This was entirelydependent on how accurately they had been able to analyse the customer behaviour and expectations.
What retailers needed to survive?
Retailers were forced to step up and execute different sets of calculated store strategies throughout the pre-thanksgiving weekend. By the end of it, they had tested their analysis ofcustomer expectations& behaviour, price trends, and product demand. They had realized the loopholes in judging which SKUs that they should have stocked upon, segments that they could have marketed on priority, prices that would have given them a competitive edge, and service quality that would augment customer recall.
The Black Friday was a good time to notethe customer expectations during one-on-one interaction, in terms of product categories and price perceptions. The digital platforms never offered this advantage of personal interaction.Consequently, it shrouds the possible reasons for not completing a purchase after the products were added to the cart. This is why, in-store customer interaction comes across as far more effective in understanding customer behaviour, and subsequent identification of effective business strategies.
Using big data and analytics to their benefit
To be at par with the kind of data that online shopping platforms generate, retailers need to get cleverer with their customer engagement programmes. Let us consider the loyalty program cards offered by several retail chains. These cards can be used for extended purposes rather than just sales invitations. This would include extracting detailed information from their customers that would answer categorical questions. Retailers would be able to quantify the affinity trends that stay consistent, the customer groups that opt for regular upgrades, theexact specs that customer find most attractive in each category, and the frequency of purchase that each category calls for.
A granular set of information can be derived at each level of customer engagement. When clubbed with big data and customized retail analytics, it would help retailers make the rightestimations.
Merchandising: Merchandising managers can group the data and isolate the set of items that each customer group wants to buy this season. Hence, they would be able to put up the display that is relevant to the modern customers and their needs.
Inventory: Inventory planners can predict the sales for each item based on the most recent demand projections as well as the historical data pertaining to the same time and category. This would help them build a reliable inventoryto back up expected demand.
Pricing: Pricing managers can relook the efficacy of their pricing strategies with help from the pricing sensitivity models, as against the market and competition prices. This would help them survive and recover the post-thanksgiving margin losses.
The verdict on this year’s strategies is now out for the U.S. retailers, which you can read here. It is better that retailers bring in more of the required customer data, and pitch it against what they already know, so that the insights might probably bring them a merrier Christmas ahead.
Find out what happens when digital intelligence meets digital business
Top Five Data Science Tren...
The world of big data, machine learning and predictive analytics is actually one of the most vivid examples of a VUCA...
Did the Indian Consumers B...
GST (goods and services tax – the new value added tax regime in India introduced in July 2018) [http://www.cbic...
The role of predictive ana...
All eyes are on the Indian FMCG and retail sectors that “form the direct path to the India Growth Story - CII N...
Analytics & Technology Boo...
One of our clients was an FMCG company that sells aroma oils, potpourri, diffusers, candles and other such products i...