The 5 new rules of retail

Why did the rules of retail need to be rewritten? Because 2020 happened and shopping patterns changed overnight. There were product shortages, store closures and long lines to get in the few stores that were open. Consumers moved to online shopping in droves and expected a seamless experience in-store and online: Curbside pickup; same-day delivery; contactless delivery; buy online, pick up in store. The list goes on.  

But there is good news for retailers. Analytics can help overcome some of the effects of this disruption, allowing retailers to move from long-term seasonal forecasting to more agile planning. “Resilience is key in this economy and analytics can help retailers develop a more flexible supply chain, all the way from the vendor to the retailer to the end-consumer’s doorstep,” says Richard Widdowson, Vice President Global Retail and CPG Solutions at SAS.

It’s a new retail game, and there are new rules.

New rule #1: Cloud analytics is for all retailers – anywhere

Big investments and long software installations are a thing of the past. That’s  because subscription and consumption-based or service-led cloud offerings like Microsoft Azure allow brands to accelerate digital transformation with commercial grade analytics. They also give organizations the ability to start small and scale up, or down, as needed.

With consumers making fast buying decisions, retailers must make the move into real-time decisioning, and unless they’ve moved into the cloud, a lot of the data they need for real-time decision making is siloed.

“But once you have all that valuable data connected in the cloud,” says Tom Backus, Business Strategy Leader Worldwide Retail and Consumer Goods for Microsoft, “you can design and optimize customer journeys, personalize interactions for each and every customer, and you can do the necessary test and learn and rapidly innovate the customer experience over time for greater trust and greater loyalty. 

New rule #2: Trust analytics to create localized assortments and pricing strategies

When it comes to merchandising, it’s risky to make decisions based on your gut and Excel spreadsheets. With analytics, you can make data-based decisions that help you achieve inventory precision in today’s cross-channel, digital world, as well as maximize revenue, profitability and efficiencies.

But how? “Retailers need integrated statistical forecasting to support the entire enterprise and achieve overall supply chain planning and visibility,” says Brittany Bullard, SAS Principal Systems Engineer for the Retail and Consumer Packaged Goods (CPG) industries. “Embedded analytics can help drive assortment planning throughout the process, providing recommendations on assortments, helping retailers understand what attributes are performing well, what combinations of attributes are performing well, and using analytics to drive the end-to-end process,” says Bullard.

“Clustering is another great example of an analytical quick win for retailers,” says Bullard. “Traditionally, stores have been clustered based upon sales volume, region, store size and so forth. SAS has worked with many retailers to intelligently cluster their stores using data mining and machine learning techniques. For example, one retailer had stores in the same region with the same volume that historically received the same products. But when we looked at what was selling and the consumer demographics shopping that local store, they were completely different. Implementing these strategies help retailers achieve true customer-centric assortments.”

New rule #3: Get closer to predicting the unpredictable with machine learning 

When the pandemic hit, long-term retail forecasts went out the window. “Companies had to pivot from their traditional, long-term planning to a more agile, short term planning that would help them get their arms around what to expect in the next one, two or three weeks ahead,” says Widdowson.

To do that, retailers had to shift away from traditional data sources, such as point-of-sale data and sales orders, to a more immediate, hyper-local approach fueled with external data -- like store closures, travel restrictions, social media and web traffic -- that creates a more accurate view of what’s happening.

SAS worked with a regional online grocer to help them quickly make this shift. “They experienced an increase in online grocery purchases of 200%, pretty much overnight,” says Widdowson. “As you can imagine, this immediately created substantial supply chain challenges.”

“We built time-learning and machine learning models, and were able to integrate additional information using predictive analytics – data that predicted future demand, improved our models and allowed the retailer to create more accurate weekly and daily demand forecasts for better decisions across the entire business,” says Widdowson.  

New rule #4: Every customer interaction is a brand experience

Your customers still expect a 5-star customer experience whether they shop in your physical store, online or a combination of both.

It’s time to elevate your shopping experience with analytics-first marketing, using data from all your channels.  Whether they choose bricks, clicks or a combination of both – analytics can help craft a harmonious cross-channel experience for your customers -- powered by data and analytics.

For example, a major US department store, one of the largest in the nation, wanted to maintain its growth and presence, and needed to have a better understanding of its customers at an individual level for better engagement. The retailer was plagued with siloed customer data and wasn’t using analytics. SAS worked with the company to help them automate marketing campaigns, informed by analytics for better targeting, conversion rates and seamless cross channel communication. 

New rule #5: Use analytics to hold your ground in the fight against fraud.

Now that products are bought everywhere, fulfilled everywhere and returned anywhere, retailers must detect suspicious behavior in real time to protect the bottom line. You can and should defend your organization with predictive analytics, network analysis and real-time streaming. 

“Retailers must refocus priorities in order to protect the consumer experience, to prevent losses in revenue, operations and the bottom line, which up until now has been just accepted as the cost of doing business,” Donna McGuckin, SAS Retail Analytics Solution Advisor.

“In 2019, fraud and abuse of returns in US alone reached more $24 billion dollars,” notes McGuckin. “The holiday 2020 returns are projected at a 73% increase over the average of the last five years. With that is going to come the potential for fraudulent activity, along with waste that’s going to really drain profitability.”

“There are over 300 different pathways a return can take,” says Ivor O’Neill, Managing Director, Internal Audit and Enterprise Risk, KPMG. “And every stage of the process costs money. Where can the system be manipulated? Where is there fraud, waste and abuse in these systems? With 300 pathways, it’s almost impossible to manually examine it – you have to use analytics to find patterns of behavior, really get down to the root cause of some of these costs, and improve business processes,” says O’Neill. 

Where do retailers go from here?

As retailers continue to encounter business disruptions, using the power of the cloud to accelerate innovation -- in working with data, customers and accurately forecasting supply and demand -- will be key to moving forward.

If you need an innovation example, check out the new solution from SAS and C.H. Robinson that will help retailers and CPG companies select the best transportation routes in hours instead of weeks. Companies will be able to make real-time fulfillment decisions regarding shifting consumer demand when plans on the ground unavoidably change – even as inventory is still moving.

It’s undoubtedly a whole new world – and the future winners will be the retailers who change their mindset, innovate quickly and use analytics to their full advantage in the new economy.