The late Mohandas Karamchand (“Mahatma”) Gandhi, once stated, “A customer is the most important visitor on our premises. He is not dependent on us. We are dependent on him. He is not an interruption in our work. He is the purpose of it. He is not an outsider in our business. He is part of it. We are not doing him a favor by serving him. He is doing us a favor by giving us an opportunity to do so.” One of the best ways to serve customers is knowing what they want so it is available when they want to purchase it. We know, however, what consumers want and need changes over time. Spotting trends, therefore, becomes an essential part of any retailer’s success. Marketing guru Kevin Stirtz (@kevinstirtz) puts it this way: “Know what your customers want most and what your company does best. Focus on where those two meet.” The late Steve Jobs went one step further. He stated, “Get closer than ever to your customers. So close, in fact, that you tell them what they need well before they realize it themselves.” The question is: How to you get close to your customers? The answer is: Big Data.

Getting close to your customers

Data, by itself, is no more useful than oil pooled underground. To be useful, data needs to be analyzed. More and more retailers are turning to cognitive technologies to help them know their customers better. Matt Field (@mattgjfield), President and Co-Founder of MakerSights, observes, “Artificial intelligence (AI) and machine learning (ML) are no longer just buzzwords of tech giants and consulting firms. Many forward-thinking companies have also implemented AI and ML strategies to solve both new and existing business problems brought on by the deluge of data. The Retail industry is now getting in on the action. A recent global study found that two in five retailers and brands are already using intelligent automation such as AI and ML and adoption is expected to double by 2021. The study also found that intelligent automation is making the biggest impact in demand forecasting, supply chain planning and customer engagement.”[1] The conundrum is that the more you know about your customers the creepier such knowledge can appear when used in questionable targeted marketing campaigns.

You might recall a few years back when Target received an enormous amount of negative publicity for sending baby product promotions to a high school girl. The girl’s father was enraged, but later found out his daughter was, in fact, pregnant. Target’s efforts to be helpful appeared creepy and intrusive. Gordon Gottsegen (@GGottsegen) notes, “Target’s data was on the mark. Still, its collection methods were creeping into creepy territory.”[2] Gottsegen adds, “From a technological standpoint, things have evolved significantly. Customer data still plays a huge role, … but in addition to predictive analytics, Target now relies on machine learning to analyze shopping habits in order to optimize its supply chain and personalize offers to customers. … Numerous other companies use it to optimize and automate tried-and-true retail practices such as SKU assortment, product recommendations, sentiment analysis, fraud detection, price forecasting, personalized offers and more.” The point is, data is useful in helping retailers know their customers better so they can serve them better. The staff at CIO Review note, “Customer expectations are very critical in retail. … Retailers need effective business intelligence to keep pace with changing customer expectations and buying trends.”[3]

According to the CIO Review article, leveraging big data in service of customers can help retailers immensely. The article notes, “According to an HBR-published study, companies that create the perfect omnichannel experience have increased their shareholder worth 8.5 times using data analytics. This report by Oracle tells retailers that their operating margins can increase by 60 percent using big data. … This indeed is the next major tech bandwagon, after all. Big data assessments are also the best way to gain insight into the view of today’s consumers.” Gottsegen adds, “While machine learning has lots of retail applications, many retailers think personalization — whereby shoppers are given a customized experience on a micro level — tops the list. That’s especially crucial as they grow physically or expand their online offerings.”

Beyond knowing your customers

Although the above discussion makes it sound like customer inputs are a one-way street to change, in reality, it’s a two-way street. Retailer innovations and changes also have an impact on consumer behavior. JoAnn Martin discusses four retailer trends affecting the way consumers shop.[4] They are:

1. Sustainability efforts. Martin notes a recent JDA survey found, “Over half of those surveyed stated that they would be very likely to purchase products that are considered environmentally friendly or sustainable compared to other products. It’s clear that sustainable business practices … are a must for organizations today.” She adds, “Gen Z and Millennials prioritize sustainability most.” The survey found, “Shopping at retailers with environmentally friendly or sustainable products is more of a priority for younger demographics with 27% of respondents between the ages of saying they’d be extremely likely to shop with a sustainable retailer, compared to 17% of respondents ages 30-44 and 15% of respondents ages 45 and over-60. This should stay top of mind for retailers considering the generations born after 1981 are more than double the size of the population of Baby Boomers.”

2. Clothing rental services. Nothing changes faster than fashion. So retailers, like Urban Outfitters, American Eagle and West Elm, have partnered with Rent the Runway to make the latest fashions available to customers and also encourage a more sustainable fashion industry. Martin writes, “The jury’s out on the everyday clothing rental service, with special occasion still the number one category for rentals: More than a quarter of respondents (27%) would consider using clothing rental services for everyday wear, yet only 13% are currently using services for this category. … Similar to sustainable habits, there is more popularity around rental services from younger generations with 35% of respondents ages 18-29 having already used it, compared to 27% ages 30-44, 24% ages 45-60 and 12% of respondents ages 60 and over.”

3. Open air versus indoor shopping centers. It’s been said that Millennials killed shopping malls but Generation Z might save them. Martin writes, “Open-air concept malls are growing popularity.” The JDA survey found, “Respondents were more likely to visit open-air shopping centers versus indoor shopping: 22% shopped at outdoor shopping centers at least once a month, while 20% shop at traditional indoor malls at least once a month. … The top two factors influencing customers to shop somewhere more frequently were having unique dining options (46%) and grocery shopping, such as Whole Foods or Trader Joes (42%). Following closely behind in third place was the convenience of services from shopping at a physical store, including buy online pick up in-stores (BOPIS) or curbside pick-up with 41% of respondents identifying this as a factor in influencing their shopping decisions. Live music (19%) and fitness facilities (6%) were also contributing factors.”

4. Online merchants opening physical stores. Although much has been written about the Retail Apocalypse and the shuttering of thousands of storefronts, many online retailers are now realizing having a physical presence is a benefit. According to Martin, one reason for this trend is instant gratification. She writes, “Instant gratification is (still) king.” The JDA survey found, “When asked about the top two reasons they are more likely to shop with retailers that have physical stores, respondents said it was so they could see, touch, feel and try out items (89%) and take them home immediately (58%).”

Retailers and consumers have a symbiotic relationship. Martin concludes, “When retailers consider consumer factors in their operational decision making, they help align themselves with more customer-centric strategies that support modern trends within the retail landscape. These collective actions have the opportunity to influence revenue, increase retention and provide less reactive, but rather proactive strategies for retailers to benefit from. As a result, this also helps retailers build brands that can survive generations versus just exist within a few trendy moments.”

Footnotes
[1] Matt Field, “The Future of AI in Retail: Fueling Change for the Industry,” Inside Big Data, 8 July 2019.
[2] Gordon Gottsegen, “Machine Learning is Changing the Way Retailers Do Business,” Built In, 17 April 2019.
[3] Staff, “Big Data in Retail: Overcoming Challenges and Grabbing Opportunities,” CIO Review, 18 February 2019.
[4] JoAnn Martin, “4 Consumer Trends You Need to Know Now,” JDA, 9 July 2019.