Artificial Intelligence and the Future of Retail

Stephen DeAngelis

December 20, 2018

Retail transactions are some of the oldest human activities. To spur trade and create wealth, explorers have plied the world’s oceans and have traversed the globe’s landmasses. The next arena of exploration for the retail sector is artificial intelligence (AI). Arthur Zaczkiewicz (@arthurzaczkiew1) observes, “Retailing is being forced to change as consumer preferences shift and technologies such as artificial intelligence power a new breed of company that brings to market products, services and an overall shopping experience that shoppers demand and are delighted by.”[1] Joerg Koesters (@joergkoesters), Head of Retail Marketing and Communication at SAP adds, “Artificial intelligence is expected to become pervasive across customer journeys, supply networks, merchandizing, and marketing and commerce because it provides better insights to optimize retail execution.”[2]

Will AI transform retail?

Hype always accompanies the introduction of new technologies and artificial intelligence is no exception. Aspiration is a fine thing but it can lead to disappointment if not grounded in reality. For the most part, retail executives have gone beyond the hype and are now looking for real benefits from AI projects. Koesters reports a study by IDC found, “40% of digital transformation initiatives will be supported by cognitive computing and AI capabilities to provide critical, on-time insights for new operating and monetization models. [And] 30% of major retailers will adopt a retail omnichannel commerce platform that integrates a data analytics layer that centrally orchestrates omnichannel capabilities.” Zaczkiewicz believes retail will transform but will remain recognizable. He explains, “This transformation requires a cultural shift of traditional retailers (as well as designers and manufacturers) that is centered on optimizing data and leveraging consumer insights to offer products and services that shoppers want. And the engine that will drive this change is AI. But that doesn’t mean the creative merchant and design activities will be replaced by robots. Instead, AI will eliminate redundancies and use automation to free up time to allow merchants to focus on what they do best: create.”

Forrester analysts, Rob Koplowitz (@rkoplowitz) and Sucharita Kodali (@smulpuru), agree a combination of automation and AI provides the best foundation for retail transformation.[3] They explain, “An incremental approach to AI in retail should focus on [three things].” Those three things are:

  • Automating customer journeys. “Most customer journeys are hindered by manual processes and legacy systems, but new tools are arriving to help. Automating customer journeys is a great starting point for retailers. Seamless journeys drive better online shopping experiences with AI-based solutions like enhanced analytics or intelligent recommendation solutions.”
  • Building software more quickly. “Customer journey automation requires more software that many firms don’t have time or resources to build themselves. As retailers identify the gaps and pain points in their shoppers’ journeys, new tools like low-code development platforms are stepping up to speed software development. Seamless journeys are the building blocks for predictive AI features.”
  • Leveraging robotic process automation (RPA). “RPA drives client-side automation and integration, which enables businesses to automate manual tasks typically handled by humans. This offers straight-through automation, as well as end-to-end transparency.”

Two themes should be apparent by now. First, retail transformation is necessary because consumer preferences and paths to purchase are changing. Second, cognitive technologies can help retailers identify and respond to those changes. Retailers failing to adapt their operations to changing circumstances are likely to be victims of the so-called retail apocalypse.

The benefits of AI in retailing

A study conducted by CB Insights concluded retail transformation generally begins with supply chains. Reporting on the CB Insights study, Kate Patrick (@katepatrick_) writes, “Confronting supply chain problems is increasingly necessary for retailers to maintain relevancy, but the retailers who straighten out their supply chains and use new tech to better gauge and meet consumer expectations will dominate the industry. That’s where AI comes in. As demonstrated by the CB Insights report, AI can learn from consumer habits in an online store and better predict and target what the consumer wants, allowing the retailer to more effectively market and handle inventory. If meeting consumer expectations is a retailers’ biggest problem, then understanding consumer behavior through AI is the way to solve it.”[4]

Lydia Hanson notes, “The retail industry is going see the walls disappear between the seller and buyer with predictive analytics and AI. … The retail industry thrives on three factors — better customer experience, greater choice and buyer advantage. … This tells us that personalized customer experience would be the top-most priority of retailers, driving them to invest more time and resources in understanding predictive analytics and AI.”[5] She goes on to list a number of ways cognitive technologies with embedded analytics will benefit retailers. They include:

  • Better pricing. “Better pricing decisions [are a] strong benefit of predictive analytics. The guesswork determined by intangible factors such as likeability and brand image are replaced by data-driven insights. Predictive analytics draws insights for retailers, that helps them reduce and increase price during different seasons to create an optimal revenue effect.”
  • Personalization. “Personalized messaging has been one of the most tedious tasks for marketers. … Now, with automation as the means and predictive analytics providing data for validation, marketers are able to target product catalogs, offers and new releases for a specific target audience.”
  • More effective promotions. “The ‘Promotions Advisor’ is another role that predictive analytics takes up, since it reads in between data points to make sense of the lifestyle and habits of consumers. These behavioral traits reflect interesting purchase trends of the consumer, which otherwise would be almost impossible to know without a direct interaction with the customer. While some promotions are woven around seasons, a majority of them which achieve revenues are personalized promotions exclusively for the individual consumer.”
  • Recommendations. “Product recommendations is another interesting area that has been empowered by predictive analytics. With subtle behavioral trends from the past and recorded shopping experience, retailers can help consumers with better product recommendations and experience.”
  • Inventory management. “Inventory and supply chain efficiency is an obvious outcome of analytics. Retailers are able to predict demand for every product, consumer type and season of sale. This helps them from being overburdened by excess inventory and to avoid the hassle of complexities involved with supply chain management.”
  • Fraud detection. “Detection of fraud is a major advantage for e-tailers, provided by predictive analytics. Data can reveal phony buyers and suppliers that will help retailers to refrain from associating with them. Though not completely eliminated, predictive analytics can minimize fraud to a great extent.”
  • Improved in-store sales. “In-store sales is an often overlooked advantage of predictive analytics. A Google survey shows that 97% of consumers are using their phones while shopping for appliances to research for further information. Retailers can promote in-store sales by optimizing over the existing footfalls.”
  • Customer service. “Customer service is a popular area that has adopted predictive analytics. It helps the agent across the phone, chat or email by indicating the problem of the griever ahead of time. This reduces time spent on each support ticket and enhances the customer service experience for the shopper, associated with the brand.”

Concluding thoughts

Patrick concludes, “If retailers want to survive, adjusting their supply chains to actually understand and then meet consumer expectations is paramount — but in order to do that, greater investment and leveraging of AI is necessary.” An IDC report found early adopters of cognitive technologies are already seeing positive results. The report concludes, “Commerce and technology will converge, enabling retailers to achieve short-term ROI objectives while discovering untapped demand. But implementing analytics will require coordination across key management roles and business processes up and down each retail organization. Early adopters are realizing demonstrably significant value from their initiatives — double-digit improvements in margins, same-store and ecommerce revenue, inventory positions and sell-through, and core marketing metrics. A huge opportunity awaits.”[6] Said another way: The future awaits.

Footnotes
[1] Arthur Zaczkiewicz, “The Future of Retail Is AI-Powered and ‘Merchant-Imagined’,” WWD, 17 January 2018.
[2] Joerg Koesters, “Will AI and Machine Learning Spell the End of Retail as We Know It?SAP Analytics, 6 September 2017
[3] Rob Koplowitz and Sucharita Kodali, “Artificial Intelligence in Retail? Nope — Start With Automation, Analysts Say,” SupplyChainBrain, 31 August 2018.
[4] Kate Patrick, “Report: AI is the ‘future of retail’Supply Chain Dive, 2 March 2018.
[5] Lydia Hanson, “Different Ways Artificial Intelligence Will Revolutionize Retail,” WhichPLM, 30 April 2018.
[6] Koesters, op. cit.