The retail landscape has completely shifted since its installment in the early 20th century. Today, the industry offers customers a limitless variety of choices while it continues to change.
When glancing at the industry’s most recent digital transformation, it can be easy to overlook the challenges digital retail pioneers had to overcome. Digital pioneers, like Amazon, had to create an online retail experience and make it simple for customers. How did they do this?
Artificial intelligence – the umbrella term for analytical methods that learn from data without relying on humans to set the rules – made all of this possible: AI can anticipate what a user is searching for and make targeted recommendations for products that might interest them. AI can drive efficiencies across all aspects of order fulfilment, from minimizing the amount of packaging used in an order to smart routing.
This new wave of disruption has left many physical retailers struggling to compete on price, assortment and convenience. However, just as AI powered advances in e-commerce, it can also offer the catalyst for change in brick and mortar stores.
To identify where AI can be a force of change, we must start by examining brands that buck the overall decline. When looked at from this perspective, three models of retailing stand out:
Retailers in the value segment possess a relentless focus on low prices, which they achieve by cutting back their assortment or removing any frills from the in-store experience. In the grocery sector, Aldi is a prime example of this form of retailing. In the U.K., it has seen its market share rise from 1% in 2001 to 8% in 2019 .
In the experiential model, category leaders often use their stores as a form of brand marketing on top of its traditional function as a place to purchase their products. Apple is the textbook example, with a global footprint of over 500 stores that each support the brand with their heavy emphasis on design and a knowledgeable workforce on hand to guide you through the sales process.
In the convenience space, retailers double down on solutions for distress purchases that online retailers can’t compete with, and strive to remove any friction from the shopping experience. In mature markets this sector, and its leaders such as 7-Eleven in the U.S., are experiencing significant growth .
So how will AI affect a transformation across the three key areas of value, experiential and convenience retailing?
For retailers focused on value, AI has the potential to realize significant efficiencies and enable leaner operating models. Machine learning (the AI subfield concerned with mining data to predict an outcome or recommend an action) and process automation will be the two main levers of change in value retail, delivering a string of cumulative, incremental benefits that will deliver large-scale impact over time.
With experiential retailers, AI will help deliver more immersive and personalized shopping experiences. Used in conjunction with augmented reality, deep learning (a subfield of machine learning that emulates the human brain), will unlock new applications to enrich the in-store experience by processing and interpreting images and text. Developments have already started in this space with companies such as MemoMi offering smart mirrors that let customers try on clothes virtually.
In the convenience retail space, AI is already being used for customers to complete their shopping trip and we are already seeing examples. In Amazon Go’s convenience stores, AI removes the need for a checkout entirely by interpreting data from in-store cameras and sensors to detect when a customer picks up an item from a shelf. AI also has considerable potential to help convenience stores make more flexible use of the limited space available to them.
At a more fundamental level, one of the most important decisions a convenience retailer can make is where to locate their stores. Until recently, predicting revenues for new locations had proved fraught with difficulty. Now, AI offers the potential to harness new sources of data to identify local drivers of store performance.
In a sign of AI’s increasing emergence in the convenience sector, the largest pure-play convenience retailer in Europe, Zabka, announced a strategic partnership on AI with tech companies SparkBeyond and Microsoft earlier this year. Zabka started using these new capabilities to re-envision its approach to location planning and store-level revenue optimization.
Whether retailers concentrate on value, experience or convenience, AI will help them meet customer needs more effectively than they do today, but it will also change the way in which retailers work with data. AI has the ability to turn this model on its head by empowering sales assistants and store managers to take the next best action – equipping them with highly specific recommendations on everything from which products to stock to the most effective promotions and price points to select.
From next best action to cutting-edge demand modelling and location optimization, the AI use cases that will underpin the future of retail all depend on an ability to cut through the complexity and make sense of diverse, ever-changing sales drivers. A new AI capability, automated root cause analysis, which is being pioneered by SparkBeyond, is beginning to deliver a step-change in retailers’ ability to understand sales drivers by surfacing relevant insights that can be understood and acted upon by the business, and which update dynamically as the situation changes on the ground.
Since the mid-20th century, store managers and sales assistants have become less and less influential in the running of a store, but AI could be about to reverse this trend and empower retailers to make more effective decisions and deliver more memorable experiences from the bottom-up.
 Kantar Worldpanel – Grocery Market Share in Great Britain
 National Association of Convenience Stores – 2018 State of the Industry report
*this blog post was first published at RetailMinded.com