Picture yourself sitting at the food court in the centre of one of the millions of malls across the country. The smell of mall food staples such as pretzels and teriyaki chicken fills the air. Passing by you in every which way are hundreds of shoppers, carrying bags of goods with smiles on their faces.

What do you think makes many of these individuals go from store-to-store so cheerfully? Often, it’s the retail workers. However, regardless of their amicable natures and friendly suggestions that add to the retail experience, new breakthroughs in the world of AI technology could replace many retail associates – but could this actually lead to a positive outcome? To understand why retail giants are making the switch to AI, we must recognize exactly how this technology is being used, why it is more efficient, and what this means for the retail industry as we creep even closer to the new year.

According to market firm Tractica, global revenue from AI will see a huge increase from $643.7 million in 2016 to $36.8 billion by the year 2025. This massive jump is not astonishing considering that AI technology currently provides multiple industries with alternatives to job creation. In fact, within the same timeframe, Forrester expects that cognitive technology – including AI and automation – will replace 7 percent of U.S. jobs. This means that retailers could significantly reduce the costs of labour and make their business processes far more efficient.

What Does AI in Retail Look Like?

Today’s retail industry is more dynamic than ever & is built on a new covenant of data-driven retail experiences. New-age buyers are increasingly seeking shopping that has been customized to suit their preferences and delivered directly to their homes. However, delivering a personalized shopping experience at a scale that is relevant and valuable is no easy feat for retailers. Thus in order to stay relevant and deliver seamless customer experiences, retailers need to incorporate innovative technology. AI and ML, which I believe are no longer futuristic technologies, are, in fact, slowly becoming an integral part of processing data, assessing needs, and deploying the right measures through both predictive and prescriptive models, again across the value chain of the organization. Let us take a look at some examples of how AI in retail is reshaping the entire industry.

Benefits of AI in Retail Industry:

AI in Fashion Retail– Brick and mortar stores has lacked the ability to retrieve essential customer information. A retail outlet equipped with AI technology is an intelligent way to gather insight into shoppers’ habits and buying preferences. Retailers can leverage video for store analytics, which turns regular stores into intelligent stores & enable things like heat maps that show where consumers are spending the most time in the store.

AI for E-commerce– AI is playing a game-changer role in online shopping and e-commerce business. While browsing or searching for online merchandise, AI algorithms recommend other similar items, as per your colour preference, budget, and other attributes along with product purchase recommendations based on the frequency of product purchase across all customers. This way, it recommends only fast-moving products to customers & allows the retailer to keep a tab on fast-moving products and manage inventory accordingly. One study from a visual commerce company (via Business Wire) found that 70% of customers surveyed are likely to buy a product based on recommendations. Amazon uses recommendations as a targeted marketing tool in both email campaigns and on most of the pages of its website. Amazon will suggest several products from various categories depending on what you are browsing and pull those products in front of you which you are likely to buy. For example, the ‘frequently bought together’ option that is usually displayed at the bottom of the product page lures you into buying the combo.

Customer Segmentation– The focal point of customer segmentation is to group customers based on their preferences. Leveraging ML for customer segmentation provides businesses with a better understanding of complex lifestyle patterns and preferences, leading to better customer insights. This way, retailers gain visibility to highly loyal customers, which further help them in strategizing targeted marketing & building an ideal customer profile for these customers. Under Armour, a well-known fitness brand is one such example for the ultimate use of ML to garner success. They use health data from third-party applications, smartwatches to extract information about the food habits, sleeping patterns and exercise routine of different customer segments. They leveraged this data to design a tailor-made fitness program for each customer segment and started providing them with coaching recommendations.

Market Basket Analysis– AI/ML algorithms provide recommendations based on product affinity/association. Foreknowledge of consumer behaviour can increase sales and give the retailer a significant edge against competitors.

• Customers and retailers get to see what products go along with other products.

• Retailers get to plan their inventory management better by stocking products that sell better & get to strategize their product portfolio mix better.

Conversational Support – A recent report by Juniper Research found that Chatbots would “redefine” the customer service industry, and forecast that the technology would save over US $8 billion in operational costs by 2022. AI-powered devices such as chatbots use natural language processers to help shoppers effortlessly navigate questions, FAQs or troubleshooting and redirect to a human expert when necessary — improving the customer experience by offering on-demand, always-available support while streamlining staffing. In turn, these bots collect valuable customer data that can be used to make future business decisions.

Price Optimization– AI/ML algorithms can help you not only collect information regarding pricing trends, your competitors’ prices, and demand for various items, but it can combine this information with customer behaviour to determine the best price for each of your products. This strategy helps retailers offer competitive prices to their customers resulting in increased e-commerce revenue. E-commerce giants like Amazon have a dynamic pricing strategy in place, and they change the prices of their products every ten minutes.

Payments- AI/ML algorithms can help in predicting the payment channels that customers from different customer segments are willing to pay. This way, retailers can strike better deals with payment companies by having them provide discounts for customers.

 Wrapping Up:

To conclude, the retail landscape is ever-changing but the value of speed, service, convenience, and newness still remains impactful. Hence, retail marketers should focus on better serving customers in a digitally-connected world. A brand should understand the entire customer journey and eat, sleep, and drink Customer experience to thrive in the ever-changing retail ecosystem.

 

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