Algorithmic Retail: A Formula for Marketers to Connect with Customers
The last year has witnessed transformative changes in the way retail works. The industry experienced a sudden exodus to digital—an increase in e-commerce, mobile apps, BOPIS (buy online, pick up in-store), social commerce. Loyalty went out of the window, with customers switching to brands and products based on availability and need. Customer preferences are evolving—brand loyalty is driven by shopping experience mainly online, high-value customers suddenly became value-conscious and offer-driven shoppers, healthy products are outdoing the traditionally popular brands and items, customers are reading beyond regular product description to understand how responsible the business is, and many such factors are influencing customer purchase decisions and behaviors.
Add to this intense competition not just from within the industry but also from outside forcing them to rethink their business models—from physical stores to e-commerce, DTC, BOPIS.
Lines of cars parked in front of stores, filled with customers waiting in their vehicles for items they have purchased online. Consumers taking their business from one store to another in search of a better, more personalized shopping experience, faster delivery, or the satisfaction of finding the items they want without driving from location to location. Retailers scratching their heads ever harder about how to stock their shelves, grappling with product shortages, and fighting competition from their market as well as from other market segments.
Insider Intelligence estimates that U.S. shoppers spent $72.5 billion via click-and-collect in 2020, accounting for 9.1 percent of all e-commerce sales. This year, those figures will increase to $83.5 billion and 9.9 percent.
Traditional retail sales have declined but e-commerce has seen a 129 percent year-over-year growth in the U.S.
Customers spend 48 percent more when their shopping experience is personalized. Plus, 57 percent of online shoppers are comfortable with sharing their personal information with a brand if it benefits their shopping experience.
Customers are becoming increasingly demanding. They are no more satisfied with fast service; they expect instant. Retailers sending personalized offers via email the next day of purchase was considered fast. That’s not good enough—they want brands to provide contextually relevant experiences and to connect with them in the moment.
How then do marketers in the retail industry cope with this pace of change? It is no secret that the retail industry must extend its frontiers from analytics to artificial intelligence and algorithms. It is the cornerstone for marketers to create a differentiated brand experience and win the long-term race for customer loyalty. And it is the cornerstone to grabbing both customer mindshare and wallet share.
Algorithmic Intelligence Can Boost Personalization
Algorithms helps retailers better understand customers, individualize customer experiences, and effectively engage customers in an omnichannel manner. As mentioned earlier, customer tastes, preferences, and behaviors are evolving fast. AI can help marketers understand these changes as they happen and connect with customers in a relevant manner. For example, owing to the pandemic, the time-of-day preference to order a meal changed from lunch to dinner for a pizza chain. There was an increase in orders for evening snacks, and weekend lunch became more popular. Pizza chains that caught this change early on were able to make a quick change to personalize based on the menu, channel, and time-of-day preferences. Some of them enjoyed more than 30 percent increases in conversion rates and about 10 percent increases in average order value and purchase frequency with personalized interaction powered by algorithmic intelligence.
Another example is of a grocer who was able to identify certain high-value customers slipping to low-value owing to the impact of the pandemic, with basket value going down by more than 25 percent. Algorithms helped identify these granular segments, and by using an AI-powered recommendation engine, the grocery was able to push the right offers to the customers in this segment based on their purchase history (market basket and affinity analysis), reversing the trend and improving the lifetime value of the customers.
Real-Time Customer Engagement Driven by AI
With customer date platforms (CDPs) that have built-in algorithmic intelligence, retailers can engage with customers in a relevant manner in real time. CDPs enable streaming data ingestion and segment creation, which is then activated in real time for personalized interaction with the customer instantly.
Personalizing products in the catalog based on what the customer is searching for on the e-commerce site to responding to a customer’s Instagram stories on the shoes she bought from a certain brand, AI enables real-time personalization for retailers.
Unifying customer’s behavioral and transactional data across touchpoints and tailoring journeys for every customer based on deep insights are must-have capabilities. Real-time decisioning intelligence helps predict customer needs and modify the journey to meet taste or behavioral changes. Algorithms and AI empower retailers with tools to drive real-time engagement through the customer’s shopping journey in the channel of their choosing—mobile, web, email, or text—delivering up-to-the-minute recommendations based on customer behavior, location, etc.
Consistent Engagement Across Channels
Today, customers are spoiled with choices in the plethora of channels they have for shopping and learning about a brand. To be customer-centric is to connect with them where and when they would like to engage with you. AI-powered platforms for omnichannel orchestration do just that—help retailers know as soon as a customer arrives on one of their channels and engage with them right there.
If regular grocery store customers decide to download the grocer’s app and make a purchase, messages, offers, and product lists are customized based on their past purchases at the store, delighting customers and enticing them to come back.
If a customer forgets to complete a transaction, an SMS is sent to the customer reminding her to do so. A near sure-shot way to increase conversion rates.
By helping retailers understand their customers’ behavior, tastes, and preferences, algorithms deliver improved customer satisfaction, loyalty, and lifetime value—the right formula for sustainable business growth. AI algorithms enable accurate, targeted marketing campaigns, thereby opening doors for new revenue-generating opportunities and minimizing spending on ineffective promotional vehicles while helping retailers scale as they grow.
The future looks even brighter with the infinite possibilities and seismic shifts that AI brings for retailers—virtual stores, live streaming, magic mirrors, and more. Challenges and roadblocks such as data fragmentation, changing customer expectations, heightened competition, and newer channels mushrooming will continue to appear. Algorithms will help retailers adapt and pivot, with customer at the center of it all.
Smitha BV is associate director, product marketing, at Algonomy, which enables retailers with its Algorithmic Customer Engagement to become digital-first businesses. She is responsible for crafting the product value proposition, messaging, and go-to-market strategies at Algonomy. She is a seasoned marketer with extensive experience in the technology industry—building brands, generating revenue, and winning over customers. Prior to Algonomy, she worked with TCS, Standard Chartered, and EdGE. She holds a postgraduate degree in management from XIME, Bangalore.