Why the future of successful customer experience will include AI

What this means: As artificial intelligence (AI) receives the attention of the retail industry, it’s clear that its applications can impact almost every part of a retail organization. Using AI in merchandising decisions and trend forecasting could have a real impact on waste reduction and keeping pace with changing consumer preferences. At a time when the overall industry doesn’t have the speed or agility to anticipate and react to trends in a timely manner, AI could be an asset in getting products to market quickly and reacting to sales information in real time. Retailers can take advantage of AI to help them in their quest to create authentic, unique, personalized customer experiences (CX). For example, brands that create personalized experiences by integrating advanced digital technologies and proprietary data for customers have seen revenue increase by 6-10% — two to three times faster than those who don’t, according to a Boston Consulting Group study. “Buyers know they have choices,” Cynthia Sener, president, go-to-market of Chatmeter, told Retail Leader Pro. “By delivering targeted customer journeys from online to in-store retail brands increase consumer trust and satisfaction and the opportunity to keep buyers loyal for life.” Optimizing CX Exceptional customer loyalty and growth is driven by a combination of AI-powered deep listening with real-time CX agility and operational efficiency. Building community with customers is the most effective way for brands to discover new opportunities and determine areas of high-potential business growth, Sener said. Still, unstructured data is growing at the rate of 55-65% per year, and mining massive amounts of unstructured data from an increasing array of sources is a daunting prospect. Fortunately, machine learning, AI-powered solutions using natural language processing (NLP) tackle the task with ease by ingesting millions of online reviews and comments and analyzing relevant keywords, prevailing topics and the sentiment expressed. With accuracy scores of 80-85%, NLP technology solutions offer highly intuitive ways for multi-location businesses to: Turn unstructured data into actionable insights to track sentiment trends and identify areas of operational improvement. Compare how locations are performing across the enterprise. Monitor unfiltered customer feedback on new products or services. Identify a brand’s blind spots. The best business intelligence technology captures real-time voice of the customer (VoC) data from countless directories (e.g., Google, Bing and Yelp), social media platforms (e.g., Facebook, Instagram and TikTok), surveys (Qualtrics), industry-specific directories (TripAdvisor and OpenTable) to mitigate the complexity of data mining for tens to thousands of locations. A VoC platform with deep listening capabilities, Sener said, makes it much more likely that a retail brand will be able to uncover its blind spots by revealing answers to questions such as: Are shoppers at your convenience chain satisfied with the new hot food items? How did shoppers at your retail stores respond to the holiday gift offerings? How many five-star ratings did your auto-supply stores receive in 2022, and which locations got the most or the least and why? Which employees are doing the best job at delighting customers, and which might need some training? By tapping into customer sentiment from AI-powered consumer sentiment analysis retailers can listen to what customers are talking about and hone in on the items, colors, styles, etc., that are on trend. “This has tremendous value in terms of forecasting,” Sener said. Sentiment analysis tools let retailers set up custom topics, so they can track trending topics relevant to their brands and locations. For example, a clothing retailer could set up a topic tracking a specific style of pants to understand the consumer reception. “Since textile waste is a significant problem in the fashion industry this type of AI-generated intelligence could lead to tighter supply chains by aligning demand and supply,” Sener said. Additionally, AI could streamline the entire inventory management process in terms of forecasting, planning and control so that retail businesses minimize the possibility of overstocking or understocking based on location-specific demand. “We’ve already seen how large retail companies like Amazon use AI-based robots to manage day-to-day warehouse logistical tasks 24/7, cutting back on hiring needs and avoiding downtime due to sick leave and PTO,” Sener said. Future of AI in CX While most retailers use data to make decisions, the hesitancy isn’t necessarily around a data-driven approach to CX. “It’s more about leveraging data to unlock automation and predictive analytics, incorporating AI to enable self-service and give agents better tools to resolve customer inquiries more quickly,” Shannon Flanagan, vice president of global strategy of retail and consumer goods at Talkdesk. “For a lot of organizations, retail or not, AI can be seen as a trigger word that may have left a bad taste in their mouth given prior experiences. We as customers can relate with chat bots that made us want to scream.” Retailers will focus on AI-assisted intelligence because it provides customized CX through personalized recommendations and as well as: Efficiency: AI can automate tasks and streamline operations, increasing efficiency and reducing costs. Customer service: AI can improve customer service by providing instant support and answers to common inquiries. Data analysis: AI can analyze vast amounts of data to make informed decisions about inventory management, pricing, and marketing strategies. Inventory management: AI can accurately predict demand and optimize inventory levels to minimize waste and maximize profits.” “In today’s world, it often seems that the only certainty for retail brands is uncertainty,” Sener said. “Holding fast to current customers while enticing new brand champions will require supreme flexibility in the coming years. The question is how will retail brands adapt, adjust and pivot to keep pace with our ever-changing world all while staying in front of the competition? The answer: AI-powered brand intelligence and deep listening to customers’ wants, needs, and expectations.” What’s next: The first step in setting up AI solutions at retail is determining where it can be most effective in both the short- and long-term. Short-term solutions like CX and customer service are routes that are easily achievable, while investments in trend forecasting, supply chain management and product development may have longer lead times and more obstacles to overcome.

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