It’s no secret that the COVID-19 outbreak changed how retailers operate and interact with customers. Early in the pandemic, we explored three trends that seemed to be accelerating including: contactless transactions, personalization, and the importance of great loyalty and rewards programs. We’ll now take a closer look at what’s happening behind the curtain and the technology that’s poised to super-charge operational efficiency and worker productivity in the post COVID world.
That technology is artificial intelligence (AI) and here are three ways retailers can put AI in retail to work to support operations.
Retail Operations Trend #1: “Returning” Efficiency
Merchandise returns are a real drag on retailers. Industry experts estimate that customers return 5% to 10% of what they buy in store and 15% to 40% of what they purchase online. Those returns add up – with merchandise returns accounting for $309 billion in lost sales for U.S. retailers. What’s more, about 9% of returns are fraudulent, with an associated cost of an estimated $27 billion. Returns aren’t fun and games for customers, either. In fact, one industry survey found that nearly three-quarters of Americans view returns as their least favorite part of shopping online.
Add it up and retailers have numerous opportunities to put strong AI and machine learning (ML) to work. These technologies can help automate the return process while problem solving and identifying suspicious patterns – with a scan-and-go in-store kiosk that eliminates the need to stand in line for the customer service desk. Additionally, ID verification systems and video analytics machine learning algorithms can be added to minimize return fraud.
How are you tackling challenges related to merchandise returns? Have you considered how AI can help automate the process, reducing friction for customers and raising productivity for your workforce?
Retail Operations Trend #2: Deploying AI “associates”
Artificial intelligence in retail is also about creating personalized experiences for retailer’s in-store, this can be done by utilizing conversational agents who can become an innovative addition to a retail industry's digital experience. AI can provide new, personalized ways to engage with customers – freeing associates to focus on those with more complex questions.
The cosmetics industry provides two intriguing examples of what’s possible. Olay has an AI-powered Skin Advisor feature, which analyzes skin based on an uploaded selfie and a customer’s self-reported skin care preferences. The AI determines the user’s “skin age” and then recommends products based on those results.
L’Occitane en Provence uses another form of AI – facial recognition software – to serve up relevant products / product recommendations as customers approach the store. After installing the solution, stores experienced a 36% bump in conversion, illustrating AI’s potential as a new member of a store “workforce.”
Even if you aren’t selling cosmetics, you can deploy AI as part of your team. How might these technologies serve as an extension of your sales team?
Retail Operations Trend #3: Lightening the load for human associates
AI and ML tools can help stores overhaul how they manage day-to-day operations, empowering associates to stay focused on customers, not manual tasks.
AI can be used to execute buy online/pick-up in store, saving customers effort and enabling associates to spend less time focusing on inventory management . For large chains, AI can help tailor product selection and services based on each store’s local people, places, and events that influence customer behavior and demand. And AI-enabled automation and predictive analytics can help in monitoring, anticipating potential outages, and replenishing inventory. Computer vision can be used to notify store associates when certain shelves need to be restocked in real-time. Things that may have seemed like science fiction 5-10 years ago are now being deployed and piloted.
In what areas do human associates provide the greatest value to your customers? How can you offload manual, repetitive tasks to AI so they can focus on those areas?
These examples are only the beginning when it comes to how retailers can use artificial intelligence and machine learning to improve in-store operations and worker productivity. Ready to put AI to work for your business? Let’s talk.
Sree Singaraju is the Senior Vice President of AI and Cloud Services at Mobiquity. In his experience, the cloud is the key enablement ingredient for any digital solution: mobile, voice, web, chat, AI/ML. Since the cloud is at the center of every Mobiquity engagement, Sree is a natural fit and great asset to every company engagement. Blending his experience leading transformations at organizations like Johnson & Johnson, Dun & Bradstreet, Merrill Lynch, and State Street Bank, with his expertise in cloud and artificial intelligence, Sree spends his time helping companies transform their goals into reality. A true believer in the power of personalization, Sree wants to support companies in their journey to create responsible AI. To do this, Sree’s work involves creating programs that cater to an audience of one, meaning every single engagement that a user has is personalized to them. No longer will customers get ads for credit cards they already have or promotions for meat lover’s pizza if they are a vegetarian. Rather, Sree is focused on creating meaningful experiences for each individual customer. In his spare time, Sree enjoys playing tennis with his friends and even participates in local tournaments. He has two sons and has coached their baseball teams. Sree is also very interested in podcasts, specifically ones that offer different perspectives so that he can learn new things and gain inspiration that can carry over into his work-life. Sree holds an MBA in Information Technology from Rensselaer Polytechnic Institute and is a graduate of Jawaharlal Nehru Technological University where he studied Civil Engineering.
Give us your information below to start the conversation.
