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Along with many other things, the past two years of the pandemic have changed our consumer patterns, with 89% of shoppers expressing concerns about in-store shopping and proximity to other people.
All of a sudden, retailers were reduced to digital for a customer interaction channel, and while online retailers barely felt the change, for offline retailers it was a new reality to adapt to. This resulted in a tech breakthrough, which normally would have taken years to make, and the ecommerce sector grew by more than 30% in 2020.
More than two years have passed and the digitization of retail is gaining momentum with AI-powered conversational agents being a significant part of it. Chatbots engage with customers online, provide information and answer questions, among other things. Juniper Research expects chatbots to save retailers globally $439 million a year by 2023 compared to $7 million in 2019. In this piece, I’ll talk about efficiencies that conversational AI can create for retailers and common roadblocks that get in the way of chatbot projects.
Related: 4 Ways to Use AI to Enhance the Customer Experience
Conversational AI meets retail
According to Accenture, chatbots are mostly expected to reduce the time for processing requests and increase the productivity of employees. Here are a few examples of how conversational AI can help retailers navigate the challenges of digitalization:
AI-powered chatbots make it possible for businesses to provide excellent customer service without increasing employee numbers. The technology enables businesses to make a call at a moment when the customer receives an order and still remembers the entire history of communication with the company. The results of a smart call will show whether customers are willing to recommend the company to other people and help businesses adjust their strategy, loyalty program and rewards system.
Improved service quality
Chatbots and voice assistants can answer consumer questions day and night, on holidays and weekends, 365 days a year. Unlike human agents, AI-powered assistants don’t need sleep and can assist customers even after business hours. Naturally, when customers get immediate help, it increases their satisfaction with the services.
Higher response rates
Bots respond instantly, in a consistent and specific manner, without giving out any unimportant information to the customer. When integrated with CRM systems, they can access order history and customers do not have to repeat basic information about themselves.
Chatbots and voice assistants allow businesses to stay in touch with customers and inform them about new products, promotions, and discounts. Customers regularly see information about the company — when they need to make a purchase, they know exactly where to go.
The consumer sees that his requests are understood. This attitude is the foundation for building trust and loyalty to the company. Brand supporters are important in competitive industries such as retail because it costs a lot more to attract a new customer than to keep one.
Faster customer feedback
Personalization in marketing has been around for some time: Some 75% of consumers are “keen on buying from brands that offer personalized digital experiences.” To offer this hyper-personalization, businesses require specific data and chatbots can easily handle data collection faster than a call center and at lower costs.
HR process automation
Large retail chains employ thousands of different professionals. They need to look for and hire the right candidates and train new employees according to the company’s standards. Bots can take care of the initial selection of candidates, setting the date and time of the interview, as well as training programs.
Related: What Small Retailers Can Learn From the Industry’s Push Towards AI and Big Data
Retail digitization: things to consider
Despite an extensive list of business processes that conversational AI can help automate, there are reasons why some retailers are in no hurry to start adopting the technology.
Legacy customer relationship management platforms
Among the things that hinder conversational AI adoption is the fact that retail companies often use legacy CRM and heavily customized billing systems. There are so many different technologies, products and systems “under the hood,” that business processes are very difficult to digitize. Sometimes, to change an order, one has to use from two to five systems to get the data needed.
So, if a company wants a voice bot that will respond to inbound calls and inform customers about order status, they need to have all the necessary integrations in place and make sure the voice bot has instant access to the right systems and data.
Still, it’s also important to say that upgrading systems or transitioning to a new CRM platform in retail is extremely expensive and time-consuming.
Apart from the pricey upgrades, there are other reasons behind the high costs of conversational AI projects in retail: from wide assortments of products to large data volumes to customization needs.
That’s why large retail chains adopt conversational AI more eagerly; they have a sufficient volume of inquiry topics and automation results in reduced contact center load, reduced time to provide information, and ultimately, customer service costs.
However, today more conversational AI tools allow even small businesses to build basic chat and voice bots, and this way start contact centre automation. With visual bot builders like ManyChat, Voiceflow or DialogStudio, it takes little to no coding skills to create a bot that will help reduce contact center load during seasonal sales.
Besides, there are ready-to-use AI-powered conversational solutions that address particular needs that retailers have. Thus, a smart Shop Assistant, for example, helps customers to easily navigate a mobile app, place orders using voice commands and check the shipping information, as well as ask users for feedback after the purchase.
Related: How AI is Making Retail Shopping Experience Simpler for E-commerce Consumers
Those who venture into an AI bot project, need to remember that the work doesn’t end there. It implies continuous training, adding seasonal items to the catalog, refining bot scenarios and promoting new specials. Here the retailer has a choice: hand over the management to a vendor or invest in a strong in-house team.
There are a lot of ways how conversational AI technologies can benefit retail, but what worked for one company may not apply to another. For example, a voice bot for outbound communication that works as a consultant and salesperson would be a good fit for products people buy regularly: contact lenses, pet food, etc. But it’s unlikely that this technology would work for a retailer selling refrigerators — here, a voice bot for NPS surveys would work much better.
Digital transformation is not something businesses can veer away from, while the growing market of conversational AI technologies and successful implementation of cases prove that retail chatbots and virtual assistants will become an integral part of our lives soon. Fortunately, as technologies evolve, adoption of conversational AI is no longer a prerogative of large retail chains, small and medium-sized businesses can begin with basic conversational solutions, but no change is too small.