Telecom & Technology Consulting
So you sell retail goods? The same can be said for your competitors. In the battle between you and everyone else in your category, your offerings are no longer the sole reason why someone chooses one retailer over another. The winning recipe can often be distilled to one element: the quality of the customer experience.
Of course, the actual products themselves play a role in your success. Yet consumers, increasingly, can view specific product categories as commodities when comparing features between multiple companies.
To that end, savvy retailers are focusing more on how artificial intelligence (AI) can give them a customer experience advantage. For context, consider that consumers will almost immediately shop elsewhere if their expectations – from finding what they want on your site to customer service to shipping – aren’t met. A recent Salesforce survey found that 71% of consumers will abandon their loyalty when encountering this scenario.
Customer service is one of the key areas where AI can prevent people from having poor experiences. The reality is that traditional technology isn’t nimble or smart enough to supply service reps with the ability to easily resolve common customer complaints. Agents must grapple with slow, inefficient technology that involves too many steps and not enough customer information.
But cloud contact center solutions that leverage AI can give agents the powerful tool they need to deliver world-class customer experiences. For example, with customer experience management, AI can deliver real-time insights into customer interactions and can automate many processes, which provides measurable results: Average handling time can be reduced by up to 21%; agent efficiency can improve by 20%; and customer satisfaction can increase by 37%, leading to a 30% boost in revenue.
AI energizes the customer experience in many other ways. With AI-powered predictive analytics, retailers can analyze consumer data, identify patterns of behavior, and anticipate expectations. Not only does this information allow you to enhance service at a micro level, you can boost results at a macro level for operations, the supply chain, and forecasting. Best of all, the actionable insights you gain from AI ultimately decrease customer turnover, and help you convert one-time customers into long-term brand ambassadors.
On a related note, AI provides an entirely new ability for personalization. This is critical, as today’s consumers tend to be turned off by general, for-the-masses messaging and experiences. According to recent studies, 71% of consumers want personalized experiences, with 76% reporting a negative impression of the brand when they don’t get the level of customization that expect.
With AI, retailers can tailor the user experience to each consumer. This includes personalized product recommendations throughout the shopping and purchasing journey. And since these offers are precisely based on an individual’s data, companies end up converting more prospects, increasing revenue, and of course driving repeat purchases.
Personalization matters not only because of consumer demand, but also due to the rise of the omnichannel retail environment. People now shop on multiple devices and platforms – in fact, consumers are engaging with your company on an average of nine channels to communicate with you. From social media to email to phone to chat, it’s essential for all communication points to provide a cohesive and consistent experience.
This is where an AI-powered solution can deliver improved results. With AI, customer data across every platform and interaction is immediately available, meaning customers only have to share information once – they never have to repeat themselves. While that may appear insignificant, repetition is a main source of negative brand perception for consumers. Surveys indicate that when the need to repeat themselves in eliminated, 92% of customers claim they will be willing to interact more with a given retailer.
AI also allows you to go beyond pure data, and better understand a consumer’s actual intention. With a feature called AI sentiment analysis, you can search keywords, index conversations, and assess the true meaning of every customer interaction. It works like this: when someone calls a contact center, the AI solution will automatically analyze speech patterns, as well as tone of voice, to measure if there’s – for example – a level of frustration or satisfaction. Retailers apply this information to train customer service reps on how to improve word choice, emotional intelligence, listening skills, and conflict resolution during customer calls.
As much as consumers demand better experiences, they also want the power to control those experiences. Thus the need to offer a robust suite of self-service tools. To that end, more and more retailers are implementing conversational AI chatbots into the customer journey. These intuitive tools give customers a convenient method for resolving issues without the need for human-powered customer service.
Another AI tool, Interactive Voice Response (IVR) systems, provides customers with conversational experience method – one that feels as natural as “talking” to a human customer service agent on the phone. IVRs automate certain tasks and can route callers to the most appropriate agent when needed, saving time and costs while delivering an efficient and memorable experience.
Efficiency is the name of the game here, as chatbots and IVR systems reduce the burden on your team. As such, customer service reps can focus more effort on complicated requests, and, in the process, improve the quality of those outcomes.
The relationship between AI and the business world is still in its infancy; every week and month brings a new development or application of the technology. This also applies to how AI will affect the way retailers enhance the customer journey. No one can predict the evolution of AI. However, the retailers that fully embrace the potential of AI are more likely to improve customer experiences, and eventually lead the pack in their respective categories.
