We have all heard about customer experience. We have our own perception of what makes that experience good or bad depending on our background and personality. But what we know for sure is that it is the cornerstone of any customer-facing business. Now, you’re not alone handling this touchy topic: AI can help you to improve your customer experience by making your company available 24/7, providing a personalized and measurable customer experience.
The customer life cycle begins with the first touchpoint they have with a brand, such as a pop-up window or email notification, making a purchase or using the product. The better the experience the customer has with a brand, the more they are likely to use and recommend it.
As the online retail industry becomes more competitive, brands are turning to artificial intelligence (AI) to improve the quality of their customers' online shopping experiences. For instance, with the "Customers Also Bought" feature, many clothing retailers such as Zalando or Asos deliver personalized recommendations.
These innovations aren't only about increasing revenue, it also reduces all the friction in the buying (and return) process. This creates a better and faster shopping experience.
Consumers also expect brands to be responsive and up-to-date. In fact, 54% of respondents would use a chatbot to ask about a product and 30% would use it to pay a bill. By adding an automated live chat, you can help your customers find answers to their questions while they’re placing an order, no matter the time of the day!
It’s wrong to say that consumers don’t like advertisements. Consumers don’t like ads that are not personalized and relevant to their current state of mind or situation. Consumers don’t hate ads, they hate bad ads. In fact 83% of people answered "Not all ads are bad, but I want to filter out the really obnoxious ones." and 77% agreed with "I wish there were a way to ad-filter instead of ad-block completely."
To stop adding noise to this over-crowded ad world, AI can help you create really relevant digital ads. Machine learning can help companies anticipate if a person is likely to click on an ad based on online behavior.
For instance, predictive targeting can allow your ads to be adapted to a specific customer based on thousands of signals. These algorithms improve over time to provide increasingly personal ads.
Customers don’t just expect the best price when making a purchase: they also expect fast customer support. Having a conversational AI allows you to provide instant answers, at any time of the day, to mundane questions like cancellation policies, order status, etc. Recent study showed that more than 40% of customers like the ability to get answers outside of normal customer service hours. In fact, 90% of consumers say getting an immediate response to a customer-service question is “important” or “very important.”
Brussels Airlines has been able to reduce the call volumes to their customer service centers while also providing multilingual 24/7 support for their customers. 70% of people who interact with the chatbot never ask to be put in touch with an agent. This has enabled Brussels Airlines to serve a growing customer base at a much lower cost. Now, the average agent response time is under one minute.
In addition to the immediate response, consumers want to have answers on the channels they are using the most. Handling it with a human-only agent team is hard and expensive. AI helps companies scale support across chat on their website, social media (Facebook Messenger bot), Whatsapp, voice platforms (IVR) and SMS. Without conversational AI, it can be very complicated to provide the truly omnichannel support that customers expect - immediate, helpful and personalized.
The help of AI doesn’t just reduce costs; it actually helps your customers resolve issues faster, providing better customer satisfaction (CSAT).
When an agent is handling hundreds of customer messages each day, it can be difficult to take a step back and be able to measure customer satisfaction. AI tools can indicate positive or negative sentiments among your customers. In this research where NLP was used, we can see that AI is able to generate and convert key characteristics into predictive variables that can train the AI to predict whether customers are satisfied, neutral, or have a complaint, without using quantitative surveys.
AI algorithms can analyze vocabulary used by customers and combine their views expressed in their own words with traditional rating scales to get deep insights. These insights can help you define your customer loyalty strategy.
According to Gartner, we can expect that 20% of all customer interactions will happen through a virtual agent in 2022. And according to Servion Global Solutions, by 2025 AI will power at least 95% of all customer interactions.
More and more businesses realize the huge potential of customer service automation to reduce response times, deliver great customer experience and improve customer loyalty. Companies will use conversational AI more and more, becoming as common as human customer service agents interactions.
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