How Can AI-Based Automation Tools Improve Customer Experience?

Thanks to different technological advancements, customers interact and engage with brands in numerous ways and on various channels. As a result, their expectations have skyrocketed, meaning that they demand seamless experiences.

80% of companies consider customer experience to be one of their most powerful competitive differentiators. In order to keep pace and be a disruptor in this digital customer experience battlefield, you should consider tapping into artificial intelligence. Machines and algorithms have become increasingly smart, to an extent that they can pick up the slack and speed up different business processes.

In this guest post, Qeedle’s Michael Deane shares some of the most effective ways AI-based automation tools can help you wow your customers.

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Introduce Customer Self-Service

No matter whether there’s a potential client who has a couple of questions about your product or an existing one, who needs their issue solved, you need to act quickly.

Putting your customers on hold until one of your customer service agents is available can be highly detrimental to your conversion and retention rate.

Stats say that consumers will wait on average 11 minutes for a customer support representative before they hang up. However, you should aim for significantly shorter waiting times if you want to keep them. AI-powered chatbots and virtual assistants can completely transform your help desk and eliminate waiting on hold. Unlike your human agents, these smart algorithms are available 24/7/365 and can handle a number of customer queries at a time.

And we’re not talking about your average chatbots that come with a predefined set of canned phrases and sentences. A synergy of AI and natural language processing has revolutionised chatbots and turned them into conversational tools. According to predictions from a couple of years ago, by 2020 the average person will have more conversations with chatbots than with their significant other.

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With chatbots dealing with some simple, frequently asked questions, your customer support representatives will have more time to focus on complex queries. This will tremendously improve their productivity and streamline the entire process, thus boosting customer satisfaction.

The fact that your smart chatbots are still machines means that they’re never tired, nervous, or angry. Therefore, your customers will always be greeted and served by a polite, patient, and helpful assistant. A successful onboarding process is another factor that plays an important role in keeping your churn rate low. AI-powered chatbots can come in handy when it comes to helping your customers navigate your product or service and showing them the ropes.

Step Up Your Upselling and Cross-Selling Game

Personalisation will help you make your customers feel special and unique. And they hold that in great regard. But, effective personalisation goes well beyond a first name. Your customers want you to know their needs and interests, and to understand their challenges. And that’s what one of the most common use cases of AI is all about – providing you with all the customer information you need in order to offer them a five-star service.

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Big data, which is a subset of AI, is capable of collecting, analysing, processing, and interpreting huge volumes of unstructured data. In other words, this powerful analytics method combs through oceans of data, identifies hidden patterns, and provides companies with valuable insights about their customers and prospects.

Amazon and Netflix managed to perfect their recommendation engines, and offer their customers relevant, personalised shopping or watching suggestions. These two giants use AI to analyse their customers’ past behaviors, compare them to that of other users with similar preferences, and find the best picks.

Such a data-driven, automated approach generates 35% of Amazon’s revenue. It’s clear that using a recommendation algorithm can be a great way to sell more. For example, it identifies what products are usually bought together and creates personalised suggestions based on that.

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Similarly, when a potential customer views a certain product, a recommendation algorithm can show items with similar characteristics from a higher price range in an attempt to upsell.

Dynamic pricing is one of the latest trends and it helps e-commerce stores adjust their prices based on the real-time supply and demand. Amazon, for example, updates its prices every 10 minutes.

AI and machine learning have enabled this strategy. Namely, it would be impossible to monitor all the important factors for every item in your online store and update the prices manually. A well-built algorithm uses all the relevant customer data and takes different factors into consideration to properly respond to demand fluctuations.

Combat Abandoned Shopping Carts With Smart Emails

Stats say that the average shopping cart abandonment rate is almost 70%. This means that only 30% of the products your customers pick and put in their shopping carts end up being purchased.

Different reasons are responsible for this not so great statistic. The thing is that you can’t do much about some of them as a lot of people are only window shopping and place items in their cart without an intent to buy them.
Apart from that, a poorly designed checkout process is among the main culprits, as well as extra costs or inability to calculate a total order cost in advance. However, certain customers simply forget that they have put something in their cart or aren’t sure whether to purchase it or not.

With AI-powered smart email tool, you can create automated email campaigns and target prodigal customers who left your website without making it to the checkout. This advanced technology allows you to automatically send personalised emails to remind your customers that they left certain products in the shopping cart. As it’s critical to reach out to these customers as soon as they leave, these smart emails are action-triggered. All you have to do is create customisable templates of the initial and follow-up emails, set up the intervals and the tool will do the rest.

Recognise Customer Sentiment and Intent

Did you know that 96% of unhappy customers won’t complain to you but will tell their friends about their negative experience with your brand? Or more precisely, they will tell the whole world if we bear in mind that most people use social media to express their opinions.

And what’s worse, you won’t be in the know when this happens and won’t be able to do anything to fix things – if you don’t use social media listening or customer feedback tools.

Mopinion is one of them and it makes things easier for brands that want to stay on top of their customer feedback. With its AI-powered features, it’s possible to perform:

  • Text analytics, thus gaining a more profound insight into customers’ sentiments towards your brand.
  • Automatic categorization using ML. This feature allows you to automatically label customer feedback and categorize it, which will streamline handling complaints and issues.
  • Automatic anomaly detection. This feature uses different factors such as variables of a feedback form, text meaning, and metadata among many others to identify trends and patterns in customer feedback and inform you of valuable insights and findings.

Natural language processing analytics is capable of analysing the conversations around your brand and identifying the overall sentiment. This means that you will be able to spot an issue before it snowballs into a total PR disaster and damages your reputation. By being informed of what your unhappy customers are talking about your brand, you can join the conversation and offer your help in solving the issues they’re having.

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Samsung used this technology to handle customers’ dissatisfaction over the red-tint issue on their S8 model back in 2017 and act upon it in advance.

Similarly, this approach can be used to identify purchase intent and target potential customers with advertising or even a discount. Natural language processing interprets in what manner your potential customers are talking about your brand and is capable of catching a whiff of positive sentiments.

Delivering on your promises and doing it in a timely manner is what your customers expect. All these use cases prove that artificial intelligence and its subsets – machine learning and natural language processing, can help you improve customer experience by speeding up customer support processes. In other words, it allows you to give your customers exactly what they want at the right time.

About the Author

Michael Deane has been working in marketing for almost a decade and has worked with a huge range of clients, which has made him knowledgeable on many different subjects. He has recently rediscovered a passion for writing and hopes to make it a daily habit. You can read more of Michael’s work at Qeedle.

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