Customer experience plays an important role in the growth of your brand. That’s why it’s essential to not only offer a great experience but also understand if you truly are able to cater to your customers well. That’s where you can use artificial intelligence to improve your customer experience measurement.
But why is customer experience so important?
Nearly 84% of consumers say they go out of their way to spend more money on great experiences. So, it’s safe to say that a better customer experience translates into higher sales and revenue.
Image via Gladly
But to improve your customer experience, you must know where you stand in the first place. For this, it’s important to do customer experience measurement. Artificial intelligence (AI) plays a major role in automating and speeding up various marketing activities and it can help improve this process as well.
So, let’s take a look at how you can use artificial intelligence to improve your customer experience measurement.
Ways to Use Artificial Intelligence to Improve Customer Experience Measurement
Here are the different ways through which you can use artificial intelligence to improve your customer experience measurement.
1. Analyze Customer Feedback
To truly get an idea of where you stand in terms of your customer experience, it’s essential to collect and analyze customer feedback. The idea here is to hear all about your customer experience from the customers themselves.
It’s the best mode of understanding where you’re excelling and or lagging in certain aspects of customer experience. Accordingly, you can understand what changes need to be implemented to improve the experience. This, in turn, can help boost the sales of your ecommerce or brick-and-mortar business.
So, how can artificial intelligence help with this?
Collecting customer feedback may be simple. However, analyzing the feedback can take a lot of time and effort, especially if you’ve got a lot of customers. You’d have to manually go through individual feedback and then analyze that unstructured data.
However, AI can speed up this process of measurement. Using text analytics platforms, you can seamlessly analyze large amounts of feedback data from your customers. This quick analysis will help you derive valuable insights that you can leverage to improve your customer experience strategy.
2. Leverage Chatbots and Live Chat
Another way in which artificial intelligence can help you collect, analyze, and improve your customer experience measurement is through the use of chatbots and live chat.
Using AI-powered chatbots, you can converse with your customers in real-time. Using the power of machine learning and natural language processing, these chatbots can understand the questions posed by your customers and answer them.
What’s more?
Apart from chatbots, you should also use live chat platforms to offer customer service in case the chatbots aren’t able to answer the questions posed by the customers.
But how does customer experience measurement come into the picture here?
When your customers chat with your chatbot or customer support representatives, they can ask them to rate the interactions. The feedback data collected can be analyzed by artificial intelligence-based tools to help you understand how well you were able to service their questions.
3. Understand Customer Emotions
To understand your customer experience, it’s important to get an idea of their emotions as well. You need to understand and predict them to find out if they’re satisfied with your brand’s services or not.
Until recently, there was no easy way of going about this. You had to rely on the customers telling you about their emotions, and such instances, unfortunately, aren’t many.
However, with the advent of artificial intelligence, it’s possible to detect the emotions of your customers from multiple channels.
For instance, artificial intelligence tools can seamlessly detect the customer’s emotions based on the messages they’ve sent or the conversations they’ve had with your customer support team.
Emotion AI tools can pick up emotional signals by observing the tone and pitch of the customer’s voice. They can also analyze the text written by your customers to understand if they’re happy, sad, stressed out, angry, etc.
What’s more?
Even if you’ve got videos of the customers, these tools can identify their emotions using their body language, changes in facial expressions, etc.
All of this analysis can help you identify how well you’re performing when it comes to customer experience.
For instance, Grammarly, the popular writing tool, can recognize the emotions in the text that’s written. This helps you better understand the customer experience and you can accordingly take steps to improve it.
Image via Grammarly
4. Speech Analysis
Most call center records are converted into transcripts for reviewing at a later stage. However, the one thing that transcripts can’t help you identify is the emotions of the customer at each point in the conversation.
You wouldn’t know if the customer raised their voice, had an angry tone, felt sad, or was elated by your service. Transcripts won’t be able to tell these things to you and when it comes to customer experience, these are all important cues that you must not miss.
All of these cues would only be available if you’ve recorded the customer’s call in its audio format. By getting access to this speech, you would be better able to understand if your customer experience was positive or negative.
Artificial intelligence can help improve your customer experience measurement in this case too. Using AI-powered speech analysis tools, you can understand the tone of each customer. Also, these tools can help you find out the:
- The intent of the call
- Topic of discussion
- Relevancy
This measurement process would be quick too as artificial intelligence would be able to go through a large number of calls with ease as compared to listening to them manually. All this information would be extremely useful for helping you understand the customer’s current situation. Based on that, you would be able to determine the future course of action as well.
5. Gather Customer Feedback Across the Journey
One of the toughest tasks that you might face as a customer experience professional is that of finding out the customer experience throughout the sales funnel.
But why is this task difficult?
The customers may go through numerous stages during the sales funnel and they may connect with you at various touchpoints too. As a result, all the customer data would be in different silos. These silos can act as deterrents to determining the customer experience as you wouldn’t have a unified database for each customer.
Analytics and insights derived from such segregated data might not be very accurate and won’t paint the whole picture for your customer experience.
However, customer journey analytics tools based on artificial intelligence can help you change this. They can unify your customer data from the entire customer journey and analyze it. This singular customer journey view will help you get an accurate measurement of the customer experience.
Final Thoughts
Customer experience plays a pivotal role in the success of your brand as it influences customer retention. That’s why it’s essential to measure your customer experience regularly and improve it.
Artificial intelligence can help with this by analyzing customer feedback and deriving insights from it. Also, you can use chatbots and live chat to collect and analyze customer feedback.
What’s more?
Tools powered by AI can also recognize customer emotions in text, voice, and videos. This can help you understand their experience and improve it. Finally, these tools can also help unify all your customer data from across their journey and analyze it. As a result, you’ll be able to get an accurate measurement of your customer experience.
Do you have any questions about the various methods of using artificial intelligence to improve customer experience measurement mentioned above? Ask them in the comments.
Image: Depositphotos
This article, "5 Uses of Artificial Intelligence to Improve Customer Experience Measurement" was first published on Small Business Trends
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