One of the most valuable things to measure in order to continuously create better relationships with customers is customer sentiment. Knowing how your customers feel about your brand and your products can guide strategic decisions, give you a better understanding of the ideal customer experience, and overall, help push your revenue upward.
If you understand what is really driving customer love, the roadmap becomes so much clearer. You can harness the exact pieces of experience that are creating that emotional connection, and improve upon the areas that are causing a rift.
But since customer sentiment is all about feelings, it can be a pretty tricky thing to measure. How can you quantify what seems like such a subjective concept, and where do you pull all of the data from?
Things like social media listening, review mining, and surveys are popular methods to collect insight into customer sentiment, but today I want to propose a typically untapped but highly valuable magnet for this data: chatbots.
Chat as a tool for measuring customer sentiment
Typically, chat is seen primarily as a support tool. And it’s true that AI support agents are powerful tools that can improve the support experience and alleviate some burden from your human support teams. But that doesn’t mean that the value of chatbots stops there.
Chat is a valuable place to pull deep and valuable information that points to indicators of customer love. In many cases, you can use chat to uncover thoughts from customers that you may have never found from a survey.
Unlike structured surveys or feedback forms, chat conversations capture the raw, unfiltered emotions of users, giving you richer, more authentic insight into their feelings toward a product or service.
One of the major advantages of using chat to measure customer sentiment is the immediacy and natural flow of conversation. Customers express their thoughts in real time, using their own words and expressions. This can help you pick up on emotions and even tone more easily.
This spontaneity can lead to more honest and detailed feedback because customers feel less constrained by predefined response options.
Chat interactions also often occur when the customer is currently engaged with the product or service, layering on the ability to give you contextually relevant information.
Advantages of using AI in chats
Of course, the value of the data you pull depends on the quality of the chatbot you’re using. If you use a chatbot that can only follow extremely limited scripts, your customers may not be engaged enough to reveal anything truly valuable.
But thanks to the rapid evolution of chatbots powered by conversational AI, these chats can increasingly feel more human, helping you tap into a treasure trove of insights on customer love without needing to get real humans involved.
Many AI tools can actively probe deeper in their conversations with customers, encouraging more detailed responses to mine sentiment data from. For example, if someone mentions frustration with a product, or if their tone indicates that they’re extremely happy with a product, the chatbot can ask more clarifying questions to get to the heart of the matter.
And thanks to chatbots sounding increasingly human, these conversations should flow naturally, making it more likely that the customer stays engaged.
So why is this better than a human support agent?
Chatbots may also encourage users to share more thoughts and feelings than they might with human agents. People often feel more comfortable expressing their true emotions when interacting with a bot, knowing there is no judgment or bias. This can lead to more candid and comprehensive feedback.
Probably the most obvious benefit, though, is the scalability. The average call center receives 200 calls per day, meaning there are 1,000 calls per week and 4,000 per month. This volume is tricky to handle, leading to high costs due to having to
AI chatbots aren’t paid by the hour. They’re more than happy to work day in and day out, and you don’t have to worry about burnout. Not to mention the 24/7 availability. These chatbots can work around the clock to provide support, keep analyze-able records, and ask probing questions.
Another advantage is the ability to leverage relevant information. While a human would be limited to looking up whatever information they can in the few seconds or minutes after receiving a question, AI is powered by loads of data. They’re just more efficient at providing better answers in less time.
In short, an AI agent like our Copilot is like a support agent and customer success manager combined. They can handle all of these support tasks easily, contributing to a better overall experience, all the while probing for and collecting valuable information about customer sentiment.
Leveraging sentiment data
If you’re using the right tools, all of this data mined from your chat should come together seamlessly to help you leverage customer sentiment.
CommandBar, for example, gives you access to customized dashboards that help you discover these moments of customer love in chat interactions. You can see, specifically, which products, experiences, features, or other components of your product or service led to these valuable feel-good moments.
By analyzing these interactions, you can identify trends, address pain points, and celebrate moments of customer love, helping you build stronger relationships with your customers.
Customer sentiment can help you inform product development and innovation.
By understanding what’s driving customer love or hate in your current offerings, you can make better decisions about future iterations. Features that resonate well with customers can be kept, enhanced, or expanded, while features that drive a lot of negative sentiment may need to be re-strategized. This helps you take a genuinely customer-centric approach to product development by making sure that your new products or updates are aligned with user needs and preferences.
Sentiment data can also be integrated into your customer relationship management (CRM) systems to personalize interactions and build stronger relationships. Support agents and account managers can tailor their communication strategies to suit each customer's emotional state and preferences by keeping a record of individual customer sentiments.
For example, a customer who has previously expressed frustration may appreciate a more empathetic and solution-focused approach in future interactions, but a satisfied customer might respond well to cross-selling or upselling.
Another great way that we recommend using this insight is to target users who expressed overwhelmingly positive sentiment with a campaign that requests a review on websites like Capterra or G2. You could also approach them to create a case study. Getting testimonials from this valuable group of people can help you put your best foot forward to others who are in the consideration phase.
Opportunities to uncover customer love are unpredictable - AI chat helps you reel them in
Your chatbots are likely being used anyway to provide support, so why not have them do double duty? By tapping into the spontaneous and unfiltered nature of chat, you can uncover deeper emotional connections and address issues with precision.
