The Essential Role of AI in Conversational Analytics

Every customer conversation holds valuable insights. But how to unlock them? That’s where conversational analytics and AI come in.

Let’s find out why conversational analytics matters, how companies are using it, and where conversational AI fits in. Plus, our free checklist can help you understand if your business is ready to integrate it.

Introduction to Conversational Analytics

First, the basics. What is conversational analytics?

Conversational analytics is the process of analyzing data from conversations, like customer service interactions, surveys, or other sources of dialogue. By unlocking these insights, businesses can get to know their customers better and accordingly improve products or services.

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As companies increasingly interact with customers across various platforms, it has become crucial to analyze these conversations and gain insights into customer behavior, preferences, and needs.

The Key Benefits

Unlike traditional analytics that reduces customers to numbers and data points, conversational analytics embraces the messy reality of human communication. By analyzing actual conversations, companies learn how customers feel and why they make decisions. This communication becomes more personal.

These four key benefits of conversational analytics provide a strong foundation for building customer loyalty, which, unsurprisingly, is the ultimate goal for most companies.

The conversational analytics approach acknowledges that customers experience brands through interactions, emotions, and stories, providing a better understanding of their needs. This goes beyond clicks and conversion rates.

The Rise of Conversational AI

As we discovered, the foundation of conversational analytics is the conversation itself. One common way companies obtain real chat data for analysis is by using conversational AI.

Conversational AI is transforming the way people work and communicate. A recent DeskTime survey shows that 76% of offices globally now use ChatGPT.

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Companies across industries are embracing conversational AI tools to handle customer service, streamline operations, and rethink how business gets done. Let’s look at some real examples.

These famous brands prove that conversational AI is driving real impact across different industries. It not only builds a base for further conversational analytics, but it also personalizes customer experience and improves overall satisfaction.

Conversational Analytics in Practice

Theory is important, yet practice is where you truly turn knowledge into action. That is why we want to show you how we use conversational analytics. At Ajelix, we have more than 18 AI productivity tools, and recently, we launched a new one.

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Agnese, co-founder of Ajelix, states that the new AI Data Analyst tool has resolved a challenge users previously faced quite often: the time-consuming process of obtaining data insights.

The AI Data Analyst, which turns raw data into insights and reports through a simple chat, was created based on user struggles and feedback that was collected through a survey. Surveys can be a great source for conversational analytics, so why not show you a sneak peek of how we analyzed the results?

We presented our messy survey answers spreadsheet to the AI Data Analyst and, first, asked for some quick insights. (Kind of funny we presented the evaluation of a tool to the tool itself, but what can we do if we actually use our own products?)

From the result that we received in a few seconds, we were already quite happy because it showed that users rate the tool well (most gave four or five stars) and will want to use it frequently.

Next, we wanted to visualize what users plan to use the tool for. So, we asked for a quick pie chart and got the result. Again, in a few seconds.

Our survey also had some open questions, for example, “What could we change to make this a must-have product for you?” Not to go through all those hundreds of responses manually, we asked the tool to summarize the answers to this question.

In a few seconds, we got this nice summary of improvement tips from our own users. Tips that are worth the most in our eyes.

As you can see, in around a minute, we got so many insights. If not for the AI Data Analyst, gaining these conversational analytics insights would have taken hours. Long live AI.

Is Conversational Analytics for You?

Conversational analytics can build your customer loyalty and unlock deeper insights, but integrating it into your workflow isn’t as simple as flipping a switch.

Without the right tools or alignment between business and tech teams, issues, like unclear ROI, can appear quite quickly. Whether conversational analytics is the right move for you depends on several factors, like your industry, budget, and team.

To help, we’ve put together a checklist to help you evaluate whether you’re ready or not to leap into the conversational analytics world.

Conversational Analytics Checklist PDF for Download

Here is the Ajelix Conversational Analytics Readiness checklist you can download for free:

Conclusion

Conversational analytics turns everyday interactions into actionable insights, and AI makes the process faster and more efficient. With the right tools, you can better understand your customers and build their loyalty.

Ready to get started? Use our checklist to find out if you’re prepared.

Curious to learn more about AI and analytics? Feel free to explore our blog section and socials.

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