Conversational Analytics: Use Cases and Examples

Artificial Intelligence
Jul 10, 2023
Conversational Analytics: Use Cases and Examples

Imagine you work for a software company. Your platform serves over 10,000 users, and they all interact with your team in different ways. Sales and success teams have video calls daily. Marketing monitors social media replies and online reviews. Support handles dozens of emails and tickets each day.

In all these conversations hide opportunities to improve your business, and create a happier, loyal customer base. But how do you approach that overwhelming amount of data? The answer is conversational analytics. In this article, you’ll learn what it is, the common use cases, and how to get started analyzing your customer interactions. 

What is conversational analytics?

Conversational analytics is the process of analyzing customer conversations. It uses artificial intelligence techniques and machine learning algorithms to human conversations into data points. More specifically, Natural Language Processing (NLP) techniques are typically used.

Customer conversations can take shape in multiple formats. But usually, nlp will be applied to a digital context:

  • Transcription of phone calls, e.g. in call centers
  • Social media interactions
  • Online customer reviews
  • Customer support interactions, e.g. emails
  • Chatbot conversations
  • Messaging apps

Conversational data gives companies better insights into customer behavior. It helps them understand what their customers are saying, how they are saying it, and why.

Example of insights from conversational analytics

Benefits of conversational analytics

With conversational analytics, companies can extract meaningful information from conversations. These customer insights will help you make data-driven decisions on many different fronts.

  • Predicting customer behavior: understand how your customers talk about their needs and problems, so you can better tailor your offering to what they really need.
  • Improving customer experience: when you know what customers like and dislike about your business, you can take action in real-time to improve their experience.
  • Reducing churn: identify imminent risks, and tackle them immediately to boost customer satisfaction and retention.
  • Improve business processes: identify recurring needs or problems in your business, and find ways of automation to save time and resources.

Analyzing conversations one by one will cost you days - or weeks - of manual work. By using AI and machine learning techniques, it now only takes a few minutes. Businesses get meaningful insights about their customers faster, at a lower cost.

For example, let’s say you run a SaaS business selling CRM software. By analyzing customer conversations at scale, you can understand which features your product users like and dislike, which you can use to drive your product roadmap.

Or you could immediately grasp the most frequently asked questions across thousands of support tickets. Create knowledge base articles or webinars to answer them, and prompt those articles to customers via chatbots. If you want to go all out, Attrock explored some of the best AI chatbots that smart brands and marketers use to optimize customer experience. That way, your support team can spend more time on complex problems.

Use cases of conversational analytics

Thanks to artificial intelligence, businesses can gain conversational intelligence on many fronts. Let’s look at some common use cases.

Improving customer experience and support

Online customer feedback can uncover pain points across your entire customer journey. By analyzing that customer data in bulk, you can identify recurring complaints and praise. With that information, you can provide better support, and work on the things that will improve customer experience.

Sentiment analysis

With conversational analytics, you can analyze the customer sentiment behind customer interactions at scale. Whether it’s support emails, online reviews or phone calls. For example, contact centers can analyze how satisfied clients are with the provided service of each agent, and track agent performance to optimize their operations.

Product roadmap

Customer conversations can reveal a lot of opportunities to improve your product or services. You will get a birds-eye view on which functionalities your users love, or which ones are missing. That information can steer your future product roadmap. Or even influence your pricing strategy. 

For example, a project management software offers its users reports with time-tracking metrics and an overview of the most profitable projects. If customers frequently mention this feature online and ask for more insights, you can lock additional reporting functionalities behind higher pricing tiers or sell them as add-ons to drive upsell.

Predictive analytics

A customer’s language hides a lot of unspoken truths. Revealing hidden frustrations or understanding how customers talk during specific touchpoints will help you react better in the future.

Let’s say you’re planning to launch a new campaign targeting feature in your marketing automation software. If your customers are currently complaining about the lack of filtering options, this is something you will not want to let go unnoticed when developing this new product feature.

Market research

Besides specific user feedback, customer touchpoints can be a great source to find out what’s generally on your customer’s mind. Therefore, social media posts or online reviews can uncover new market trends. These trends can help give direction to your company’s vision, product direction or marketing strategy.

How to analyze conversational data

Conversational analytics pulls text from different data sources, and uses natural language processing to turn it into data points. But still, you will need to analyze that data and turn it into actionable insights.

Using an analytics dashboard, you can combine all your metrics and KPIs in one or more visually understandable dashboards. You may need to hook up your conversational analytics to your favorite business intelligence tool through an API.

Example of a sentiment analysis dashboard on tweets

Examples of conversational analytics tools

Besides typical customer and marketing intelligence software, you can use multiple types of software to help you along the conversational analytics process. Below are just a few examples.Below are just a few examples.

  • Speech analytics: tools like CallMiner or Google’s speech-to-text convert voice interactions - like video calls or voice messages - to text and identify patterns, sentiment or keywords through different algorithms.
  • Generative AI: conversational AI tools like ChatGPT can help you find patterns in text snippets, or analyze large text datasets at scale with the underlying language models like GPT-4.
  • Business intelligence: tools like Tableau or Power BI help you visualize all your conversational data in concise reports for a high-level view on your customer data.
  • Embedded analytics: tools like Luzmo go one step further, and even let you embed visual dashboards into your own software application to share conversational insights at scale.
  • Text analytics: tools like MonkeyLearn use artificial intelligence to clean, label and visualize customer feedback.

Equipped with these tools, you can carry out conversational analysis more easily, and ultimately make better business decisions.

Getting started with conversational analytics

Analyzing customer feedback at scale is one of the most overlooked things you can do to grow your business. And for those who want to do it, it’s often an overwhelming task. Luckily, new AI technologies are making conversational analytics more accessible for many businesses out there.

But even if you’re equipped with the most powerful AI tools, you’ll still need to visualize all of that information in interactive, value-adding reports to make smart decisions with ease.

With Luzmo’s self-service dashboard editor, you can drag and drop dashboards together in days, not weeks. Embed them into your software application or customer-facing portal to deliver conversational analytics to all your product users in no time.

Sign up for a free trial, or get a guided tour from one of our product experts today!

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