Learn how conversational analytics can help businesses understand their customer base, gather valuable insights, and improve overall customer experience through AI-powered machine learning.
Conversational analytics is a trending form of market research that helps businesses gather granular insights about their customers’ behavior, motivations, and desired outcomes.
But what exactly is it and can it have a positive impact on how businesses make decisions moving forward? Read on to find out and learn:
Let’s switch on our AI machines and dive in.
The term is a mouthful but the concept is straightforward. Conversational analytics is about evaluating customer conversations through the use of AI and deriving actionable data in the process.
Customer interactions by telephone, chats, reviews and even social media mentions can be used to gather nuanced insights about your customer base that would otherwise be difficult or impossible to obtain.
Conversational analytics uses artificial intelligence (AI) and machine learning to do natural language processing (NLP), which basically means getting computers to understand and make sense of speech like humans do.
The technology behind conversational analytics can be applied to do live transcribing and analysis of phone calls, chats, reviews, and other areas of written or verbal interaction to get insights into how your customers react with and perceive your brand.
Similar to how companies continuously evaluate their customer service, conversational analytics allows businesses to learn from customer interactions and answer complex questions such as:
By analyzing customer conversations, you can identify patterns in the buyer’s journey and make informed decisions with data-backed feedback.
From driving sales to improving your product, here are the main ways companies can benefit from conversational analytics.
Sales teams that operate by phone constantly review and assess their calls. But with the help of AI, calls can be analyzed in real-time to identify certain patterns across conversations.
For example, if certain points frequently come up in conversations, conversational analytics software can inform sales teams about these patterns and help them better prepare and improve.
Examples of such patterns are:
And so on. The more actionable insights you have, the easier it is to improve your sales process and address customer concerns in ways that drive sales.
By analyzing customer speech and text interactions with AI-powered machine learning, companies can get an understanding of the customer experience and how it can be improved.
Analytics tools give businesses a competitive advantage and help them understand:
This wealth of data helps point businesses in the right direction to easily make informed decisions on what channels to focus on and what needs tweaking.
Conversational analytics lets you gain customer feedback without asking for it through surveys or questionnaires. This helps lessen interruptions in the buyer’s journey for an overall smoother process.
When addressing churn rates (the rate at which customers no longer want to do business with a brand), companies can analyze and look for patterns in the events that eventually led to a customer leaving.
If there is a common trend, companies can easily identify and potentially resolve the issues that lead to churn rates.
Customer service and quality control often go hand in hand. But with conversational analytics, you can quickly spot what customer frustrations and pain points arise from all channels of interaction and act accordingly.
For example, keyword terms and phrases such as: “I wish there was an XYZ feature,” or “You should add a so and so button,” can be automatically tagged and noted for product design and development.
Any industry with customer interaction can benefit from conversational analytics. From healthcare to retail to customer service, AI-powered algorithms can help extract valuable data at scale.
Popular airline company JetBlue uses multiple AI integrations to streamline its operations, including conversational analytics. Across JetBlue contact centers, customer sentiment was analyzed to create a list of pop-up scripts and instructions based on customer inquiries.
In another instance, when running a promotional campaign that included free baggage, conversational analytics helped pick up that the vast majority of passengers did not consider this offer reason enough to fly with JetBlue. As a result, JetBlue readjusted its promotional offer to one that was much better received by customers.
While these changes may seem small, they result in a significant overall impact on the customer experience and sales processes. It’s these simple tweaks that can make all the difference for a company and put it far ahead of competition.
Conversational analytics helps teams and businesses leverage customer communication in new ways to gain valuable insights. Any industry with regular customer interactions can use AI to make data-backed decisions to improve how customers interact with brands.
The key highlights of conversational analytics are: