How does conversation intelligence work?
In order to extract data-driven insights from interactions between sales professionals and consumers, conversation intelligence is software that employs artificial intelligence (AI) to analyze speech or text. For real-time decision-making, the conversation data from various platforms is transmitted between CRMs, ad platforms, data analytics and attribution systems, and digital experience platforms. To enhance the shopping experience, boost conversions, and eventually generate revenue, it is utilized by revenue teams in marketing, sales, customer experience, and eCommerce.
What distinguishes conversation intelligence from call tracking software?
Yes. The complete system, known as conversation intelligence, enables revenue-generating teams in marketing, sales, customer experience, and eCommerce to comprehend each call’s motives, including the intent, results, sentiment, and decisions made, and to act on that information in real time. Call monitoring, conversation analytics, and integrations are among the tools included in the conversation intelligence system.
Another component of the system that is utilized to gather data from the discussions you have with clients is conversation analytics, often known as conversational AI. How this functions is explained below.
You can automate and respond to conversation data in other platforms thanks to integrations with other technologies that allow conversation data to be streamed back and forth. For instance, you could send conversion data to Google Ads or import website user experience data from a UX platform like Quantum Metric.
How Can Conversation Intelligence Record, Transcribe, and Analyze Conversations Using AI?
Platforms for conversation intelligence mine conversations for information using conversational AI or conversation analytics. Using natural language processing (NLP) to help computers “understand” speech and artificial intelligence (AI) to extract and organize data from it, conversation analytics is the process of obtaining useful data from human speech and conversation. In order for the algorithm to analyze voice, it must first be recorded and then translated into text using NLP. This allows the AI to interpret the speech, spot patterns, and categorize the data as the user specifies.
That is a lot of alphabet soup, I suppose. It basically comes down to giving computers the ability to interpret speech and enabling people to draw conclusions from enormous volumes of talks at scale. Up until a few years ago, both of these tasks were challenging, if not impossible.
AI is used to organize the data that natural language processing extracts from human speech and take appropriate action. Using conversational analytics, data may be gathered and processed from both spoken and typed speech, such as during phone calls and voice assistants (e.g. customer service chatbots). Although there are many uses, in this article we will concentrate on how marketing, sales, customer experience, and eCommerce teams use Invoca’s conversation intelligence product.
How might the platform’s findings influence a sales, marketing, or customer experience strategy?
There is no better source of truth than the voice of the customer themselves when you’re attempting to understand the core of your customers’ motivations and demands. To determine what works and what doesn’t, revenue teams have traditionally had to rely on digital statistics like click-through, abandonment, and bounce rates. Even while those measures are significant, they only make up a small part of the whole.
When you speak with your customers, they will express their particular needs, the reason they phoned in the first place, and what will eventually motivate them to make a purchase. None of these measures can compare to the breadth of information that customer conversations provide, including post-call surveys, NPS, and click data. The challenge has been having widespread access to those interactions. The only people who truly understand what is going on are typically sales representatives, who are unable to inform other teams because they are stuck in the call center. They couldn’t do it quickly or accurately enough, even if they could.
For teams in marketing, sales, customer experience, and eCommerce, consider how conversation intelligence functions.
To determine their true acquisition costs, optimize digital efforts, and personalize digital touchpoints, marketing teams employ conversation intelligence to link purchases and other conversions made over the phone to specific digital campaigns.
In order to keep more buying journeys entirely digital from beginning to end, e-commerce teams employ conversation intelligence to build a data-driven feedback loop as escalations occur. They also use the insight to improve e-commerce and conversion flows.
Conversation intelligence is used in customer experience to obtain visibility into the full end-to-end purchasing journey, which includes both digital clicks and human-to-human talks. This reveals points of friction in the purchasing process, equips CX teams with revenue-focused insights to drive top-line development, and fosters the growth of stronger relationships between brands and their target audiences.
Additionally, sales teams can use conversation intelligence to learn which agents are functioning at their peak levels as opposed to those who might benefit from coaching and criticism. As a result, the team becomes more efficient and productive overall, increasing sales and reducing agent churn.
Nearly all revenue-generating teams at B2C organizations have the opportunity to deploy conversation intelligence tools, which also sheds light on a contact center blind spot that has long bothered these teams. “There is still a significant gap between what marketing knows about customers and the insights produced in the contact center in the majority of firms. Customers end up having fragmented experiences, and organizations miss out on opportunities as a result, according to Nicole France, VP and Principal Analyst at Constellation Research. “A big opportunity exists in being able to precisely identify consumer demands and priorities—from their own words—and apply them across teams. An essential tool for enhancing the customer experience and achieving company goals is conversation intelligence.