Conversational analytics help sales professionals make better business decisions and improve performance. Learn what conversational analytics is and why sales teams need it in today's post.
What is Conversational Analytics?
Conversational analytics (CA) is an advanced software technology that leverages the power of artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to interpret signals in verbal communications. It's mainly used in Sales to derive data insights on prospect or customer behavior. But how does it work?
How it works
To derive data insights, CA applies NLP, AI, and ML technology to record, transcribe, analyze, and identify patterns in communication - turning qualitative data into quantifiable feedback.
In sales, conversational analytics analyzes text and speech communications (e.g., emails, calls, chat bots, etc.) to extract important data patterns between sales and customer/prospect interactions.
CA technology offers professionals the ability to:
- Record and transcribe calls
- Identify keywords in conversations
- Analyze customer sentiment
- Get insights on call duration, speech ratio, and more!
Why do Sales Teams Need Conversational Analytics?
Recalling and analyzing verbal exchanges is something successful sales professionals do every day, but enabling the power of technology unlocks these insights faster, broader, more effectively, and more accurately.
Through conversational analytics, sales teams can save time analyzing customer interactions. And get automatic feedback on prospects or customers:
- Pain points
Overall, this benefits sales professionals tremendously. They can make better business decisions and deliver better results for their team. But how does it apply across different management levels?
Let's take a look case by case.
Sales reps can automate note-taking and stay fully engaged during calls thanks to call recording and transcription. This means they don't have to waste time writing down what prospects are saying, as calls are taped and written down for later accessibility.
Once the call is over, reps can also reduce time analyzing recordings with keyword search, and sentiment analysis features to understand what prospects are saying/feeling about relevant business topics (e.g., product, pricing, etc.) and create appropriate follow-up actions.
Conversational analytics helps sales managers track and improve rep performance more effectively.
For instance, thanks to call recordings and transcriptions, managers can see which selling techniques are performing best to train new hires.
They can also see which agents are following the scripts and average agent-prospect speech ratios to eliminate performance gaps among team members.
Workflow automation and direct feedback after calls help sales teams be more effective and productive. This is excellent news for sales leaders, as it leads to higher revenue and lower agent turnover.
The Future of Conversational Analytics in Sales
Now that the question "What is conversational analytics, and why do sales teams need it?" is answered. Let's take a look at the future of CA solutions.
Today, conversational analytics solutions are being developed to deploy more in-depth data studies.
From root-cause analysis to data extrapolation, conversational analytics software like Thumb is growing in scale to help sales teams and other revenue teams (Product, Marketing, Customer Success, and Customer Support.) boost performance and customer satisfaction.
How Thumb Helps Sales Teams Gain Actionable Insights from Customer Conversations
Thanks to the power of automation and conversational analytics, Thumb turns qualitative customer feedback into visible quantifiable metrics that are valuable to the success of sales and the entire revenue operations.
Thumb's sales intelligence solution helps sales teams capture all customer interactions, track key conversation patterns and gain strategic insights about their product, customers, and competitors.