Conversation Analytics Definition:
Conversation Analytics is a sophisticated technology that works on driving insights from a phone conversation between two people. It usually makes use of digital call recordings, transcribes it and uses Machine Learning or Keyword spotting to find trends in the transcripts.
These trends include engagement metrics like Talk to listen ratio, the Average number of questions asked, monologues etc. Conversation Analytics can give qualitative insights about conversations that were never possible before. It enhances the lives of Quality Assurance professionals who don’t have to rely on techniques like call sampling to reviewing the performance of reps.
How is Conversation Analytics beneficial for businesses?
Bottom of the Sales funnel is the moment of truth. Conversations between sales rep and customer are a storehouse of wealth of information.
These conversations contain clues to unravel the mystery of why deals are won or lost. The key to unlock this potential is Conversation Analytics.
While conversations between buyer and seller have always been happening, it is the growth of digital businesses that has led to the increase in availability of digital conversations.
Revenue related functions like Sales and Marketing are generating digital conversations. Even retention teams are using Inside Sales function and Digital Engagement tools to reduce churn and expand revenues.
Digital marketing uses Chatbots, Live Chat, and Contact Centres to generate Marketing Qualified Leads which are then passed on to Sales. Digital Sales teams use multiple channels like Email, Voice and Video calls to close a deal. Conversations happening across these text, voice and video-based channels are stored digitally and can be accessed by analytics engines.
Recent advances in data sciences, as well as technologies such as natural language processing and automated speech recognition, have opened up the possibility of analyzing conversations as humans do.
For text-based channels like Chat and Email, conversations are directly fed into the analytics engine. While voice-based channels require ASR to first convert speech to text. In addition to that, voice and video analytics can also be used to gain insights like Tone and Emotion.
Conversation Analytics for Sales
Conversation analytics can be used for Sales Conversion Optimisation. It can help in identifying and prioritizing opportunities by picking up intent clues from customer conversations. Another use of it is to develop a personalized rep coaching plan by analyzing rep-customer interactions and identifying areas of improvement.
CRMs don’t fully capture the reasons behind a deal’s win or loss. The details are hidden in conversations a Sales rep has with a customer. Conversation Analytics uses ML to uncover the critical elements of winning sales calls. Sales leaders can use it to get a feel of the market by mining customer conversations for signals on competitors, products and pricing.
Conversation Analytics enables you to:
- Identify the hot leads within seconds.
- Search for any pricing discussions.
- Search for competitor mentions.
- Identify rogue conversations easily.
- Get an overview of every rep’s performance.
- Know what works best for your Sales.
With the rise of digital businesses and Inside Sales, we are seeing an expansion of SalesTech beyond CRM. New categories of tools like Sales analytics, automation, acceleration, enablement, engagement, and intelligence have come up. Under Sales Analytics, the upcoming field of Conversation Analytics promises to help Sales teams win more deals and maximize conversion.