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We used our own product for Sales Conversation Analytics

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The Team at CallMiner

August 05, 2021

Project Ice cream SCA

The positive impact reverberated throughout the company…

In early 2020, CallMiner underwent a two-part initiative to gain better company-wide insight. Firstly, we wanted to have a first-hand understanding of what it is like to launch a ground-up program using our software. Secondly, we had many new sales representatives that not only needed to undergo an initial training, but also be coached throughout their growth with the company. We had seen how our clients have used CallMiner’s solution suite to acquire insights far beyond the compliance-level in their contact centers and knew we already had the necessary components for successful a Sales Conversation Analytics solution within our system.

This is how Project Ice Cream was born, named after a kid-friendly take on "we drink our own champagne."

The goal of the project was for the whole CallMiner team to have a better understanding of the aspects of business and data that inform our use cases and be able to lean on each other’s respective strengths to improve the experience. By mid-February 2020, we were mining our sales conversations, augmenting them with crucial metadata, and delivering digestible and coachable insights to our business development representatives.

Within the first day of deploying our instance, we had already found an important insight:

"In reviewing our first call in the CallMiner Eureka platform with the team in Waltham, we discovered a lead talking about our nearest competitor in the real-time space. The BDR did a decent job contrasting our solution against an installed solution and secured a demo. The insight is that there was a TON of competitive marketing information in the call for marketing to build on. Competitive mentions are one of the use cases Eureka is built for (marketing intelligence) and on the first day, boom, we get a hit. Awesome!" - Mike Dwyer, VP of Research

For those following the timeline, this is about where COVID surged, and every organization had to rapidly switch to remote work. The importance of email and chat interactions also increased, and we realized we’d have to mine more than just Ring Central interactions if we wanted to continue getting valuable insights from CallMiner.

During initial discussions, we talked about emails/chats as a 'down the road' future development. Now with the potential of more email vs. call due to the time, we had to move it to the forefront. The various contact types merged seamlessly with the call transcripts to create a bigger picture of the business development and sales journey and allowed our initiative to keep up with the times.

Now, over a year later, we reached out to some of the people who saw first-hand how Sales Conversation Analytics could increase their own capabilities. Here are some of the responses!

Justin, a member of the business development team, found that Sales Conversation Analytics created a simple way to bubble up what was working across the whole team, and design a unique yet successful unscripted approach for each team member:

"The main things that I was looking for were how specific approaches, rebuttals, and competitor mentions could impact the conversation. By looking at openings, we could see which opening consistently led to longer calls. With rebuttals, we looked at which rebuttal to which objection would lead to a longer call and would lead to more information gathered. Competitor mentions allowed us to understand which competitors seemed to have a larger market presence and so letting us know which battlecards we needed to study more. We also looked at the closing statements of our BDRs to find which BDRs were doing the correct steps to set up a next steps conversation, and by seeing who did what, we could coach to get the best habits across the entire team.” - Justin Joss, Business Development Representative

Bryan, a valued business analyst with CallMiner, was able to harvest the analytics from the system to uncover and monitor big picture insights to support company-wide initiatives:

"Drink our own champagne. That’s the mindset we went with when we started Project Ice Cream. We wanted to get a better understanding of what customers deal with, as well as gain insight into our own processes. As business analysts, we are at the end of that stream. We receive the output of the work that had been done throughout implementation and that harvested data is the tool you need to do your job. We were able to customize that data to match the initiatives we were supporting, like the correlations between objections and objection busters, as well as the flow of a deal through contacts and touches. When insights are uncovered, we can easily transfer those insights to actions that can then be monitored and visualized over time." - Bryan Tice, Business Analyst

The data science team at CallMiner Research Labs also reaped the benefits of the harvested data, using it as part of their data lake for machine learning and AI initiatives:

"So much of what we do revolves around extracting features from data to use as input to our machine learning models. For example, if we want to use machine learning to evaluate potential deals, and we think competitor mentions would provide value, someone would have to annotate all of those mentions. Instead, we can extract the data from Eureka using the API and use that as input to state-of-the-art natural language processing approaches. The work already being done by those close to the system greatly expands our potential feature store with minimal additional effort." - Kirsten Stallings, Lead Data Scientist, CallMiner Research Lab

As insights became action and that action saw ROI, the value was felt farther up from the analytics trenches, by stakeholders and members of the executive team as well.

"As VP of Research, it was exciting to be able to see how our product was affecting an organization, from the inside out. Having an under-the-hood perspective on the data flowing through Eureka, allowed us to see where bottlenecks and monkey wrenches might occur, and we took those learnings back into the product for our customers' benefit. It was a lot like being a mechanic, but able to work on your own car first." - Mike Dwyer, VP of Research

"The value I derive is from the data and the insights that it provides. The questions I am looking to answer are "Are we effective?", "What are prospects and potential customers looking for?", "How does our current offer shape the interaction and what are we missing?" and "What are the unexpected use cases of new markets we are uncovering?". I use CallMiner Analyze to dig through trends and calls to uncover them, which feeds our analytics and strategy efforts." - Rick Britt, VP of AI, CallMiner Research Labs

We found value in using our own CallMiner software for Sales Conversation Analytics. And with the announcement of a new solution within the CallMiner Eureka platform just a few weeks ago, it gets easier.

With CallMiner Sales Conversation Analytics, enterprise and business development sales teams gain real-time and post-interaction intelligence in an easy-to-use, customizable dashboard. Building on existing capabilities found in CallMiner’s Analyze and Coach products, CallMiner Sales Conversation Analytics enables sales executives, directors and supervisors to identify and scale best practices, uncover and act on coaching opportunities, and gain visibility into pipeline health. We hope you enjoy our champagne (and ice cream).

Learn more about CallMiner Sales Conversation Analytics here and here.

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Whitepaper

Forrester New Tech: Conversational Intelligence for B2B Revenue, Q3, 2021

Learn how to use conversational intelligence to improve B2B sales