Rafiki tracks numerous metrics, data and provides revenue driving intelligence by highlighting the topics that drive customer behavior (Customer Intelligence), spotting risks and opportunities (Opportunity Intelligence) and recommends the various ways to level set the performance of the reps by helping the leader to replicate the best reps (Organization Intelligence)
These metrics and data points are spread across multiples under the Analytics Menu.
First the Meeting Stats gives a quick snapshot of the Weekly/Total Meeting Volume and the Average Minutes taken by each Rep
Then Rafiki tracks seven key interaction metrics (selected from prior studies from academia such as Harvard University and others, on what constitutes successful customer conversation):
Talk-Listen Ratio – This metric measures the average amount of time spoken by each team member across all calls. Per a Harvard University Study on conversation metrics, this recommendation be between 40-60% of the meeting time.
Longest Monologue – This is longest talk made by a team member in a meeting. It is recommended that the maximum length be no more than 2.5 Minutes
Longest Customer’s Story – This is the longest time when the customer talks in a minute. The recommended length is same as the longest monologue that is around 2.5 Minutes.
Interactivity – This measures how often the conversation switched back and forth from customer and a sales rep. This is on a scale of 0-10 and the recommended score is between 5-10.
Patience - After the customer completed talking, the rep takes this long before taking over the conversation. The recommended wait time is between 0.5 and 1 second.
Rep Question Rate - This shows how frequently the team member asked questions during an hour of conversation. It is recommended to ask 18 or more questions
Prospect Question Rate - This shows how frequently the prospect asked questions during an hour of conversation.
These metrics are shown for the meetings filtered across the filter criteria.
Topic & Tracker Stats:
Rafiki's AI technology not only transcribes and maps the speakers to the right transcription at a top tier industry quality, but also maps those what was spoken into meaningful sales, marketing and conversational topics that sheds light on, how they impact revenue.
By measuring what was spoken by whom and when, across multiple sales reps, one can use this as a signature for replicable behavior. For example, by measuring the average time spent across a set of meetings by a rep or a team and comparing that against a successful sales exec/team, one can get additional clues about shaping their future conversation.
Once you get a glance of the reps that talk about a certain topic, you can dive deeper into a rep specific topic track behavior. This shows the typical time spent per topic by that rep when compared to the average. If there is a struggling rep, this type of conversational analysis can guide them to focus on the topics that matter to the customer. (especially when filtered on the topics identified as being impactful)
The same sort of analytics are available for Customer/User created Trackers as well. This extensibility and application of Rafiki's powerful AI to customer and industry specific use cases, provides significant customization and analytics that can then be downloaded or integrated with the customer's backend Business Intelligence platforms or Sales Ops.