Every call on Jargon is recorded, transcribed and analyzed. It's this last part we're going to focus on in this quick reference guide. The summary we generate from each report contains loads of interesting information, but it can be daunting to look at for the first time. Here's a quick guide!

Sample Report

If you'd like, you can check out the source report for these pictures at https://www.jargon.ai/flash-report/sample.

As you can see, right after the title of the call, date and duration, you get some beautiful gauges and information. We've roughly split the data into two sections - Conversation Summary and Participants Summary. The first describes the overall flow of the conversation, and the second how each person behaved during the call. 

Conversation Summary

Vocabulary Score
We use the transcript we generated to score the level of vocabulary used during the discussion. This is a rough guide based on sentence length, complexity of the words and a few other factors. Conversations that are too academic or complex tend to score lower in retention and make information transfer harder. This is useful for helping coach your team on how to keep things simple.

Smiles per Hour
This is a fun metric that gauges how often people are smiling. Depending on familiarity, mood and context, you can use this as a proxy for how people were feeling on the call. 

Empathy Score
Based on the idea of Linguistic Style Matching, which says that matching speaking styles and pronoun usage tend to be a realiable proxy for being "in sync" with another person. Our “Empathy Score” is a great indicator of how well a conversation flowed, and it can have a big impact on perceived quality, satisfaction and sales outcomes. 

Participant Summary

We gather data at the participant level, so each person who joined the call will get their own line in this table. Here's a close-up of John, who was the owner of this call.

Tags
We tag participants based on how they behaved during the call. You may notice that John, in the picture above, was tagged as an "Interruptor." Based on our metrics, he interrupted Priya more than usual for a call of this length. Something to watch out for. He also got tagged as "charming," which indicates he caused Priya to smile more than a few times. Good for you, John!

Words per Minute
Pretty self-explanatory, but speaking too quickly can cause you to lose people, especially non-native speakers. It can also alienate those who don't know you very well. We highlight those who fall outside the average range with a badge, like the one Priya was awarded for her rapid-fire 176 WPM rate of speech!

Talk Time
Talk time is a great way to manage yourself and see if you're leaving enough time for the people around you depending on your use case. For example, effective sales people allow their prospects to do the talking, and find success when they have a talk time of ~40%. If you're pitching an investor, on the other hand, we expect you do to most of the talking. This is a great tool in context.

Sentiment
Sentiment tracks the positivity of the words you're using, which can affect your perception as a persuasive communicator. It's important to remain positive if you plan on communicating any kind of plan, projections or future-looking statements.

Engagement
This is a raw measure of how engaged each participant seemed during the conversation. Were they making eye contact, were they looking at the screen, did they click away to read emails for half the call? Depending on who they are and the context, this is a wonderful metric to keep track of. 

Conclusion

Jargon tracks a ton of information during the calls. How you use that information is up to you and depends on your role, but metrics matter! What do you think we should be sharing? Any suggestions are welcome at support@jargon.ai.

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