Conversation metrics are quantitative measures used to analyze and assess the quality, effectiveness, and dynamics of spoken interactions in customer calls.

The Conversation Metrics tab is divided into seven tabs showing the interaction your reps have on their calls. See whether team members are spending more time listening or talking, or whether they are asking questions, and so on.

Here you can quickly compare and contrast your current meeting with other meetings or other reps and see how your conversion metrics are fairing against your own prior meeting or from another rep.

The average percentage of all the calls in which the team member spoke. The recommendation is for no more than 65% of the time.

The talk-listen ratio is a metric used to measure the balance between speaking and listening during a conversation, typically in the context of sales calls, meetings, or other professional interactions. It is calculated by comparing the amount of time one person spends talking to the amount of time they spend listening to their conversation partner(s).

A balanced talk-listen ratio is generally considered a positive indicator of effective communication. It shows that the speaker is not dominating the conversation and is allowing the other party to express their thoughts and concerns.

Here's the formula for calculating the talk-listen ratio:

Where:

For example, if the speaker spends 30 minutes talking and the listener spends 15 minutes talking, the talk-listen ratio would be 2:1. This means the speaker is talking twice as much as the listener.

In the context of sales and customer success, an ideal talk-listen ratio might vary, but a commonly recommended ratio is around 1:1, meaning that salespeople should aim to spend roughly equal amounts of time talking and listening during their interactions with clients or prospects. This helps ensure that they understand the customer's needs, concerns, and pain points, and are able to provide appropriate solutions and responses.

The longest Monologue refers to the longest uninterrupted stretch of speech by a single Rep during the meeting. The recommended maximum length is no more than 2m 30s.

In the context of sales and communication analysis, it is often used as a metric to gauge the effectiveness of a conversation, as longer monologues can potentially signal a lack of engagement or an imbalance in the talk-listen ratio.

Here is how the longest monologue is calculated:

Long monologues can be problematic in customer interactions because they might not give prospects or clients enough opportunities to voice their thoughts, concerns, or questions. A more balanced approach, with shorter stretches of speech and active listening, can lead to more productive conversations and a better understanding of the needs and preferences of the prospect/customer.

In practice, it's important to strike a balance between providing information and engaging the listener. Reps should aim to minimize lengthy monologues and instead focus on fostering more interactive and dynamic conversations, which can ultimately lead to better sales outcomes and stronger relationships with clients or prospects.

The longest customer story refers to the lengthiest narrative or anecdote shared by a customer or prospect during the call computed in minutes. The recommended length is between 1 and 2 minutes.

This metric can provide insights into customer engagement, as a longer story may indicate that the customer feels comfortable sharing their experiences and concerns.

To calculate the longest customer story, you can follow a similar process as with the Longest Monologue. However, instead of measuring the lengths of all uninterrupted stretches of speech, you would focus on identifying and measuring the lengths of stories specifically shared by the customer or prospect.

The formula used to compute the longest customer story:

This shows how often the conversation switched back and forth between the Rep and the Customer and is on a 0–10 scale. The recommended grade is 5 or more.

The formula used to compute Interactivity:

Where:

This formula gives you an average number of speaker switches per minute, which can be a useful metric to analyze the dynamics and flow of a conversation. A higher number of speaker switches per minute might indicate a more interactive and engaging conversation, while a lower number could signify that one person is dominating the conversation or that there are long pauses between speaking turns.

This shows how long the Rep waited after the customer completed talking before taking over the conversation. The recommended wait time is between 0.6 and 1 second.

To compute patience, you can calculate the average waiting time between interactions or turns of speech.

The formula used to compute Patience:

However, calculating patience solely based on waiting times may not provide a complete picture. The patience score could factor in not only waiting times but also interruptions, the frequency of back-and-forth interactions, and talk-listen ratios.

This shows how frequently the Rep asked questions during an hour of conversation. It is recommended to ask 18 or more questions.

Formula to compute Rep Question Rate:

Where:

This formula gives you a normalized question rate, allowing you to compare different calls or meetings, regardless of their duration, by showing the average number of questions asked per unit of time (per hour).

This shows how frequently the Prospect asked questions during an hour of conversation.

Formula to compute Rep Question Rate:

Where:

This formula gives you a normalized question rate, allowing you to compare different calls or meetings, regardless of their duration, by showing the average number of questions asked per unit of time (per hour).

You can also add another rep or team's meetings over time and compare the metrics.

The Topic Tracks option gives a detailed view of the topics spoken over time and quickly allows you to compare how another rep may have addressed the meetings. By comparing the Topic Tracks

The topic Breakdown option similarly allows the rep to compare the topics and their sub-topics across multiple meetings.

With these detailed analysis options and state-of-the-art transcription quality, Rafiki provides unsurpassed Conversation Analytics and Intelligence to the user.