Measurement Methodology

What is Meeting Score?

Meeting Score provides an overall metric on how well your meeting is going by combining Read’s analysis of Sentiment and Engagement. By analyzing facial and verbal elements of all meeting attendees, Read assesses how people are reacting (positively, neutrally or negatively) as well as their level of involvement and interest in real time. This provides all meeting attendees with a scientific measure of the meeting’s effectiveness so you can drive to a better meeting experience together.

What is Sentiment and how is it measured?

Sentiment measures how positively or negatively attendees are feeling throughout a meeting. Read analyzes both facial and verbal cues from attendees to determine whether they are expressing positive, neutral or negative reactions to the meeting in real time. For example, if you are presenting a slide to a large group and can’t see the facial expressions of all meeting attendees, Read can detect that people are smiling and nodding their heads. Sentiment levels will begin to increase, indicating to you that your audience is reacting positively to your content.

Read uses well-established methodologies and proprietary models to analyze facial and verbal elements, such as facial expressions, head movements and body language, as well as the pitch, volume and intonation of attendees’ speech. Read also analyzes the overall content of the speech (for example, if people are using positive or negative words and phrases) with natural language processing (NLP), a type of machine learning that allows computers to understand the meaning behind human language.

What is Engagement and how is it measured?

Engagement is a measure of attendees’ level of involvement and interest in a meeting. We measure engagement through a combination of facial and verbal cues, as well as the talk time of attendees throughout the meeting, to assess whether engagement levels are high, medium or low in real time. For example, if you are in a team meeting and people start to get distracted, Read will notice that they are looking away and leaning back from the screen. Engagement levels will begin to decrease, indicating to all meeting participants to refocus on the meeting.

Read uses well-established methodologies and proprietary models to analyze facial and verbal elements, such as facial expressions, head movements and body language, as well as the pitch, volume and intonation of participants’ speech. The proportional talk time is also considered. Finally, Read analyzes the overall content of the speech (for example, if people are using positive or negative words and phrases) with natural language processing (NLP), a type of machine learning that allows computers to understand the meaning behind human language.