Using AI for
the perfect pitch

Question: What about fake emotions? How do you deal with them?

Answer: Though the Facial Coding could distinguish between different kind of smiles, our algorithm currently doesn't. At the moment, we detect every smile as a positive emotion. But when you are smiling sarcastically then someone mostly reacts with a frown. You can spot this emotional change in our emotion graph.

Question: Do you incorporate emotions from previous frames, or is each frame treated individually?

Answer: For us, each frame is treated individually in the analysis. But when we calculate our KPIs, or display our graph we use the moving average. So you always have the last 5 to 20 seconds considered. That means we capture drag on the emotions.

Question: What was the average time delay of emotion adjustment between one person to another?

Answer: It really depends on the people. Sometimes you see that people are really reflective of this. When they see somebody is smiling, their own emotions instantly go up. And sometimes there is a little lag, cause people need to process this.

Question: Do you actively use Mataono for own meetings and what has changed?

Answer: For me, the perception of a pitch improved. Now, I better understand the concept of emotional selling. And how important it is to draw attention by emotionally include the audience. When I draft a pitch I try to get as much as possible content in that evoke a high range of emotions.