AI for Video Coaching: 3 Practical Applications

June 21, 2018 | Lauren Boutwell
AI for Video Coaching: 3 Practical Applications

Companies across industries have started to adopt artificial intelligence (AI) to supplement and augment the work of humans. The technology is being used for everything from predicting the winner of the 2018 World Cup to communicating with customers at TGI Friday’s restaurants to scanning resumes at Accenture.

Sales organizations are becoming a significant adopter of AI. In fact, Gartner reports that by 2020, 30% of all B2B companies will employ AI to augment at least one of their primary sales processes.

Jim Dickie, co-founder of CSO Insights, described the benefits and efficiencies of AI in a 2018 blog:

“AI will alleviate the tedium of data entry, prospect research and pipeline/sales funnel reporting/forecasting. At the same time, AI will provide new levels of insight into buyers, their interests and proclivities. Selling energy will shift to ingenuity/insight, and away from tedium. Sellers will be required to develop higher emotional quotients (EQ) for elevated relationships and ingenuity quotient (IQ) for higher value-add.”

This value for sales teams can now also extend to video coaching. At Brainshark, for example, we recently released our AI-powered Machine Analysis engine. Now, before a sales manager reviews a video coaching submission, Brainshark can automatically generate actionable insights into a reps’ coverage of key topics, emotions exhibited, and other performance metrics, as well as auto-scores for each video.  

How can this form of AI help your reps and managers when it comes to video coaching? Check out these 3 practical applications.

1. Take some of the heat off sales managers

Sales managers have a lot on their plate and coaching tends to be one of the first things neglected when they’re strapped for time, especially when dealing with a large sales force.

Let’s say you are sending out a video coaching activity to 30 reps. An AI application can automatically score the responses to the activity based on parameters that you set. Having the machine do some of this scoring for you makes it a lot easier (and quicker) to distinguish which reps hit the mark and which may need more help, allowing you to better prioritize your coaching time.

Not only does this type of AI application ease time management challenges, but it can also help you develop benchmarks of what ‘good’ looks like.

2. Provide better, more consistent feedback

Sales managers are human; they can be biased and subjective without meaning to be. Using an AI application with video coaching can help make coaching feedback more useful and consistent for reps.

After a rep submits a video coaching activity, the machine can deliver an automatically generated score – again, before a manager reviews the submission. The advantage? Reps can see, without bias, metrics on their performance and nuances in their pitch that a manager might miss. They can also identify areas they need to fix much quicker.

If the rep misses the mark? The reps have a practice environment via the video coaching solution so they can work on skills multiple times, until they are ready for that buyer conversation. This is a better option then having reps ‘practice’ on buyers – they should be ready long before that.

3. Help reps keep emotions in check

Video coaching exercises can measure a lot of things for reps, such as effectiveness in delivering a pitch, ability to communicate value propositions, and more. What a rep says is (obviously) very important. But what about how they say it?

An AI application has the ability to analyze videos – on a frame-by-frame basis – for personality and emotional insights that often go undetected by humans. For example, when delivering a message, is a seller coming off as happy, or contemptuous? Are they perceived as open or introverted?

Getting feedback in these areas can help reps understand how their delivery of words can convey their personality and in turn, affect a buyer conversation.

For more information on Brainshark’s new Machine Analysis engine, check out this short presentation or contact us for additional questions.

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