AI Will Help Us With The ‘Why’ Of Engagement Rates

What are the most important contributions that artificial intelligence will make to businesses?

Ask ten people and you will get ten different answers. But sometimes we get an idea of ​​how it’s going to work, thanks to presentations from people who have been at the forefront of the process for years.

A story of innovation

One of those people is Ed Baker. He began his studies in the late 1990s at Harvard and completed his graduate studies at Stanford. He worked at Facebook, then Uber, then on something called Whoop, a fitness app. He launched Friend.ly and Datesite.com, as well as an app where people could “send hotness” to rate their friends and classmates.

Along the way, he learned a lot about engagement and conversion, and what he calls the “viral loop.”

In a recent TED talk, Baker reviewed some of his creations during his college years, mostly consisting of dating sites and social apps (see below).

Certain indicators, he pointed out, can show stakeholders more about how their inventions are attracting the attention of an audience. There is the K factor and detailed lifecycle activity analysis showing how many users convert to secondary engagements.

Businesses, in turn, can use this data to achieve better results in delivering and selling products and services.

Trial and error and cultural trends

As Baker described how to measure customer engagement, he gave us two examples of business decisions that took a mediocre result and converted it into more significant success.

The first concerns Facebook’s Japanese audience, where he said people simply aren’t inviting each other to join.

When they looked into it, they discovered that Japanese culture had a stigma around invitations. So, as he pointed out, they changed the copy and engagement exploded.

The second example concerns Uber’s operations in India, showing that users did not want to enter their credit card information. When Uber changed the form to allow cash rides, the numbers increased significantly.

Artificial intelligence analysis can help

What does this have to do with AI?

Well, without concentrated human decisions and the resulting research and exploration, these successes would not have been implemented. Someone had to figure out why people weren’t converting and experiment with solutions. Artificial intelligence, on the other hand, can do this without any human intervention.

Programs of the future will be able to make all of these adjustments, keep trying new things, new angles and approaches, and figure out which one is most effective. He may not have the same inhibitions as humans, as in the case of the CEO of Uber, who Baker said at the end of a successful bet said, “I hate you guys, and I love you guys,” referring to the team. brave.

With AI, there will be no barriers to go out and try new things.

In fact, you could argue that companies have been doing this for years, in the form of A/B testing. A/B testing, in which marketers take two different outcomes and measure their success, encourages this type of exploration in a way that hasn’t been articulated before.

In other words, A/B testing brings a level of sophistication to contact marketing.

AI will do the same across all industries and at all levels of business. This will change the situation in a significant and profound way. And this has to do with Baker’s explanation of engagement, that it is based on complex factors and trends in human behavior. We don’t need to be experts in focus groups if we have AI to figure it all out for us. We just need to know how to use the tools and then we can sit back and watch them work their magic.