Our algorithm enables the streaming platforms to interact with their users based on their semantic profile and adopt their offerings around the content that matters most to the users and their emotions.
We are a content recommendation platform that helps the streaming platforms which offer music and video content, to personalise their content based on the user’s mood.
Now, you can detect your user’s emotions in real time through our platform which is backed by AI and deep learning. Our algorithm helps you understand user’s emotions offer them the content fits their emotional statement and they surely want to buy.
A better offer, less waste!
One of the major challenges of music and video streamer platforms is the best way to optimize their offering and curate millions of content they have on their platform.
Most of the platforms use regular approach like categorizing products e.g. ‘Genre’, ‘Artists’, ’Popular’, etc. Therefore, many products do not get enough chances to be shown up and they always look for every new tool of product offering.
Through humanized data based on user’s emotions, we help other platforms provide meaningful and more accurate recommendations to their users, not only by old methods like keywords, demographics, etc. It brings:
The figure below depicts the growth of a music streaming platform (Spotify), during our pilot test. Notice the increase in upsell and the reduce in bounce rate. We offered Kabbex to 2000 users, and, this was done in only a 30 day period including 10 days of observation with a team of 2 people.
The figure above is gist of an academic research that investigated that how emotions will affect the shopping decisions and vice versa. As you may see, surprisingly, 62% of people buy things to repair their mood. The research published in the journal of Psychology and Marketing. The research has been conducted in the United States with 407 participants in series of studies in 2011.
You can achieve your content monetization targets, if you personalize your content based on your user’s emotions. However, most of technologies are not able to capture the real time emotions because they change time to time.
We are the best people dedicated to solving this problem for music and video streaming platforms.
A team of psychologists, machine learning professionals and marketers, are here to understand your customers and your needs to help you doing more with less.
“My core concept is that the streaming platforms fail their monetization targets, not because they curated them enough or do not have top rated content, but the problem is that they have hundred thousands of content, but still using old methods to offer them to the users. Then, they end up with their license rights ended and have not make enough money out of them ”
“It’s possible to achieve your content monetization targets, if you have the right information and you follow the right steps in the right order. The right information about what emotion the user is at the time and what music or video could bring the highest engagement. Unfortunately, most platforms use very expensive tools with overwhelming data that at the end of the day, can’t help the reaching their targets. We have dedicated the last few years to solving this problem.”
Again, this is for founders, CMOs, and VPs of music and video streaming platforms who are trying to monetize their content better and more efficient, but who can’t figure a way to fill their pipeline and throw gasoline on the fire.”
We have founded in 2019. I and my co-founder have extensive experience in ICT and digital domain.
“For those of you who don’t know me, my name is Jafar Lotfi and I am founder and CEO of Kabbex,
And 3 years ago, when I was working in iflix, I started thinking how can we monetize our contents better and easier.
We had thousands of content and only a few percentage of them selling very good and easy. We had so many content and our users did not go to search all of them. So, basically, not very much of them being discovered by the users.
I was wondering how the other platforms like us, solve this problem, but learned that almost all platforms using the same technics for content personalization and monetization. And what was that, you think?
We were waiting that the users search something, then personalize everything according to what they browsed. It was working, but not quite for everything, for instance they mostly look for popular content, so the other not very popular ones, did not get any chance to be shown up. The interesting part was that, there was not very much we can make out of advanced technologies like machine learning. Unfortunately, those researches could not be ended up with a solution to help us toward our goals, at that time.
I decided to solve this problem myself and run a series of rapid hypothesis testing and experiments which resulted in the development of Kabbex. The Unique and Useful Insights I gained was by far my expectations. Solution worked better than I have ever imagined. Everyone else was asking if it will work for them as well. My new mission is to get the solution in the hand of marketers in music and video streaming platforms like you.
Facts About Mood-based Content Recommendation That Will Blow Your Mind