Nordict Hiit x Raptor
A Personalized Workout Experience
Challenge
Presenting the right training video that fits the users’ needs and activating all content on the website – not just the newest uploads.
Solution
Based on Raptors algoritms, Nordic Hiit is able to present the most relevant training video to their users that matches training level and interest.
About
When we talk about personalization, it usually refers to a commerce site, product recommendations, or upsales. But data-based recommendations can cover so much more. Nordic Hiit is a great example of that.
Nordic Hiit is an online training concept with online video workouts on demand.
The mission for Nordic Hiit has been clear from the beginning; it should be easy for everyone to live a healthy lifestyle – even during a busy schedule and without having to hit the gym.
Nordic Hiit has developed a platform which gives their users access to 1000+ workout videos within the categories HIIT, yoga, running, office workouts, pregnancy workouts, postpartum exercises, and pilates. The videos can be accessed on their website and through their app.
Challenge
With the increasing success, the team at Nordic Hiit wanted to develop its platform further. Nordic Hiit wanted to be able to present personalized video recommendations on their website and in their app based on the individual user’s behavior and preferences.
After all, an aspiring marathon runner needs a different workout plan than a new mom wanting to strengthen her back.
Nordic Hiit had to take their business from being a static “one-size-fits-all” delivery model, where every user was recommended the same videos, to a hyper-personalization model.
We wanted to make our site more personalized towards the individual user. The old solution was a “one size fits all”, where all users received the same training video every day no matter the training level, equipment, and goal. We needed a solution where our users get treated as individuals and receive a video that is tailored towards their behavior and preferences.
Nordic Hiit did not have the tools or the correct platform to solve and meet these challenges and demands. Nordic Hiit’s agency, Novicell, turned to Raptor Services and asked if this was something Raptor was able to solve.
Raptor took on the challenge and started working on the foundation of the recommendation algorithm.
Nordic Hiit did not have the tools or the correct platform to solve and meet these challenges and demands. Nordic Hiit’s agency, Novicell, turned to Raptor and asked if this was something Raptor Services was able to solve.
No matter the idea or challenge, Raptor was able to solve it. When the “Proof of Concept” had been developed, tested and approved, Raptor were fast to implement the solution on Nordic Hiit’s website and app. Raptor’s personalization engine is very scalable both horizontally and vertically in the sense that when Nordic Hiit comes up with an idea for the recommendations, Raptor has no problem solving it. They have moved the recommendations from a stage where they only needed to pick the next video to a more advanced setup, that involves many complex algorithms.
Solutions
Every user on Nordic Hiit’s platforms has chosen a specific training level, training goal, training days, and what equipment they have available in their home, on their profile.
This means there are a lot of different preferences that have to be taken into consideration when creating recommendations for the users.
Whenever a user clicks on “next video”, a signal is sent to Raptor’s recommendation engine. The Raptor recommendation engine then starts the process of finding the most relevant video for the individual user on Nordic Hiit’s platforms. This takes place in 3 steps:
Step 1: The algorithm starts by separating the three different training levels that the individual user has chosen in their profile preference settings. This means that there are three different algorithm paths which are either beginner, intermediate, or advanced.
Step 2: The recommendation engine then starts a data filtering process by looking at the individual user’s profile. Based on the chosen equipment, training goal, and training days it will include and exclude videos from the video catalog containing +1000 videos. Likewise, the algorithm will make sure that the videos fit the current season, so the workout videos that fit into a winter environment do not get recommended in the summer months.
Step 3: In the last step, the algorithm takes into consideration which workout videos you have watched recently. If you have just done a workout that trained your legs and abs, then the next video should not contain the same exercises.
When the user clicks the “play” button, the algorithm immediately finds the most relevant video.
The algorithm starts this process every time a user clicks the “next video” button, and every time the algorithm finds the correct order of videos to show. All these steps in the algorithms happen within milliseconds, and therefore there won’t be any delay for the user.
We are proud of this case since it shows how custom our personalization engine can be. The results of the Nordic Hiit solution are a testament to the agility and customization of our solution. We emulate a personal trainer to find the most relevant workout videos based on the user’s preferences. This will give the users the best training results based on their training level, goal, equipment, and previous workouts.
Results
The recommendation engine has been running on Nordic Hiit’s platforms for a while now, and the results so far have been great.
Over the past year, Nordic Hiit has seen a significant boost in Customer Lifetime Value (CLV).
They have also seen a rise in Trial-to-Paid conversion rate and an improvement in Churn Rate.
Great results like these have many causes. Nordic Hiit has consistently improved their video content, expanded the range of workouts they offer, and created a great sense of community amongst members.
Much of it can also be ascribed to a higher level of customer satisfaction as a result of more individualized training videos.
We are very satisfied with the solution that Raptor has built. The solution is still new, but we expect that the implementation of personalization on our platforms will result in better training results for our clients. This means that they will stay with us longer now that their experience with us is 100% personalized towards their behavior and preferences.
Ida and Christina describe the improved customer satisfaction like this:
With the old solution, a lot of our users found it annoying that the videos they got recommended entailed training equipment, which they did not have in their home and the training videos was not divided into the different training levels, so the workout was difficult for some of our members. This will not happen now due to the implementation of Raptor.
Another result of the implementation has been that a lot more of the 1000+ videos are being viewed, and not just the most recent videos. Before, a lot of the older videos did not get any views, since they did not appear anywhere after the initial release.
The Future
Nordic Hiit’s journey towards creating the most personalized online training experience in the market doesn’t end here.
Recently a ”favorite” button has been added to the videos, which users can use to save a workout they enjoyed.
But the button does more than just save a video for future use!
The favorite button can be used to create lists of the user’s favorite workouts, but we can also use the data to recommend related videos that other users who have liked the same videos have seen.
We all know it from Spotify, which creates playlists based on the music we listen to. We can do the same for video workouts. If a user has watched a lot of workout videos about yoga or stretching, then we can create a playlist with more videos like the ones they have watched.
Trigger messaging is also a part of Nordic Hiit’s future plans.
If a user has been at the same training level for a certain amount of time, Raptor can send messages like “Is it time to take your training to the next level?” to get users to watch new videos, which hopefully means that they will remain a member.
Based on all Nordic Hiit’s user’s behavior such as clicks, favorites, and profile settings, the plan is to create a public playlist that is tailored towards the individual, which can create even more value for the user.
Raptor Solutions
Website Personalization
Product- & content recommendations for web and search
Take-aways
Raptor has helped Nordic Hiit take their home workout platform to the next level, offering a personalized and individual workout experience for their users. This case proves that the right personalization engine can be customized and tailored to any business and its goals.
- Nordic Hiit went from a static one-size-fits-all model to a dynamic 1:1 personalized workout experience
- The right personalization engine can be used to personalize any businesses customer journey
- Tailored recommendations ensure a better customer experience overall, and for Nordic Hiit it has boosted Customer Lifetime Value (CLV), Trial-to-Paid conversion rate, and prevented churn.
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