"Data is numbers, but remember that every single one of numbers is a real human being"
- Rochelle King, Spotify VP Design -
Product Design with Data
​Videopass mobile app was released in the Japanese market in 2015, and currently there are 1.3 million subscribers.
In July 2016, Android TV app was rolled out and pre-installed on the set-up box, which is integrated with the user's Videopass account in advance.
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In order to optimize the TV watching experience, we have started to collect user's behavior data and utilize analysis tools to discover the problems users experienced and the opportunities for future improvement.
What's the goal and key metrics
As a data-driven practitioner, our team start with these two questions before diving into the data analysis :
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What's goal and impact can we help our client to achieve?
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What key metrics can supportively evaluate the success of the product?
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We strategically integrate the client's business goals into the whole picture, which is fundamentally based on various user segmentations. Ultimately, we digest a fundamental goal, AVPA (Average Viewhour Per Auidence) and utilize this key metric to assess the health of the product.
Funnel observation 1: user select the movie or drama from home page
Funnel observation 2: User select the movie or drama from see more view
Observation and findings
The funnels are presented which users use to select the video to watch from the "See more" page that has a 6.86% higher click through rate(CTR) of play button than the Home page. To put it another way, the users possibly have a higher opportunity to find the movie or drama they want to watch on the “See more” page and play it. However, the "user behavior flow" in Google analytics shows that users are more likely to stay on the Home page to explore the movie or TV drama.
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This finding make us think :
Since the users prefer to stay on the Home page to explore the videos, how can we help users find the video they want to watch easily ? Also, how could the playback conversion rate of Home page be increased accordingly.
Ideation in the design workshop
My role : facilitator
Participants : PM, designer, front-end developer, SQA
A problem can be solved by various solutions. Therefore, we went through a design workshop to broadly generate the possible treatments to solve the problems we found through data analysis.
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PM, designer, front-end developer, and SQA were invited to participate. On the other hand, PM also played an important role to act as the voice of our Japanese PM (customer).
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At the final session of the workshop, each idea was reviewed and the participants voted for the ones which met the 3 principles :
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Meet customer 's goal & user needs
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Technical feasibility
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Measurable​​
Build up the hypotheses statement
As a result, we created a hypothesis according to the selected ideas and there were two:
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Hypothesis 1
Users can explore the videos within 30 counts (original counts is 14) in each item group on the Home page. If users can't find what they want to watch, they can still access the “See more” page feature to find more videos.
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Hypothesis 2
Users can infinitely scroll right to explore as many item as possible in each item group on the Home page without accessing the “See more” button.
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"Experimentation is a way for you to have a conversation with your users."
- Designing with data -
What's next...
Product design is an iterate process, so we shall learn from and utilize data to understand the users' behavior.
Now we continually plan an experimentations and predict the hypotheses which could have statically significant changes after A/B testing. The experiment result will be expected to show how users will react to it and whether something interesting is going on.
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