Designing FightMe P.1 What is a challenge?
Brief — Create a challenge based video app that encourages participation based on learnings from the current product
One of my favourite forms of literature is the ‘Koen’, something like a riddle, but distinctly in the Buddhist tradition.
Nan-in, a Japanese master during the Meiji era (1868–1912), received a university professor who came to inquire about Zen.
Nan-in served tea. He poured his visitor’s cup full, and then kept on pouring.
The professor watched the overflow until he no longer could restrain himself. “It is overfull. No more will go in!”
‘Like this cup,” Nan-in said, “you are full of your own opinions and speculations. How can I show you Zen unless you first empty your cup?’
TL:DR Assumptions are thought ‘shortcuts’ designed to save time and effort, but they can also inhibit learning.
I try to approach design with a blank mind, waiting to be filled with knowledge from users, stakeholders, data and the market.
I was lucky enough to join a product with enough momentum to inform a new design, but my early days at FightMe were spent trying to understand what a good challenge looked like to us and to our users.
What the data told me
‘Without participation we are YouTube’ is a phrase I liked to band about the FightMe office. YouTube is obviously a massive success, but participation not observation is at the heart of a social challenge platform.
To understand how to maximise participation, we first needed to understand the challenges that foster participation.
What are FightMe’s most participated challenges?
In a similar experience to sifting through tweets via hashtags, before the redesign of FightMe, traversing videos through tags was the easiest way to view videos related to specific challenges.
While some of the user generated tags where tied to a particular challenge e.g. flipshit, others where more general (such as #singing or #handstand).
In order to piece together a solid understanding of the most popular challenges I categorised the various hashtags by frequency, the most quoted tag being the top result.
The ‘generalist’ tags (e.g #singing) represented a category rather than a specific challenge and by labelling and eventually removing these from the data set, I was left with a solid measure of the most participated challenges on the app.
First assumption: Are there different levels of challenges?
Whilst organising the data, it became obvious that there where different levels to entry for challenges and grouping these challenges would enable me to make assumptions about the impact complexity had on nature of participation.
There were challenges for the highly skilled such as Parkour, Rapping and Skateboard. These tend to require some innate skill so, naturally, I labelled this group ‘Badass challenges’.
Then there are challenges that allowed users to participate from their office or school, on a 5 minute break. These challenges required few technical skills but had a comedy element and offered a feel good experience. I christened this group ‘5 minutes and a phone.’
In between the high and low barrier challenges were the ‘a little hard to do’ segment. These are challenges that require some skill, but where generally ‘simpler’ than the ‘badass’ type.
With a loose taxonomy of challenge types I decided it was time to dig a little further and question the characteristics of the most participated challenges beyond my initial assumptions.
Are there common traits visible in all highly participated challenges?
Pattern recognition is a major part of data analysis. Sometimes these patterns are so obvious that they beam like neon signals from your dashboard.
Sometimes the data has to be pruned and shaped in a process that allows the trace of that pattern to shine through.
During this time I was lucky enough to encounter the work of Stanford PhD B.J Fogg. His behavioural design theory helped me understand the pattern of ‘simple to do’ actions.
When this framework was applied to FightMe’s most participated challenges it highlighted a formula that was easy to understand.
It may come as no surprise to learn that the most participated challenges had a low barrier to entry, gave clear instructions on how to participate (low brain effort) and offered a short burst of novelty.
But during this mapping process, a category of challenges was discovered that offered marketing potential.
A person filming themselves throwing a solo party session could be deemed as a little odd. But when 100 people join in, it offers a pretty unique social experience. ‘Lonely Rave’, ‘High Five a Stranger’ and ‘Random Acts of Kindness’ are highly participated challenges that go against social norms and I dubbed these- ‘Feel connected feel good’ challenges.
These ‘Feel connected feel good’ challenges had good marketing potential as they we’re interactive experiences unlike anything else on the web.
The other 99%
Although getting users to participate was the number 1 goal of the redesign, it is common knowledge that most users of social apps are spectators and as such, spectatorship is an important factor to help understand app usage.
While I could have used ‘views’ to map spectatorship, FightMe’s currency of ‘applauds’ had more value simply because they act as a stamp of approval while a ‘view’ tells us little about the satisfaction that particular content provides.
Nearly all of the highly ‘applauded’ videos come from the ‘Bad Ass challenges’. It was obvious that this type of content offered a lot of FightMe users high spectator value.
The data also highlighted that even though ‘five minutes and a phone’ challenges are likely to be participated in, they didn’t necessarily accumulate spectator value. This gave us some indication of their shelf life.
Balancing the need to deliver value to spectators and participants would impact the type of content we promote on the app. Now we had a solid hypothesis regarding which types of challenge are likely to produce which types of interaction. The end product was a proposal for a challenge creation schedule.
The aim of this proposal was to enable FightMe’s community managers to experiment with the challenges they promoted in the app. The results would give us further insight into how app engagement was effected by exposure to challenge types.
The biggest risk of the information provided by this research was the wide focus FightMe had adopted in attracting users with interests ranging from, singing to parkour. The data on highly participated challenges was based on the assumption that we would maintain (and grow) in all the verticals in which we’d previously operated.
New features and different approaches to marketing fit could lessen the relevance of the results, but the benefit of having the wider team understand a ‘simple to do’ framework would prove to be useful regardless of challenge vertical.
Thanks for reading this post I’d love to hear your feedback. In my next post I’ll discuss designing the core of FightMe’s experience ‘The Challenge Details’ screen.