Hi everybody my name is Keri Mallari and I'm a PhD student at the University of Washington's Human
Center Design and Engineering department I'll be presenting the work that I did with Spencer
Williams and Dr Gary Hsieh on understanding analytics needs of video game streamers. To start
off I'll be showing a short clip of a twitch streamer looking over her twitch analytics
Wow chat i feel like I've been streaming for over a year now with over 150 hours but I still
haven't really grown i average around the same number of viewers and maybe some days are better
than others and also you know like maybe same days have given me peaks in my follows, but this
analytics page isn't really telling me what I'm doing wrong or what I'm doing right. And even this
statistic isn't super helpful like such as live views or minutes watched. I'm not really sure you
know like what type of information do i need more or like what to do with this current information.
That short clip isn't unusual for other streamers to wonder themselves and also highlights some
of the questions that we try to answer in this paper such as "how do streamers utilize current
information provided to them by the streaming platforms?", "what additional information streamers
need and why?" and "what are some challenges and opportunities to support live streamers in
their communities?" We conducted an interview study where we recruited participants from
Twitch and Mixer who have had experience on the platform streaming and also using the analytics
within those platforms. We accompanied this data with data from our participants' discord servers
and collecting messages sent by the streamers for the past six months. We found approximately 8,000
messages with as little as 110 messages to 600 messages per streamer they follow the grounded
theory coding approach for analyzing our interview and discord data for the themes in our findings .
For our first question we try to answer how do streamers utilize current information provided
to them by their streaming platforms and these [table shown on screen] are the currently available internal platform
analytics available both on twitch and mixer so either these statistics are either just switch
just mixer or available in both but we've categorized them into three areas of stream
performance, viewer engagement, and revenue and we found that streamers use more than just that they
also use social media platforms to view you know their promotion, impression, and engagement metrics
within their communities. We also see that they use communication tools analytics
to help understand and view interactions within their community members,
and then internal platform analytics, such as shown in the clip before are used to primarily
track progression of either a single broadcast or the entire career of a streamer and then there's
also third party streamer analytics that's used to track additional insights such as you know
donations that happen during on stream or income from merchandise. Then we tried to answer what
additional information the streamers need and why and we found that there's three main areas
of analytics needs: "content production", "marketing strategies", and "community management" these are the
types of information that streamers identified that can help them improve these analytics needs so for
Content production these are information that can help them kind of alter maybe change maybe their
the game that they're playing or their streamer persona or maybe some technical aspects of the
stream. Marketing strategies these are information that can really help the streamer kind of maximize
their viewer potential, understanding what referral source is effective for them or understanding the
competition on the platform with category and time saturation, and then community management these are
information that can help them improve you know the growth and safety of their communities such as
the viewer age or their viewers history on on the platform
And finally we identify some challenges and opportunities to support live streamers and their communities
We found that existing analytics are very platform-centric and platform-serving
and they don't necessarily identify like how streamers can achieve success or improve uh and
are just kind of like there. we also found that these analytics are only descriptive
while other fields have predictive and prescriptive analytics current insights are just limited to
basic dashboards about what happened in the past and finally we found that there is
lack of qualitative feedback and streamers do value qualitative feedback so it's kind of hard for streamers
to store and recall useful feedback that happens during broadcast.
We identified opportunities to develop maybe additional analytics to support direct needs of streamers
such as maybe inference models about viewer behavior to identify- to help with future streaming techniques
and also opportunities to develop human-centered analytics that cater to needs of a given community and
can potentially be generalized to other fields as well.
In this page is the summary of our findings. Thank you for coming