Webinar Slides: Cost of Errors on VoD Services

February 9th, 2021
Cost of
Errors Webinar
All rights reserved. © Bitmovin Inc 2021

Your
presenters
Christoph
Prager
Product Manager,
Analytics Product
Katy Oberdiek
Senior Product Marketing
Manager

● Introduction
● The ambiguity of errors
● Cost of Errors for SVOD platforms
● Cost of Errors for AVOD platforms
● Data to reduce error rates
● Summary and Q&A
Agenda

The ambiguity of errors

Errors per device/platform

Top Error Codes in Bitmovin Analytics
A problem well known
● Error codes are
seldomly clear
● Often only point
towards a direction of
where the error could
originate from
● In extreme cases the
error code and
message tell
developers nothing
● Error Message:
“Unknown”

Errors across the Bitmovin Analytics platform
Errors across Bitmovin Analytics
● Categorizing all errors we
see in Bitmovin Analytics
(across all players and
platforms)
● Only 15% of errors point
directly to an underlying
issue
● 65% are ambiguous, only
pointing towards a
problem area
● 20% of all errors are
unclear

Well studied
correlation
between
technical
streaming issues
and viewers
abandoning
playback
Limelight (2018): 29% of viewers
abandon a video after a single
buffering incident 37% after a
second buffering event
Akamai (2017): “for every
additional second of startup
delay, an additional 5.8% of your
viewership leaves”
Krishnan & Sitaraman (2013): “a
viewer who experienced failure is
2.32% less likely to revisit the
same site within a week”

What monetization model
do you follow?

*Bitmovin Video Developer Report 2020

The cost of errors for SVOD
video streaming platforms

Two data points we based our model upon
Vimeo* identified that the technical
issues churn rate lies at 6%
The ARPU across different
SVOD types is around $15*
*Vimeo: https://vimeo.com/blog/post/reduce-subscriber-churn-rate/

Errors per subscriber per day
Error % Industry
Insights Bitmovin
Analytics:
6.6%
Plays attempts per
subscriber per month
150
Errors per subscriber
per day
0.33

Customer lifetime value
*Vimeo: https://vimeo.com/blog/post/reduce-subscriber-churn-rate/ **Assumption
ARPU*
$15
Technical churn rate*
6%
Subscription price**
$15
Days until churn
500 days

Errors per subscriber over customer lifetime
Days until churn
500 days
Errors per subscriber
per day
0.33
Errors a viewer sees till
churn
165

Error % decrease – lifetime value increase
Errors a viewer sees till
churn
165 errors
Error % decrease
10%
Days it takes to reach
the threshold after
decrease
505.5 days
Increase in customer
lifetime value
1% / $2.75

Case SVOD - incremental change matters
Number of subscribers
1,000,000
Subscribers who churn
due to technical
reasons
60,000
Increase in revenue
$160,000

The cost of errors for AVOD
video streaming platforms

“A viewer who experienced
failure is 2.32% less likely to
revisit the same site within
a week”
Krishnan & Sitaraman (2013)

Errors per subscriber per day (unique viewer level)
Plays per unique per*
week
1.5 plays
Ads per play*
2
Weekly recurring
viewers
30%
Cost per 1000 errors
$1.25
CPM
$60
*Data from Bitmovin Analytics / **Krishnan & Sitaraman (2013)
Viewers who
experienced failure are
2.3% Less likely to return**

Case 2 - incremental changes matter
Number of play
attempts per week
25,000,000
Bitmovin Analytics
industry insights
error rate
6.6%
Foregone revenue due
to errors
$2,000 / week

But how can the error rate
be reduced when error
codes and error messages
are so difficult to work with?

More context
around errors
● Session level data can
provide context around
the error
● Information about the
viewer’s tech stack
● Bandwidth conditions
● Suitable for support
teams for confirmation
of viewer behavior
Session Details visualization and log

Error detail provides stack traces
Additional error data
Additional error data
in the form of stack
traces point towards
the origin of an error in
the code

Segment information
Segment information
(Innovation)
If an error is identified
additional data for 10 segments
around the error is collected.
● HTTP status
● Type
● Download speed
● Time to first byte
● Size

Better error messages
Choose your Player based on
the quality of the error
documentation
Bitmovin Player & Analytics
teams working together on
improving error messages
based on findings from the
Analytics service

Summary
Cost per 1000 errors in AVOD
$1 - $3 per 1000
errors
LTV increases by
1%
with each 10% error decrease
(for subscribers who churn for
technical reasons)

Please find the links
to all related assets
Cost of Errors Whitepaper
The whitepaper serves as a great reference guide to
explain what each error code means so you’re able
to correct them.
Cost of Errors Calculator
The calculator is a tool in which you can enter your
numbers to calculate the cost of these errors as it
relates to your business.
Errors per device class infographic
Learn more about how errors affect a standard
streaming workflow in this handy infographic.

Thank you.

Webinar Slides: Cost of Errors on VoD Services

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