This document discusses Bauer Media's use of Snowplow for data collection and analytics across their 116 websites in Australia and New Zealand. Some key points: - Bauer Media started collecting Snowplow data in 2014 without a specific use case in mind. - They now use Snowplow data for cross-site reporting, ad hoc analysis, checking audience reports, and stalking individual users. - Snowplow allows them to track things like page views, user behavior, content metadata, and ads that can't be tracked as well with Google Analytics.

1. Snowplow drives
everything we do
What and why?

2. Digital and print publisher
Family-owned German company
116 sites across Australia and New Zealand
Tag management across all sites
Bauer Media

3. Just start collecting
Snowplow data collection in 2014
We didn’t really have a use case

5. Stuff we record
Page views
Metadata around content
User logins
Email click-throughs
Ad impressions

6. Use cases started showing up
Cross-site integrated reporting
Ad hoc tricky analysis
Sanity checking industry audience reporting
Stalking individual users
Audience overlaps

10. User behaviour
Ad impressions
Content metadata
Trending service
Recommendations
Dashboards
Ad hoc analysis

11. Some things you can’t do in GA
Tag-based reporting
Accurate reporting of in-app Facebook using user-agent contains FBAN

15. We’re using Snowplow 0.9.2 from 2014-04-29!
It just works
We’ve been busy building other stuff

16. But...
Page pings is b0rken: no time spent or scroll depth
(Out-of-the-box) browser categorisation is terrible
Hourly batches are a bit higher latency than we’d like
No context shredding, but JSON queries are performant enough

17. runSnowPlow.sh
Web page
(JavaScript in
page creates
image beacon)
S3
Cloudfront
SnowCannon
(Node app in
Elastic
Beanstalk)
Redirects to
Writes logs
to
ETL
(Elastic Map
Reduce)
S3
events
(Redshift)
events_temp
(Redshift)
x_events
(Redshift)

18. Tips
Redshift can get very expensive very quickly
Decent dashboarding platforms are rare
And plenty of crap ones are overpriced
Just tip everything in and worry about what you’ll do later

19. What’s next?

20. Future plans
Upgrade ETL to real-time: probably our own solution
Time spent and scroll depth
Shredding?