Snowplow - Analytics & Data Rollout at Seven
- 1. consolidate analytics across multiple platforms Presented by Luke Lewandowski Head of Dev & QA
- 2. Introduction Luke Lewandowski Head of Development and Quality Assurance at Seven Nearly 12 months ago we launched 7plus - OTT product MVP was developed in 8 months - 5 platforms launched - HbbTV, AppleTV, Web, iOS & Android Currently over 12 platforms that 7plus runs on P&T department runs more than just one product now in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018
- 3. “It always seems impossible until it is done.” Challenges Nelson Mandela
- 4. Challenge #1 - Event Comparison Multiple platforms with each having different event types Meaningful comparison between platforms becomes problematic - even though it shouldn't! A non-technical person should NOT need to know about differences between platforms (within reason) in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018
- 5. Challenge #2 - SDKs! Every platform has its own SDK with their own "smarts". Eg. page load analytics or GPS location for mobile device. Right now there are 16 open trackers for SnowPlow on GitHub Testing becomes a little bit harder as you don't know what to expect from each SDK. The "It is 2 lines of code" scenario - but many hours of scratching your head from QA perspective. in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018
- 6. Challenge #3 - Cost Each industry metric has to go through certification/testing process. Industry metrics - means even more SDKs to be implemented. in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018 Justifying the ROI on each platform is very cumbersome and to achieve analytics alignment across 10+ platforms is very hard.
- 7. Challenge #3 - Cost CD. in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018 MVP Scenario - 7plus - 5 platforms - 4 different SDK (DMP, Industry Metric #1, Industry Metric #2, Analytics #1) - Each analytics platform, implementation + testing (and certification if required) - 1 weeks Example rate $800 p/day for developer = $16,000 per platform MVP = $80,000 just to implement basic stuff JUST FOR DEV!
- 8. “We cannot solve our problems with the same thinking that created them.” Solutions Unknown
- 9. Unify all events & attributes in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018 GOAL: Roll out analytics/data in a way where anyone in the business is empowered to use that data for business/product decisions. Consolidate all events across all devices. eg. Application Launch event means the same thing across all platforms. Version all of our events. Each version bundles product and technical events. Allows for events that would have never been ROI justified to be implemented that benefit analytics team as well as dev & qa. Often those events end up actually being used for product! Major versions are backward compatible.
- 10. Unify all events & attributes cd. in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018 GOAL: Roll out analytics/data in a way where anyone in the business is empowered to use that data for business/product decisions. Provide tools & educate business stakeholders how to use their data to find information they are seeking. Utilise concept of inheritance for our attributes to make implementation a lot easier for developers & QA.
- 11. Example events
- 12. Tackling SDK Nightmare! in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018 GOAL: Keep the cost of roll out and maintenance low (both dev & qa). As well keep consistency across platforms - even if they are on yearly release cycles! One analytics platform - proxy them all!
- 13. Tackling SDK Nightmare Cd. ! in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018 GOAL: Keep the cost of roll out and maintenance low (both dev & qa). As well keep consistency across platforms - even if they are on yearly release cycles! We have found a lot of SDKs to be easy to roll out - however, not to deliver what we want. We have failed pretty bad the first time we tried to roll out iOS, Web & Android. All events were inconsistent with different properties. We have created our own very light weight SDK that pushes events through POST and it only contains what's absolutely required. We write application that validates events against our custom context / properties to make life a lot easier for everyone involved in analytics. This also ensures that certifications are also much easier as we test at the source.
- 14. Benefits in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018 Every platform uses same set of events that are easy to understand - regardless of platform. Implementation of new destinations - eg. Google Analytics is simplified - roll it out once and all platforms benefit. Big cost efficiency! Internal data department gets a copy of all events - where before they had to ask each product to roll things out - which is sadly never a priority! We are now benefiting from some of the interesting work they do because of it. Our product features can now consume some of the events to make our product better. (eg. CRM, notifications, marketing, continue watching etc.) Our certification process is much easier with the time we invested into internal tooling that can easily pick up issues with events early.
- 16. Drawbacks in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018 As we are working on getting more products on the platform - we are having to reshuffle the infrastructure to ensure separations of concerns, stability etc. Bottlenecks related to throughput - Kinesis Sharding - although we are Melbourne Cup battle tested. How do we manage development across departments that might want their own destinations? How do we manage cost across product / ROI etc. ?
- 17. Things still to tackle in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018 Utilise SnowPlows' built in features - eg. schema validation, enrichment (we tried but failed) Roll out all platforms with our TinySDK instead of full SDK. Next iteration of our standard of events - including features to make analytics even more maintenance / dev friendly. Monitoring (especially when it comes to context) eg. you can't pause video that you haven't started watching. Implement context testing on the validation tool.
- 18. Q & A in/luke-lewandowski Creative Commons Attribution 4.0 International License Produced in 2018
- 19. SnowPlow Trackers - https://github.com/snowplow/snowplow/tree/master/1-trackers AWS Template that we used - https://github.com/Bit- Clouded/Glenlivet/tree/42613f8a5fdb34d41d43effa7ed799d52b6b097d/analytics Sharding Limitations - https://aws.amazon.com/kinesis/data-streams/faqs/ References