On the stage of Mobile Spree San Francisco 2018, Andrew Platts, Director of Data Engineering, discussed how Smule developed a BI system that allowed them to quantify user behaviour at each step of the funnel. By then linking this behaviour with acquisition data from Adjust (at a user level), Smule was able to link users across channels.
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“The high pole in the tent is data integration”
Michael Stonebraker Apr 2018
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Data Integration
Smule Partners/Web
Adjust Partners
Adjust
Data Platform
Smule
Data Platform
APIs SDK
Real time callbacks /
Server to Server Events
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• Core UA /Realtime . Self
Sufficiency empowering UA
• Data enhancement /
Integration
• Data Quality
Using Adjust to improve integration
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How to work with Adjust
• Mobile Engineering resistance to SDKs
• Build an ROI case - particularly around fraud - see examples
before. e.g (CRM/Braze)
• Update the SDK frequently
• Instrument an event listener that in the client that can duplicate
your own in-app event
• Use DCPs
We have more data than ever to inform our decision making but instead of making our jobs easier it often seems to make them more confusing.
In the tale of the ancient mariner, having shot the Albatros, the fog lifts for the crew to become becalmed , surrounded by water they cannot drink.
That is a tale of superstition - we are supposed to be ‘data driven’ of course. So how can we make our data more drinkable - more usable ?
Everyday we here how AI and machine learning are increasingly influencing our lives. In April Apple pulled off a coup by hiring Google’s chief data scientist . The New York Times reported that top talent in the field is attracting 8 figure salaries. A study says there are only 10k individuals qualified to do this work
How do data scientists actually spend their days ? The clean data 80% of the time. Cleaning and preparing data so they can analyze it.
Michael Stonebraker is the winner of the Turing Award - Ingres , Vertica , Berkeley , MIT - “The high pole in the ten is Data Integration”
This hides a complex system - its the manifestation of what lies underneath
The central message for this talk is how you can leverage Adjust’s system to enhance your own BI system. Here are five examples of things we do at Smule
This is a perennial problem for most app - particularly over time. It lies behind the abilty to create accurate LTV models. Some of your best uses can be those who buy a new device . On any day , what % os users are upgrading ? The persistent Adjust ID is valuable especially with 18% of people zeroing out IDFA.
A wealth of Carrier, connection and Geo data available. We used this in SEA to simplify our diagnosis of streaming problems. Using a unique message ID to send on our internal and through Adjust . We enrich now from two source.
We found we were missing events
As we move to increase retention and engagement through less costly CRM, we face a nouber of problems. We want a single name space for campaigns . This is central our ability to create a multi touch system that assigns revenue and engagement to the correct touch point . To do this , we use custom variables.
The cold start problem ? Recommender systems know little about you on Day 1. But those paid channels know a ton about you - so use it . I would trust FB to be pretty good at targeting ads based on age and gender - This data is available to you. Our data shows the median time from app open to install callback of 17 secs. In many cases, that’s enough to show more relevant content that will improve retention and engagement. You can feed this to your recommender system. Or simply curate content.
You’re getting this from your Ad Partners so build it into your BI platform
Some suggestions on how to start getting more out of Adjust