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Welcome to the Mobile & Hybrid App Analytics accelerator. Once finished, you will be able to build a deeper understanding of customer behavior on your mobile apps and use your data to influence business decisions.

Here you will learn to:

  • Model and Visualize Snowplow data
    • using the snowplow-mobile dbt package and Streamlit
    • using our sample data (no need to have a working pipeline)
  • Set-up Snowplow Tracking in a hybrid mobile app
    • track events both from a native iOS/Android/React Native code as well as embedded Web views
  • Apply what you have learned on your own pipeline to gain insights

Hybrid apps are mobile apps that in addition to a native interface, provide part of the UI through an embedded Web view. Snowplow events are tracked from both the native code (e.g. written in Swift or Kotlin) as well as the Web view (in JavaScript). Our goal is to have both events tracked from the native code as well as the Web view, share the same session and appear as tracked with the same tracker.

Who is this guide for?

  • Data practitioners who would like to get familiar with Snowplow data.
  • Data practitioners who would like to set up tracking in a mobile hybrid app and learn how to use the Snowplow mobile data model to gain insight from their customers’ behavioral data as quickly as possible.

What you will learn

In approximately 2 working days (~12 working hours) you can achieve the following:

  • Upload data - Upload a sample Snowplow events dataset to your warehouse
  • Model - Configure and run the snowplow-mobile data model
  • Visualize - Visualize the modeled data with Streamlit
  • Track - Set-up and deploy tracking to your hybrid mobile app
  • Next steps - Gain value from your own pipeline data through modeling and visualization
gantt dateFormat HH-mm axisFormat %M section 1. Upload 1h :upload, 00-00, 1m section 2. Model 2h :model, after upload, 2m section 3. Visualize 2h :visualize, after model, 3m section 4. Track 6h :track, after visualize, 6m section 5. Next steps 1h :next steps, after track, 2m

Prerequisites

Modeling and Visualization

  • dbt CLI installed / dbt Cloud account available
    • New dbt project created and configured
  • Python 3 Installed
  • Snowflake, BigQuery or Databricks account and a user with access to create schemas and tables

Tracking

  • Snowplow pipeline
  • Hybrid mobile app to implement tracking on

Please note that Snowflake, BigQuery and Databricks will be used for illustration but the snowplow-mobile dbt package also supports Postgres and Redshift.

What you will build

Mobile & Hybrid Apps Analytics Dashboard

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System overview

The diagram below gives a complete overview of the system covered in this accelerator:

  1. Events are tracked from app logic both inside the Web view as well as the native app code.
  2. Tracked events are loaded into the warehouse by the Snowplow BDP or Open Source Cloud.
  3. The raw events are modeled into higher level entities such as screen views, sessions, or users using the snowplow-mobile dbt package.
  4. Finally, we visualize the modeled data using Streamlit.
flowchart TB subgraph hybridApp[Hybrid Mobile App] subgraph webView[Web View] webViewCode[App logic] webViewTracker[Snowplow WebView tracker] webViewCode -- "Tracks events" --> webViewTracker style webViewTracker fill:#f5f5f5,stroke:#6638B8,stroke-width:3px click webViewTracker "https://github.com/snowplow-incubator/snowplow-webview-tracker" "Open tracker package" _blank end subgraph nativeCode[Native iOS/Android] nativeAppCode[App logic] nativeTracker[Snowplow iOS/Android/React Native tracker] nativeAppCode -- "Tracks events" --> nativeTracker style nativeTracker fill:#f5f5f5,stroke:#6638B8,stroke-width:3px click nativeTracker "https://docs.snowplow.io/docs/collecting-data/collecting-from-own-applications/mobile-trackers/installation-and-set-up/" "Open tracker docs" _blank end webViewTracker -- "Forwards events" --> nativeTracker end subgraph cloud[Cloud] snowplow[Snowplow BDP/OS Cloud] warehouse[(Warehouse)] dbt[snowplow-mobile dbt package] streamlit[Streamlit] snowplow -- "Loads raw events" --> warehouse dbt -- "Models data" --> warehouse warehouse -- "Visualizes modeled data" --> streamlit style dbt fill:#f5f5f5,stroke:#6638B8,stroke-width:3px click dbt "https://docs.snowplowanalytics.com/docs/modeling-your-data/the-snowplow-mobile-data-model/dbt-mobile-data-model/" "Open dbt package" _blank click snowplow "https://snowplow.io/snowplow-bdp/" "Snowplow BDP" _blank end nativeTracker -- "Sends tracked events" --> snowplow