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This accelerator will assist you in collecting user interactions and preferences from your Consent Management Platform (CMP) using Snowplow’s enhanced consent plugin.

User consent for data collection is essential for personalization, marketing, and ML driven actions. While CMPs provide some data on user preferences, Snowplow’s enhanced consent plugin allows you to gather more detailed information about user consent.

By using Snowplow to collect consent preference data, you can enhance your data model with granular, context-rich selection data at the user level. Having access to user consent data in your data storage enables you to incorporate it into your segments or machine learning models and take action based on customer preferences.

Here you will learn how to:

  • Set-up Snowplow Consent Tracking on your CMP (examples using Cookiebot and OneTrust)
  • Model your data using the Snowplow-Consent model
  • Create a consent health check dashboard from your data in Streamlit

Who is this guide for?

  • Data practitioners who would like to get familiar with the Snowplow enhanced-consent-plugin.
  • Data practitioners who want to learn how to use the snowplow-consent dbt package and set-up tracking using their companies website or single page application, to gain insight from their customers’ behavioral data as quickly as possible.

What you will learn

In approximately 5 working hours you can achieve the following:

  • Track - Set-up and deploy tracking to your website or single page application to allow consent tracking
  • Enrich - Add extra properties and values to your collected data
  • Model - Enable and run the consent module within the snowplow-web data model
  • Visualize - Visualize the modeled data with Streamlit
gantt dateFormat HH-mm axisFormat %H:%M section 1. Track 3h :track, 00-00, 3h section 2. Enrich 1h :enrich, after track 00-00, 1h section 3. Model 1h :model, after enrich, 1h section 4. Visualize 1h :Visualize, after model, 1h

Prerequisites

Complete our Advanced Analytics for Web accelerator if you don’t have any Snowplow modeled web data in your warehouse yet. You don’t need a working Snowplow pipeline, a sample events dataset is provided.

Modeling and Visualization

  • dbt CLI installed or dbt Cloud account available
    • New dbt project created and configured
  • Python 3 Installed
  • Snowflake, BigQuery or Databricks account (apart from the Streamlit visualization you should be able to follow along if you are on Redshift / Postgres as the data model supports those, too!)

Tracking and Enrichment

  • Snowplow pipeline
  • Web app to implement tracking
  • CMP Set up

Model outputs

  • snowplow_web_consent_log: Snowplow incremental table showing the audit trail of consent and Consent Management Platform (cmp) events

  • snowplow_web_consent_users: Incremental table of user consent tracking stats

  • snowplow_web_consent_totals: Summary of the latest consent status, per consent version

  • snowplow_web_consent_scope_status: Aggregate of current number of users consented to each consent scope

  • snowplow_web_cmp_stats: Used for modeling cmp_visible events and related metrics

  • snowplow_web_consent_versions: Incremental table used to keep track of each consent version and its validity

‘streamlit-dashboard’