User Retention Stack

### Analyzing User Retention with Cohort Data.

Extract and transform cohort data from user analytics platforms using Airbyte and dbt to gain insights into user retention and churn.

How to get started:

- Check out the [README](https://github.com/airbytehq/quickstarts/tree/main) and the [Contribution instructions](https://github.com/airbytehq/quickstarts/blob/main/CONTRIBUTING.md) in this repo.
- Check one of the [existing quickstarts](https://github.com/airbytehq/quickstarts#list-of-available-quickstarts) and observe their structure.
- (Optional, but highly recommended) Implement one of the quickstarts by following the instructions in their README. I recommend starting with [E-commerce analytics in BigQuery](https://github.com/airbytehq/quickstarts/tree/main/ecommerce_analytics_bigquery)

Start with the README, CONTRIBUTING.md, and existing quickstarts linked in the issue, especially ecommerce_analytics_bigquery. Follow that quickstart's structure and instructions before planning the cohort-retention workflow. Done means adding a complete quickstart that extracts and transforms cohort data with Airbyte and dbt and explains retention and churn analysis.

Written by the indexing model from the issue text.