Branch to Tableau

This page provides you with instructions on how to extract data from Branch and analyze it in Tableau. (If the mechanics of extracting data from Branch seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is Branch?

Branch Metrics lets businesses generate deep links they can use to track conversions and user engagement on web and mobile transactions. It provides a business analytics dashboard to surface user behavior data.

What is Tableau?

Tableau is one of the world's most popular analysis platforms. The software helps companies model, explore, and visualize their data. It also offers cloud capabilities that allow analyses to be shared via the web or company intranets, and its offerings are available as both installed software and as a SaaS platform. Tableau is widely known for its robust and flexible visualization capabilities, which include dozens of specialized chart types.

In addition to its business software, Tableau also offers a free product called Tableau Public for analyzing open data sets. If you're new to Tableau, this offering is a great way to experience Tableau's capabilities at no cost and share your work publicly.

Getting data out of Branch

Branch exposes data for things like install, open, clicks, and web session start through webhooks to user-defined HTTP POST callbacks. You can add a webhook through the Branch dashboard.

Sample Branch data

Branch exchanges data in JSON format. Here’s an example of the data returned for a clicks endpoint:

POST
User-agent: Branch Metrics API
Content-Type: application/json
{
    click_id: a unique identifier,
    event: 'click',
    event_timestamp: 'link click timestamp',
    os: 'iOS' | 'Android',
    os_version: 'the OS version',
    metadata: {
        ip: 'click IP',
        userAgent: 'click UA',
        browser: 'browser',
        browser_version: 'browser version',
        brand: 'phone brand',
        model: 'phone model',
        os: 'browser OS',
        os_version: 'OS version'
    },
    query: { any query parameters appended to the link },
    link_data: { link data dictionary - see below }
}

// link data dictionary example
{
    branch_id: 'unique identifier for unique link',
    date_ms: 'link creation date with millisecond',
    date_sec: 'link creation date with second',
    date: 'link creation date',
    domain: 'domain label',
    data: {
        +url: the Branch link,
        ... other deep link data
    },
    campaign: 'campaign label',
    feature: 'feature label',
    channel: 'channel label'
    tags: [tags array],
    stage: 'stage label',
}

Preparing Branch data

If you don’t already have a data structure in which to store the data you retrieve, you’ll have to create a schema for your data tables. Then, for each value in the response, you’ll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them. Branch's documentation should tell you what fields are provided by each endpoint, along with their corresponding datatypes.

Complicating things is the fact that the records retrieved from the source may not always be "flat" – some of the objects may actually be lists. This means you’ll likely have to create additional tables to capture the unpredictable cardinality in each record.

Loading Data into Tableau

Analyzing data in Tableau requires putting it into a format that Tableau can read. Depending on the data source, you may have options for achieving this goal, but the best practice among most businesses is to build a data warehouse that contains the data, and then connect that data warehouse to Tableau.

Tableau provides an easy-to-use Connect menu that allows you to connect data from flat files, direct data sources, and data warehouses. In most cases, connecting these sources is simply a matter of creating and providing credentials to the relevant services.

Once the data is connected, Tableau offers an option for locally caching your data to speed up queries. This can make a big difference when working with slower database platforms or flat files, but is typically not necessary when using a scalable data warehouse platform. Tableau's flexibility and speed in these areas are among its major differentiators in the industry.

Analyzing Data in Tableau

Tableau's report-building interface may seem intimidating at first, but it's one of the most powerful and intuitive analytics UIs on the market. Once you understand its workflow, it offers fast and nearly limitless options for building reports and dashboards.

If you're familiar with Pivot Tables in Excel, the Tableau report building experience may feel somewhat familiar. The process involves selecting the rows and columns desired in the resulting data set, along with the aggregate functions used to populate the data cells. Users can also specify filters to be applied to the data and choose a visualization type to use for the report.

You can learn how to build a report from scratch for free (although a sign-in is required) from the Tableau documentation.

Keeping Branch data up to date

Once you’ve set up the webhooks you want and have begun collecting data, you can relax – as long as everything continues to work correctly. You’ll have to keep an eye out for any changes to Branch’s webhooks implementation.

From Branch to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing Branch data in Tableau is to store that data inside a data warehousing platform alongside data from your other databases and 3rd party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Branch to Redshift, Branch to BigQuery, and Branch to Snowflake.

Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to solve this problem automatically. With just a few clicks, Stitch starts extracting your Branch data via the API, structuring it in a way that is optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Tableau.