Product and marketing data can be a powerful pair, but they often live in silos. In this article, we'll talk about how to get them talking to each other. Once you get the data together, you need to create a process for creating reports and dashboards your team can rely on.
Getting custom analytics that blends product and marketing data is a common but difficult problem.
These databases are usually separate and their APIs do not allow for easy access to each other's data. And even if they did, the analytics capabilities of those platforms is usually pretty limited. Here's how to get them to work together:
A data warehouse is a central, trusted location that stores your organization's master dataset. A good place to start with this would be Snowflake, which has a free version available for up to 1 TB of storage and up to 5 GB of querying per month. The setup process usually takes just a few clicks.
With a data warehouse in place, you can use a tool like Fivetran or Stitch to sync data from all your other apps into Snowflake. Both Fivetran and Stitch support hundreds of integrations and are adding more every day. But getting all your data in one place is an important first step toward cross-functional analysis.
To get started, you’ll want to connect your data warehouse as an integration in Cascade (Cascade supports connections to Snowflake and most other data warehouses). Once the data is in Cascade, it’s easy to use Cascade's cleaning tools to clean and blend data on common keys. Once you have what you need, you can publish the analytics-ready tables back to your data warehouse.
It’s important that you set up a schedule for publishing these reports so that they are regularly updated with fresh insights about how your products are performing in the market and which digital channels are driving revenue growth.
To analyze and publish the results of your blended data, use a separate workflow to create and publish a Data App with your analytics in it. You can then use these data apps to create custom analytics that update over time as new data becomes available:
You can create a data app that looks like this:
Once you have a data app up and running, it's important to share it with your team. As the host of this new platform, you're best positioned to explain how it works and why it's important for everyone on board.
Including your teammates in this process will help build buy-in for using the data app as well as establish trust among team members. This will also help encourage collaboration throughout all of your teams—you've got plenty to choose from!
There's no shortage of data in the modern workplace. Every department can collect their own take on how the business is doing, but each will have a piece of the story. By using tools like Cascade to clean and blend data in a warehouse like Snowflake, businesses can lay the groundwork for a sophisticated data system, get a holistic view of the company and use it to inform better decisions in every aspect.