Maximize your Startup Growth with First-party data
What’s the problem?
Startups usually sell high-consideration products with a long sales cycle, so startups often face the challenge of attribution.
Why? Because, usually, the purchases fall out of the attribution window (7 days for Facebook, 28 days for Google Ads), how do you avoid this problem to make data-driven decisions and grow?
Types of data: First-party vs Third-party
Google Analytics and Facebook Ads are examples of third-party data. When using these platforms, businesses rely on data collected by another company to measure the effectiveness of their marketing efforts. While these platforms provide valuable insights, the data collected may not be as reliable or accurate as first-party data for products with a long sales lifecycle.
On the other hand, pushing events directly to a warehouse such as Google BigQuery is an example of first-party data. By doing this, businesses collect data directly from their customers or users. This data is typically the most reliable and accurate because it comes directly from the source.
Collecting first-party data is essential for startups because it allows them to track the entire customer journey from start to finish. This means that they can accurately measure the impact of their marketing efforts and understand which channels drive the most conversions.
Doing so allows them to make data-driven decisions and grow their business more effectively.
Implement a First-party Data Strategy 101: The easiest, faster way.
Define what are the events that you want to track.
To define the events you want to track, I recommend following the Segment Events Spec as a general rule, even if you don't use Segment. Using their Events and Actions Naming convention is a great way to unify and guarantee different systems' compatibility. This will also help ensure that your data is consistent and can be easily analyzed later.
Define where you want to store your data and how you want to visualize it.
There are many data warehouses that you can use to store your first-party data. Some popular options include Google BigQuery, Amazon Redshift, Snowflake, and Microsoft Azure.
At a high level, a data warehouse is a system for storing and managing large amounts of data. Data is typically stored in a structured format, which makes it easier to analyze and query.
Once you've chosen a data warehouse, you must connect your site. This can be done using a tool like Segment, which allows you to collect and send data to multiple destinations, including your data warehouse.
I like using Looker Studio and BigQuery to analyze and visualize your first-party data. Looker Studio provides an intuitive interface for creating charts and dashboards, as they are a great option, especially if you're already using other Google products like Google Analytics or Google Ads.
Define how you would connect your site (source) with your warehouse (destination)
Many tools can connect your site (source) with your warehouse (destination). In particular, I like to use Segment and Rudderstack because they are affordable and reliable options for syncing sources and destinations. However, alternatives such as Server Side Google Tag, custom implementations, and different providers could be attractive. The choice will vary depending on budget and resources.
Conclusion
Startups face attribution challenges, with high-consideration purchases falling out of the attribution window. First-party data, collected directly from customers, is the most reliable and accurate for tracking the entire customer journey. To implement a first-party data strategy, define events to track, choose a data warehouse, connect the site to it, and use a tool like Looker Studio to analyze and visualize the data.
This could be challenging to implement, but using different ways to distribute your product, such as Ads, newsletters, and organic traffic, is super rewarding. Being able to map the entire funnel and understand the touch points that lead to purchase accurately is critical to Maximizing your startup growth.