This is the finale of our four-part series walking you through how to build out your own product-led growth (PLG) customer relationship management (CRM) tool. First time here? Start with part one.
Part 3: Load your modeled data into your CRM
Now that your CRM is configured, you’re finally ready to sync your product data.
There are many different ways to sync data between systems. However, if you have modeled your data using dbt, one of the the most straightforward methods is to use a “reverse ETL” tool like Census, Hightouch, or Grouparoo. These tools read your dbt-modeled data directly from your data warehouse and sync it to a wide variety of other SaaS tools.
In most cases, you simply need to configure the reverse ETL tool to map your events, metrics, and properties to fields on the objects in your CRM.
Hightouch has put together a guide for how they sync their product data to a CRM in Hubspot using, you guessed it, Hightouch!
Part 4: Turn your data into action
With the most important data now loaded into your newly-minted CRM, you can easily keep tabs on your most important customers all in one place.
However, anyone who has used a CRM before will tell you that the real value comes from the automated workflows you build on top of the data stored inside.
For example, consider a common scenario in companies with a product-led motion:
- How do you identify which of your self-service users needs additional support from someone on your team?
- Then, how do you decide what type of support to provide?
- Finally, how do you know whether your interventions are having the desired effect?
To start to answer these questions, you’ll first need to identify the list of users that are demonstrating a need for assistance. For example, using the phases from part 2, you can build a segment of users in the “Activated” stage that have not yet reached the criteria for “Expanding.” Then, we can layer in additional criteria that only includes users from the types of companies you typically work with.
With this segment built, you can trigger specific actions every time a user or account is added. If the tool you chose for your PLG CRM does not natively support this type of triggered workflow, you can use Zapier to the same effect.
For this example, let’s say we want to let our sales team know when a new user meets our criteria. This can be done by sending a Slack message to the owner when the user is added to our segment.
Using monday.com, you can create simple automation rules to alert your team when your criteria are met.
Finally, you can start to understand the impact of your actions by creating segments of users and accounts where certain interventions occurred. For example, add accounts where sales presented a 1:1 demo to a dedicated segment. How do important metrics like conversion rate, ARR, and retention rate compare for accounts in the segment versus those that aren’t?
For even more reliable metrics, segments can be used to experiment with sales-led interventions by randomly assigning some users and accounts to a “holdout group” and others to an “exposed group.” Comparing outcomes of the two groups can indicate whether the experimental action had the intended effect.
As you can see, it’s possible to build a basic PLG CRM using free or low-cost tooling. Whether you choose to build your own or work with a dedicated platform like Pace, there are many new and interesting workflows you can enable by enhancing your existing CRM with data from your SaaS product.
Have you built your own PLG CRM or used similar tools to add product usage data to your CRM? Send us a note! We’d love to hear about your experience and feature you in a future post.