Data is a huge part of my job as a marketing operations manager; the more, the better. And we have a ton of it at StreamSets. But for those of us in marketing and sales, product usage data has always been just out of reach.

I’m excited to announce this has changed. Using StreamSets and Software AG webmethods.io, I recently integrated product activities into Salesforce to give Sales and Marketing the intelligence they need to help convert free trials, find customer service opportunities, and more. You can check out my demo below.

To integrate product activities into Salesforce, StreamSets first needed to make sure that the user information within both our platform and Salesforce was in sync. At the time, our ability to get information on users who signed up was spotty; crucial data like names, companies, email addresses, and other relevant information was often missing from our Salesforce database. In a joint effort with one of our in-house data engineers, Kavya Nagarajan, we configured a StreamSets Data Collector to fill those gaps, enabling the import of that user information into Salesforce.

Consistently importing this data allows us to track all sign-ups for the StreamSets platform more reliably at a scale we couldn’t reach before. We now have insight into sign-ups through backend platform invitations, direct sign-ups, and third parties like Snowflake Partner Connect. 

In laying the groundwork for our reverse ETL projects, it’s important to acknowledge the pivotal role played by one of our Data Engineers, Vignesh Kanaan. Vignesh successfully undertook the complex task of consolidating all our fragmented data into Snowflake, establishing it as our single source of truth. This foundational work greatly facilitated the subsequent user database synchronization between our platform and Salesforce using StreamSets Data Collector.

With user data successfully synced up, I was ready to start the next phase of my project. My goal: Track and organize a user’s StreamSets product activity (or usage) data within Salesforce.

This involved migrating the data from a Snowflake table into Salesforce and making it accessible by attaching it to the Lead, Contact, and Account objects.

We defined product activities as specific actions or events within the StreamSets platform that could indicate an increased willingness to purchase the product or inform us where users might hit roadblocks. We created a table in Snowflake tracking these actions: user creation, org creation, engine creation, pipeline creation, and other milestones, all the way to running a job.

I used webMethods.io for this integration. It queries product activity data from Snowflake, processes the data—completing important operations such as mapping Snowflake fields to their respective Salesforce fields—and pushes the newly transformed data into Salesforce, storing activity name, date, and UUID values into the “product activity” custom object.

We designed the project’s architecture to create strong connections between product activities and key Salesforce entities. Activities are tied to leads, and leads are matched to accounts based on the similarity of the lead’s company name, website, and email domain to respective account data in our database.

Product activities are also linked to contacts, each automatically tied to a single account. Through these parent-child relationships, we can query all product activity performed by multiple users working at the same company and aggregate that activity at the account level, giving us visibility into overall account usage.

Since we offer a 30-day platform free trial, product activity can be a powerful sales tool. Using a Salesforce custom metadata type we dubbed “PQA Criteria,” we set thresholds defining what amount of activity constitutes a “Product Qualified Account.” Once an account meets the criteria, Salesforce alerts the Sales team to evaluate these accounts for potential opportunities. By storing our criteria in custom metadata instead of hard-coding it, we can easily adjust the thresholds to respond to emerging trends and better identify activities that indicate a strong likelihood of purchase.

This integration is brand new, but we’re already starting to realize huge benefits. The unified view of product interactions across leads, contacts, and accounts lets our Sales and Customer Service teams extend a hand when the customer needs help. And the alignment created when product and engineering, sales, and marketing all know how customers use our product is invaluable.

If you’re interested in integrating your product activity data into Salesforce—or any other data, anywhere, for that matter—talk to one of our data integration experts today.