How Revenue Leaders Are Operationalizing Behavior Analytics — Without Depending on Engineering
If you are a revenue leader at a high-growth SaaS company, your pre-sales funnel analytics are probably fully operationalized. But when it comes to post-sales analytics, chances are you’re nowhere near where you want to be.
We’re still missing behavioral analytics to show exactly how our customers are using our product for most of us. This means no timely insights about churn risk or upsell potential. And if you do have some basic product usage tracking, it’s typically not up-to-date, available at your fingertips or in the apps you need it most — such as your CRM and collaboration channels like Slack.
According to Shreesha Ramdas, GM & SVP at Medallia, the issue is with operationalizing your behavior analytics: “It’s the classic data fragmentation issue that halts the momentum of the growth teams.”
The behavior data you need is usually locked in multiple systems — product usage tracking tools like Mixpanel and Pendo, application databases such as Postgres and MySQL, and data warehouses including Snowflake and Redshift. And, you need help from your BI and engineering teams to stitch it together and operationalize the delivery.
We’ve All Seen This Movie
But this is starting to change. A new class of analytics automation tools is emerging to challenge the status quo. These tools empower analysts and operations teams to build analytics on their own. No programming skills are required.
Here’s How It Works
#1 Connect to Your Systems
Your DevOps or Engineering team provides secure access to platforms where your product usage data is tracked. It’s often spread across multiple cloud platforms, such as:
- Click events — like logins, downloads and shares — are stored in apps like Pendo and Mixpanel.
- Application events — like purchase orders, service calls, and shipments — are typically found in databases such as Postgres.
Your analyst or ops specialist connects the no-code analytics platform to these systems with simple point and click. These analytic platforms often have 100s of integrations to popular cloud apps and databases.
#2 Build Analytics
The analyst uses no-code UI to build visual dataflow to collect data, analyze it and deliver the insights where you need. Anyone with Excel and SQL skills can do this.
#3 Automate & Operationalize
The analyst automates the data refresh — every few mins, every day, every week or more.
Revenue Teams Are Now in Control
The analytics that required specialized engineering skills are now possible to build by the analysts and operations teams on their own. And modern revenue leaders couldn’t be more excited!
“This is a game-changing technology and can usher in a new era of no-code operational intelligence giving momentum back to the GTM teams”, according to Shreesha Ramdas, GM & SVP Medallia.
The revenue teams can finally take their destiny into their own hands while freeing the engineering teams to focus on the core product development. It is a win-win for everyone. Not only that, these tools do not require heavy time or skills investment to see the ROI.
How are you operationalizing your customer dashboards? Drop us your thoughts in the comments or connect with us to chat more!