How Miro's RevOps Team Redefined Data Empowerment While Navigating Hyper-Growth

The Challenge: Rapid Growth’s Double-Edged Sword

Miro’s RevOps team was a victim of its success.

As their customer base and team grew exponentially throughout the pandemic, so did the scale and complexity of their data workflows.

Throughout their rapid growth, the team grappled with managing data from multiple systems and standardizing reporting structures as their data volumes grew, making it more challenging for the team to deeply understand Miro’s sales funnel and processes.

“We didn’t want to create blindspots as a result of trying to aggregate and analyze increasing volumes of data from multiple systems,” Miro’s Head of Go-to-Market (GTM) Strategy, Alexander Bugajski, recalls. The team was forced to regularly generate bespoke analyses to navigate the multifaceted nature of the business. And then, these analyses would quickly become obsolete due to the speed at which Miro was growing.

“Our capacity was maxed out,” said Alex. 

Miro’s RevOps team needed a tool that could seamlessly aggregate data from various sources, automate their ad-hoc analyses, and create reusable data products for their stakeholders. And for Alex, spreadsheets — with their flexibility and ease — were the preferred platform.

“I wanted to continue using spreadsheets given the rapid pace of change at Miro. There wasn’t time to formalize things. And I didn’t want to add another SaaS tool in our current stack,” he stated, hinting at the struggles the team would soon face.

The Solution: Turning the Spreadsheet Into a Core Piece of their Modern Data Stack

The team initially turned to Looker to help automate their workflows. The experience wasn’t ideal due to complications with LookML, Looker’s proprietary language.

“My primary use case with Looker was to craft SQL queries within it. The intention was to then transfer this data to Google Sheets using the Looker-G Sheets connector.” While this wasn’t the most reliable method, it served as a temporary solution.”

Then came a revelation: What if there was a tool that directly syncs Snowflake and Looker with Google Sheets?

His search led him to Coefficient.

“The realization that my spreadsheet could directly connect to our data warehouse was an absolute game-changer,” Alexander exclaimed. “It was like having my own instance of Snowflake I could pull data out of for my models.”

The Results: A Dynamic Hub for Real-Time Data Modeling and Testing

The adoption of Coefficient marked a turning point in the RevOps team’s operational efficiency and strategic agility. Armed with immediate access to data, they effectively turned Google Sheets into a dynamic sandbox environment for iterative modeling, testing, and validation of real-time data.

“With Coefficient, our spreadsheets became true powerhouses of functionality. Not only could I design and optimize solutions, but I also could manage analytics, data modeling, hygiene reporting, and error checks with more scalability than ever before in Salesforce,” says Alex.

This newfound capability empowered Alex to architect a series of influential models:

Lead Management

By utilizing Coefficient within Google Sheets, Alex created an automated lead router that integrates seamlessly with Salesforce. This system now enables more efficient activity and insights than ever before.

1. Their team cracked the code of lead velocity. Automation workflows now occur upon lead acceptance.
2. Miro thrives on real-time insights. The team’s new SLA tracker offers insights into how leads are moving through the funnel. SDRs review daily metrics about incoming leads, their conversions, and weekly comparisons, so they can continuously fine-tune their processes.

Forecasting

Alex introduced a comprehensive forecasting model for the rapidly growing business, integrating product usage and key account triggers that were not in Salesforce.

Creating and iterating on advanced data pipelines for an ever-growing amount of account and product data would have required hiring and reliance on parallel teams such as business technology, analytics, and data engineering.

Alex and his team needed to remain lean and unshackled.

Coefficient provided a newfound ability to draw data from a diverse set of sources right inside of their spreadsheet. This unlocked Alex’s ability to create a central hub that informed finance on capacity modeling, aided sales ops in quota setting and established a reliable productivity model.

The result has been a significant increase in forecasting accuracy, ensuring aggressive yet achievable scale without overhiring.

Account Routing

To support the company’s land-and-expand model, Alex devised an automated account routing system. With roles such as AEs, CSMs, AMs, and SEs constantly evolving, this system auto-fetches data, processes it, and then reroutes the relevant information back to Salesforce.

Initially manual, the introduction of Coefficient transformed it into a self-sustaining workflow. With just an hour of updates each quarter, it efficiently directs the sales team to their respective accounts and has been running seamlessly for over three years.

At this point, the RevOps team was using Coefficient as its centralized reporting hub, eliminating the need for bespoke analyses. With a single source of truth that automatically updates to keep data fresh, the team could strategize with confidence.

Coefficient’s influence quickly extended beyond the RevOps team after other teams became aware of its capabilities. The Go-to-Market team, in particular, found it to be invaluable, benefiting from real-time insights. The team built activity models that track key activity metrics alongside pipeline build. These models automatically refreshed every hour, stack ranking by reps against their targets.

In reflecting upon the journey, Alex encapsulated the evolution poignantly: “I recall the hours spent in the old routines. Today, tasks that once consumed hours of my time each week are accomplished in minutes.”