RevOps: Metrics are How you Make Data-driven Decisions Happen

Guy Kerem, Senior Data Analyst
Guy Kerem
Senior Data Analyst

For Revenue Operations (RevOps), data is everything. No matter if you’re a solo CRO, a small team or an enterprise division, the challenges are the same: 

  • How can we use data to increase efficiency and remove friction in our revenue process? 
  • How do we convert data tables to insights that inform decisions and GTM strategy? 
  • In short, how do we make revenue more data-driven? 

In this post, we'll demystify the powerful and often underestimated role of metrics in creating lean, data-driven revenue organizations. 

If you're curious about the secret sauce that makes modern RevOps tick, and eager to discover how to leverage metrics to make teams more aligned and action-biased, then dive right into the world of metrics-driven RevOps right here. 

But first…

RevOps: Metrics are how you make data-driven decisions happen

What is Revenue Operations?

RevOps is a modern approach to managing and enhancing business revenue activities across the customer journey. In an increasingly competitive and unpredictable climate, businesses strive for efficient, quality execution at high speed. RevOps offers the alignment, accountability, and adaptability required to achieve these goals by synchronizing sales, marketing, and customer success, breaking down silos, optimizing workflows, and harmonizing the various tools and systems that are part of the revenue stack.

RevOps and Data

One of the core missions of Revenue Operations is to make revenue more data-driven. Revenue Analytics, one of the key principles of a well-executed RevOps Strategy, focuses on data alignment (notably between sales and marketing), defining clear goals, monitoring performance, and continuously generating and distributing actionable insights. 

Data is key to achieving one of the missions of the RevOps team: optimizing the way people, products and processes work together to deliver value to customers and generate revenue for the business. So how can RevOps teams truly “move the needle” here? 

The short answer: Metrics. 

The slightly longer answer: Robust RevOps Metrics that make data more accessible, accurate, and actionable, helping the organization become more data-driven than ever.

Understanding RevOps Metrics

What is a metric?

A metric is a framework for comparing different measures in order to enable comparisons, put measures in context and find relationships. 

For example, if we closed 10 deals this quarter, that’s one measure - just a number - but the number of deals over time is a metric - a signal that shows us how the business is doing. 

The most common metric signals are measures over time, between-group comparison and share of target or quota achievement. Essentially, metrics put results in context and help us answer questions like: 

  • How is our performance changing over time? 
  • How well are we hitting our targets? 
  • Which segments or groups are performing better than others? 

Good metrics deliver data to decision-makers in a more accessible and actionable form, making them invaluable assets for RevOps teams to build, maintain and share.

What type of metrics are most useful for RevOps?

There are many RevOps metrics modern businesses have to track, these will usually fall into the following categories:


Knowing the amount of revenue generated and retained is essential for any business, teams must employ metrics to reliably report and analyze revenue: 

And more…


Optimizing the revenue process means reducing friction and increasing efficiency. RevOps teams monitor conversion rates metrics across the funnel and pipeline to find successful strategies and fix bottlenecks:

And more…


A lot of things need to happen to generate revenue, tracking and monitoring activity metrics is crucial for understanding what is happening and what’s changing over time: 

  • New Leads
  • Number of Calls / Meetings / Emails
  • New Opportunities

And more…

RevOps Analytics with Metrics

Metrics provide decision makers and teams across the organization access to well-defined, meaningful signals, instead of relying on repetitive, variable queries that often end up being incomplete or contradictory. 

RevOps teams that demonstrate business analytics best-practices focus on creating the set of metrics they need to track KPIs, evaluate performance and investigate root causes that are critical to their business success.

Data driven decisions

KPI Tracking

Key performance indicators (KPIs) help business leaders understand the overall performance of the business. Tracking KPIs is crucial for accountability and aligning efforts across the organization as well as for reporting purposes. 

Example: Tracking and regularly reporting on ‘New Pipeline’ focuses the organization on sourcing more new opportunities and alerts to sudden changes in volume.

Evaluating Performance

Metrics are often used to assess the effectiveness and efficiency of different segments, groups, owners and more. By breaking down the metric into groups, leaders and users can quickly compare and evaluate performance across metrics. This can highlight the areas that need improvement as well as those that are exceeding expectations and should be emulated. 

Example: Breaking down the ‘Opportunity Win Rate’ metric by ‘Region’ gives a clear view of which geographic regions are most efficient in closing deals.

Investigating Root Causes

To successfully optimize different business processes, RevOps employ different metrics to locate faults that need addressing or advantages that can be leveraged. By drilling-down into the root causes of underperforming or excelling metrics, RevOps teams can direct the attention and efforts of decision makers to where they are needed and can be most effective. 

Example: Drilling down into the different components of ‘Net Dollar Retention Rate’ can uncover if low results are caused by high churn (“leaky bucket”) or unsuccessful upsell strategy.

Implementing metrics effectively

A RevOps team that correctly builds and maintains key metrics is much more effective at managing and monitoring the revenue organization as a whole. Metrics are tools to make RevOps’ lives easier and more successful, and just like any tool there’s a correct way to utilize them. 

Metrics must be carefully defined, maintained and communicated in order to be effective.

  • Definition: Metrics must measure what they’re supposed to. For the numbers to reflect reality, the raw data must be complete and the calculation precise.
  • Maintenance: As the organization develops and changes the tools and processes involved in revenue generation, so must the metrics. Adding data sources or updating calculation logic is crucial to keep metrics relevant.
  • Communication: Even if we build and maintain accurate metrics, they’re only as useful as the number of decisions they inform. RevOps’ ability to impact the business depends on making the right metrics known and accessible to all the necessary functions and decision-makers.

How Metrics make teams more Data-Driven

Everyone wants a data-driven business, but how do you get there? The general opinion was that a data-driven business is a direct result of high investment in CRM, data quality, hygiene and tools. However, attitudes have shifted in recent years. The current mindset is best reflected in the saying: “Data culture eats data strategy for breakfast”. This approach states being data-driven is a lot more about how well people in your organization access, trust and consume data rather than a matter of technical infrastructure and data quality.

A recent BARC Data Culture survey found companies achieved improved decision-making, process improvement and cost reductions through investing in their data culture. In the survey, “Data Access” was considered the most influential initiative for achieving better data culture and realizing the benefits of a data-driven organization.

Metrics are the key to unlocking this “Data Access” and building data culture in the revenue organization. They do this by removing the three main obstacles to “Data Access”.

Data is siloed

Good business metrics are “defined-once and used-everywhere”. By defining and aligning on the inputs and calculations of a central set of metrics, teams avoid contradictory results and decision makers get one reliable source of truth for their questions. 

Metrics make data more connected and open to collaboration.

Data is missing context

Even accurate data is useless if it’s incomplete or missing context. Decisions are often delayed or blocked because decision-makers ask for supplementary data or analysis to ensure their interpretations and judgements are sound. Metrics readily provide the flexibility and context needed in order to make data more meaningful and clear-cut to decision makers (e.g. trends over time, significant changes, group comparisons, etc.). 

Metrics make data more transparent and meaningful.

Data is complex

Finally, data can be extremely messy and complicated. By clearly defining metrics that are tied to the business’ goals, RevOps teams provide a much more accessible interface with data. Decision makers are equipped with metrics they can rely on to get meaningful answers to their business questions, without depending on analysts to translate a question to a manual query. 

Metrics make data accessible to anyone and simple to understand.

In conclusion

The purpose of RevOps is to streamline revenue activities throughout the customer journey by aligning processes, boosting efficiency, and fostering data-driven decision making. 

Metrics are the key to achieving these objectives; helping track KPIs, assess performance, and identify root causes. By implementing a metrics-driven approach, companies are better positioned to foster a data-driven culture, leading to improved decision-making, continuous process improvement, and, ultimately, increased revenue. 

RevOps teams must prioritize developing robust metrics, integrating them effectively for more accurate, aligned, and actionable data, leading the charge towards a more data-driven business.

Discover how to make data-driven decisions

CRM Data Hygiene: Best Practices for Maintaining Clean and Accurate Customer Data
Building an Effective Revenue Operations Tech Stack: Key Components and Best Practices

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