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As data plays an ever-increasing role in today’s B2B organizations, both marketing and sales operations professionals are in position to solidify their place as critical revenue drivers.

As outlined in the ebook, The Rise of Revenue Ops, there are four key pillars to revenue ops: Management & Strategy, Process Optimization, Technology & Project Management, and Data & Analytics. In this article, we’ll focus on best practices for the fourth pillar, Data & Analytics.


What does Data & Analytics mean through the lens of B2B ops?

Data and analytics, through the lens of B2B ops, is about getting the right information to the right people, whether that’s marketers or salespeople. For many organizations, this means getting accurate marketing measurement data in the hands of the right people -- pushing it to marketers when it’s relevant to them and pushing it to salespeople when it’s relevant to them. For more mature organizations, ops needs to move beyond getting merely accurate data and become focused on getting actionable insights that answer meaningful problems.

How can ops ensure proper data governance?

The first action ops should take to ensure proper data governance is to assemble key stakeholders across the marketing and sales teams during key planning phases of building the marketing and sales technology stack and organizational process.

Have the stakeholders agree up front about what is the single source of truth, and have all stakeholders involved in decisions about making changes to the data structure going forward. For example, when changing your attribution model, the VP of Marketing can’t make the decision alone because the change in data affects the sales team as well. Data will only be trusted -- and therefore effectively used -- when all of the stakeholders are in agreement.

Ops should facilitate these meetings and provide expertise as to the effects of technological and process changes with an eye for providing increasingly valuable and actionable data.

What are best practices for data management, stewardship, and delivery?

Proper data management -- accessible, actionable, and accurate data -- can be ensured by creating a single source of truth for both the marketing and sales teams. Not only does that data have to be truthful, it has to be addressing the right problem.

Attribution plays a key role, as it connects marketing and sales data, and lives in the CRM. Even then, the impact of how attribution helps ensure proper data governance depends on how marketing ops configures the attribution technology. For example, first touch attribution data may be accessible, actionable, and technically accurate, but it doesn’t address the right problem. The problem is measuring and understanding the full customer journey, and that requires multi-touch attribution data.

Ops should facilitate figuring out what the true marketing and sales problem is, and then find the best solution to solve that problem with accurate and consistent data.

The next step is for ops to create or facilitate the creation of dashboards for more senior stakeholders. For more junior practitioners, ops should focus more on providing access to the data, enabling them to create their own reports.

C-level, presidents, and vice presidents don’t require the same depth of data that practitioners need, but they do need to be able to understand the big picture -- trends, hitting forecasts, etc. Where the dashboard data comes from should be clear, allowing these key stakeholders to dig in deeper, but only as necessary.

For practitioners who may need to look at the data on a day-to-day basis, ops should facilitate the creation of reports and ensure that the data continues to be accurate and answers the questions that each function requires.

What should ops practitioners keep top of mind to ensure data integrity and accuracy?

Creating a culture of accountability and transparency is invaluable to ensuring data integrity and accuracy. No matter how much ops would like to automate all of the data inputs, some of it will always be self-reported and analyzed. Explain the importance and get everyone to buy in on the importance of data integrity and accuracy, and having it built into the process, will help.

In many instances, technology and process are two sides of the same coin. Take data cleansing, for example. De-duping and cleaning out bad data (incorrect contact information) isn’t a one-off activity; it needs to be built into the process.

Furthermore, advanced attribution models play a role in ensuring data integrity and accuracy, as well. Organizations using multi-touch attribution report being more confident in the accuracy of their data, rating it a 3.41 out of 5 on average, while those who aren’t using multi-touch rate their confidence a 2.73.

What kind of analytics and reporting can help ops improve their B2B marketing / sales efforts? How can ops effectively manage key metrics and align them with goals? What are the best practices for effective marketing attribution?

Full-funnel analytics and reporting is the key to improving B2B marketing and sales efforts, including creating alignment between the two functions. This means enabling marketers to speak in the same language as their sales counterparts -- revenue. Many organizations don’t have the technology or process in place to do this yet, but it should be the goal for ops practitioners. That’s because while measuring marketing performance with opportunities and pipeline is a great improvement on leads and MQLs, measuring with revenue encourages marketers to help with things like sales enablement and other ways to improve win rates at the bottom of the funnel. Marketers who are focused on the full funnel are 119% more likely to report sales and marketing alignment.

Through full-funnel revenue attribution, ops can provide data on key metrics throughout the entire funnel: leads, opportunities/pipeline, and customers/revenue.  This happens by capturing touchpoints from the very first anonymous touch to the last touch that closes the deal. That’s the level of data that B2B marketers need in 2017, and it allows marketers to apply increasingly complex and accurate attribution models (e.g. algorithmic or custom attribution models.)

When considering attribution models, the marketing team’s ultimate goal should determine the appropriate attribution model. If you’re at the stage where the marketing goal is opportunities, use a multi-touch model that ends at opportunity creation (e.g. W-shaped); if you’re at the stage where the marketing goal is revenue, use a multi-touch model that ends at customer creation (e.g. Full path).

“If you’re struggling to figure out what metric(s) to prioritize, think about which is the actual goal and which are just indicators of the goal. Focusing on the actual goal will show ops practitioners how to prioritize technology and process implementation, maintenance, and optimization.”

Dave Rigotti, VP of Marketing, Bizible

How does Data & Analytics affect ops practitioners in the future?

Data is increasingly important to both sales and marketing, which put ops practitioners in a really great place to grow in their company.

Since ops practitioners know the data inside and out, from both a technology and process perspective, organizations will continue to elevate the role, creating a senior management position (e.g. Chief Data Officer) or, alternatively, the next generation of marketing leaders will come from an ops background.


  • Ops needs to focus on getting data that answers the right questions -- spend more time figuring out what the right question is and what data is required to answer it.
  • Everyone should have access to the data and key metrics because it builds a culture of accountability and transparency, but ops should tailor how they communicate data to the specific needs of the stakeholder (typically by level)
  • Align your attribution model to your goals. If you’re at the stage where the marketing goal is opportunities, use a multi-touch model that ends at opportunity creation (e.g. W-shaped); if you’re at the stage where the marketing goal is revenue, use a multi-touch model that ends at customer creation (e.g. Full path)
  • Measuring marketing performance with revenue is critical to creating true alignment between marketing and sales

Download the complete ebook, The Rise of Revenue Ops.