3 ways MOps can bridge the gap in marketing analytics

Marketing has always been challenged to demonstrate impact on pipeline and revenue — and it hasn’t gotten easier. Success metrics have evolved beyond impressions, opens, and click rates, with privacy changes like Apple iOS 15’s open-blocking feature pushing marketers to rethink impact measurement.

New martech tools focus on measuring marketing impact, tracking customer journeys and analyzing sales funnels. They enable discussions on direct vs. influenced pipeline, multi-touch attribution and AI and machine learning. Organizations are also adopting data warehouses and CDP structures for data aggregation and analysis using tools like Tableau and Power BI.

However, some data analyst teams working within data visualization platforms still lack the expertise needed to understand marketing impact. This is a challenge for marketers who must demonstrate campaign ROI but lack data proficiency. Such knowledge gaps keep these powerful insights from being brought to light.

Marketing operations: The hidden superpower

While often overlooked, marketing operations (MOps) teams hold vital expertise in proving marketing ROI. They shape lead scoring, lifecycle models and campaign success metrics. 

These platform experts manage systems, data integration and campaign tracking. Unfortunately, this valuable knowledge often stays confined within the MOps team, missing broader utilization.

To bridge this gap, there must be better alignment within the organization. Alignment isn’t limited to sales and marketing — it extends to marketing operations, sales operations, and data science. Collaboration empowers marketing operations to support and educate data science teams to advance marketing analytics within a data-driven framework.

Dig deeper: How to align B2B sales and marketing teams

3 key areas for marketing operations support

Here are three ways MOps teams can help bridge the knowledge gap, delivering valuable insights that benefit the entire organization.

1. Development of a data glossary

MOps can create a data glossary focusing on essential marketing terms, such as scored leads, MQLs, qualified leads, and source information. For many marketing automation platforms, system default glossaries can be an easy starting place.

MOps documentation may also have many of these terms outlined. For instance, the details of why and how a source value may be set together with what behaviors may move a lead to a “score qualified” status and what that means in the handoff to sales. 

Documentation around a lead lifecycle model and how that aligns with CRM stages for leads, accounts, and opportunities is key to analyzing funnel health and velocity. If a team doesn’t have these processes documented, working with your sales, sales operations and data science teams is a great place to get started.

2. Alignment 

Marketing operations leaders bridge knowledge gaps between marketing, technology, and data. They can translate marketing terms into data language for data science teams to apply in models. 

The teams must align on the definition of MQL, marketing influence and success. This ensures that when marketing talks about “influence on pipeline,” it is understood and agreed upon across the business. 

These terms can then be applied across standard reporting that stakeholders can access – keeping teams on the same page. Regular meetings between MOps and data science teams also help to promote collaboration, educate analysts on marketing goals and drive insights for ROI and revenue.

3. Continued growth of the marketing reporting machine

Members of a MOps team specializing in data reporting and analysis, often referred to as marketing intelligence operations, also play a vital role. They bridge the gap between data science and marketing expertise, ensuring that marketing reporting receives the attention it deserves. 

Providing career development opportunities in BI tools or SQL can transform them into an internal marketing reporting powerhouse.

Turning marketing data into revenue-boosting insights

If your data science team struggles with marketing-specific models and reporting metrics, look to your MOps teams for translation and support. This enables your organization to measure marketing effectiveness and impact on revenue accurately. 

Bridging these language and knowledge gaps can help to generate insights that can be used to unblock stuck pipelines, accelerate deals and generate wins for everyone — not just for marketing colleagues or for the business as a whole.

Dig deeper: How marketers can measure success