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Revenue Operations

Why Marketers Don’t Understand Their Salesforce Metrics

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Joe Schattschneider, Senior Consultant for Marketing Data Strategy at CaliberMind, joins Camela Thompson to dig deep into the often tangled web of Salesforce metrics, data alignment, and cross-departmental data confusion. 

From understanding the distinct perspectives of CEOs, CMOs, and sales teams to optimizing campaign structures for cleaner reporting, this discussion provides actionable strategies for RevOps pros to bridge the gap between marketing and sales data.

Executive and Department Perspectives on What’s Important

CEOs are laser-focused on profitability and growth, seeing every dollar spent as an investment needing a quick return. CMOs, on the other hand, are all about engaging those elusive buying committees and nurturing thousands of interactions long before sales even steps in. 

Meanwhile, VPs of Sales are living in the now, obsessed with hitting their numbers and feeding their teams a steady stream of qualified leads. RevOps must juggle these priorities and ensure everyone gets the data they need to succeed without losing sight of the big picture.

“CEOs care about profitability and growth, CMOs focus on buyer engagement, and VPs of Sales just want to hit their number. ” — Camela Thompson

Jump to clip to hear more about department perspectives

Marketing vs. Sales Data Structure

Marketing automation systems and CRM platforms speak entirely different languages, and that’s where the confusion starts. Marketing systems, like Marketo, tend to focus on every tiny interaction—whether it’s a webpage visit or a form fill—while CRM systems prioritize account-level data and direct actions that are more likely to convert. 

The challenge for RevOps is translating these distinct data structures into a cohesive strategy that both marketing and sales can rely on. Marketers are pressured to justify every ad dollar while sales teams need to understand the actions that directly influence conversion.

Jump to clip to learn how marketing and sales systems view data differently

The Hidden Challenges of Campaign Hierarchies

Campaign hierarchies in CRM systems often look neat on the surface but can be a nightmare when it comes to reporting. Enterprise companies often stack campaign layers upon layers, creating complex hierarchies that are nearly impossible to manage effectively. 

The more layers you add, the harder it gets to report accurately and make sense of the data. RevOps professionals need to be wary of over-complicating campaign structures, as it leads to confusion and inefficiencies. Instead, simplify and streamline wherever possible.

“Unless you're using campaign hierarchy perfectly, you're just introducing more risk and more reporting challenges.” — Joe Schattschneider

Jump to clip to understand why you shouldn’t use campaign hierarchies as a folding mechanism

Flat Data and Why It’s Best for Reporting in Your CRM

A flat data model is the secret sauce for better reporting and data accuracy in CRMs. Instead of creating complex, multi-layered campaign hierarchies, use custom fields on the campaign object. This not only simplifies data management but also makes it easier for sales teams to understand what actions prospects are taking. The flatter the data structure, the easier it is to generate clear, actionable reports that everyone in the organization can use effectively.

Jump to clip to hear about how to build a flat data model

Best Practices for Campaign Structures

When it comes to campaign naming and structuring, the focus should be on creating campaign names that clearly communicate to the sales teams which action was taken and how likely it is to convert.

Member statuses within campaigns should be standardized and used consistently to track interactions. By adding data to the campaign member, you have one place to see the asset and the UTM parameters. It keeps things from getting messy.

“Your campaign name should tell sales exactly why they should follow up—no cryptic codes, just clear, actionable info.” — Camela Thompson

Jump to clip to learn how to support sales without marketing losing important data

The Key to Prep for AI/ML Models: Consistent Data Structure

As AI and machine learning become more integral to operations, consistent and standardized data cannot be overstated. AI models rely heavily on clean, well-organized data to deliver accurate insights. Without standardized data structures, even the most advanced AI tools will struggle. For RevOps professionals, this means doubling down on data consistency and ensuring that all inputs are reliable and standardized.

“Garbage in, garbage out has been a thing forever. It is so much more important when working with AI.” — Joe Schattschneider

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Importance of Sharing Systems Knowledge Across Departments (46:28 - 50:59)

Different departments view and use data in unique ways, and it’s up to RevOps to ensure that everyone understands how these systems work together. By fostering better communication and knowledge exchange across teams, RevOps can help create a more cohesive and efficient data strategy that benefits the entire organization. Understanding these diverse perspectives not only improves alignment but also enhances the overall effectiveness of the company’s data operations.

Jump to clip to learn about knowledge exchange across team

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