Survey insights: Why data quality is the key to GTM excellence

High-quality data is essential for businesses, as it serves as the foundation for trusted insights, actionable strategies, and informed decision-making. During Dreamforce, we conducted a survey to assess go-to-market (GTM) data quality. With over 230 responses from sales and marketing ops leaders, the study provided valuable insights into the maturity of GTM organizations and how they managed and utilized their data. The findings revealed some surprising trends in data practices.

Here’s what we discovered.

RevOps data quality: A look at maturity levels in GTM organizations

Question 1. How is your data stored and managed?

The survey highlights varying levels of data management maturity among participants.

• 22% have no standardized data processes
• 60% of respondents struggle with inconsistent and incomplete data management
• Only 16% have optimal data processes

The survey reveals that 22% of participants rely on spreadsheets or sales/marketing automation tools, pointing to less mature data management practices. While 60% have adopted more advanced processes, they still face challenges in maintaining high data quality. In contrast, 16.31% have achieved optimal data management, indicating an effective and efficient approach to data quality within their organizations.

Data quality gaps: Most organizations still have work to do

Question 2. How is your data cleaned?

The survey revealed that, despite many organizations recognizing the importance of high-quality data, more than half still have significant work to do in improving their data management practices.

• 27% of organizations struggle with incomplete and scattered data, hindering effective sales and marketing efforts
• 50.21% of respondents had some data processes in place. They are using both sales automation and marketing automation platforms, but they still can’t fully transform into a data-driven organization
• Only 21.89% of organizations have solid data governance in place, with marketing and sales platforms working in sync, highlighting a gap in achieving true data quality and alignment

These findings underscore the ongoing challenges in data management that organizations must address to fully leverage their sales and marketing efforts.

Funnel management and its impact on data quality

Question 3. How are your leads managed?

Many survey participants revealed that their funnel management processes weren’t optimized.

• 52.36% of respondents reported having immature funnel management processes, needing both reporting and structure
• 36.91% could identify their ideal customer profile (ICP) and use automated reports but struggle with real-time data sharing and multi-touch attribution
• 10.73% are advanced, capable of marketing to individuals, grouping prospects into buying groups, and leveraging their data to identify new opportunities

These findings underscore a clear need for improved data quality in funnel management. Without accurate, real-time data, many organizations struggle to identify their ideal customer profiles, optimize marketing efforts, and achieve full attribution. Focusing on data quality is key to building structured, efficient funnel processes and unlocking new growth opportunities.

Data maturity: From manual mayhem to automation excellence

Question 4. What parts of your funnel are automated?

Insights from the study reveal varying levels of data management maturity among organizations, from early-stage processes with minimal automation to advanced systems that can quickly adapt to new opportunities and compliance regulations.

• 49% of organizations are in the early stages of maturity, with minimal automation. As the company grows, maintaining up-to-date processes becomes increasingly challenging, highlighting the need for more structured data management.
• 37% use one or both sales and marketing automation platforms but still rely on some manual processes, which can impact personalization, outreach, and attribution.
• 12% of organizations are highly mature, with a fully managed and governed database. They easily adapt to new compliance regulations, meet business demands, and pivot quickly to seize new opportunities.

Taking time to automate processes can enhance efficiency and fully harness RevOps data quality for GTM success.

GTM data maturity: Challenges and opportunities for improvement

Question 5. How is reporting managed?

The study reveals a range of GTM data maturity among organizations, from those lacking adequate reporting and historical data to those facing challenges with manual processes and limited automation. A smaller portion has achieved full data maturity, using their data effectively for forecasting and driving informed decisions throughout the funnel.

• 35% of participants either lack adequate reporting and historical data or have limited information for effective ICP analysis and growth strategies.
• 45% indicated that their data is managed manually or only when necessary, and while some reporting is automated to reduce the burden, various challenges remain.
• 18% have achieved GTM data maturity, enabling them to leverage their data not just for historical analysis but also to take actionable steps, make forecasts, and drive data-driven decisions at each stage of the funnel.

The role of data quality in achieving GTM success is crucial. Without reliable, well-structured data, organizations face challenges in reporting, forecasting, and making data-driven decisions at each stage of the funnel.

Unlocking RevOps data quality for GTM success

The health check helped participants assess their data’s reliability, highlighting the importance of maintaining clean, actionable data for optimal GTM strategies. From funnel management to automation, organizations at various levels of data maturity face common challenges: incomplete data, manual processes, and limited real-time reporting.

Achieving high-quality data is key to building structured, efficient systems that drive better decision-making, accurate forecasting, and effective go-to-market strategies. Investing in data quality improvements can help organizations overcome these challenges and unlock their full potential.

Ready to take control of your data quality journey? Take the data quality health check and see where you rank! You’ll get a personalized roadmap to help get your data go-to-market ready!

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