World of DaaS Roundtable Recap: The Great Renewal - Reducing Churn and Expanding ACV

At our latest World of DaaS roundtable, data leaders discussed the evolving challenges of retaining and expanding enterprise customers in an increasingly competitive data economy. The conversation explored how companies are mitigating churn, proving ROI, and deepening customer value in the era of AI.

1. Data Quality Is Still the Bottleneck

Participants agreed that customer churn often starts with inconsistent or misunderstood data quality. When integrations fail or datasets underperform against internal expectations, renewal risk rises sharply.

As one executive noted, “If the project fails before our data reaches production, that customer is gone.” Others emphasized the importance of embedding deeper quality assurance and integration support into onboarding: “Our job doesn’t end when the data is delivered—it ends when it’s delivering value.”

Several attendees observed that customers continue to underestimate the complexity of harmonizing internal and external datasets. Even sophisticated organizations struggle with metadata management, lineage tracking, and version control, all of which directly affect satisfaction and renewal.

2. ROI Remains Difficult to Prove

A recurring theme was the difficulty of translating data’s theoretical value into measurable ROI. Many vendors are now reframing success around speed to insight and business impact, not just delivery metrics.

One participant noted that clients “don’t always know what success looks like” and often require structured hand-holding to connect data outputs to revenue or cost savings.
Others described shifting toward prescriptive support: “If we can guide them to one clear win in the first 60 days, they’ll stay for years.”

Even among companies with low churn, participants reported increasing pressure on renewal pricing as customers scrutinize data ROI in tighter budget environments. Several observed that 2023–2024 brought “renewal fatigue,” with cost-cutting CFOs re-evaluating every contract line item.

3. External Reference Data Accelerates Retention and Expansion

One powerful antidote to churn is anchoring internal datasets to external reference data—especially for use cases like identity resolution, customer attribution, and operational benchmarking.

As one attendee summarized, “The more reference data you integrate, the harder you are to replace.”
By tying data products to customers’ core systems and daily workflows, vendors build long-term dependency and create natural upsell opportunities.

Several participants discussed building quarterly business reviews and product education into their account plans, ensuring data remains visible and indispensable even as champions change or teams reorganize.

4. Agentic AI Shifts the Focus to Orchestration and Onboarding

AI’s rise has not necessarily increased churn—but it has transformed customer expectations.
Participants described a new wave of “agentic” AI workflows where clients expect their vendors to orchestrate integrations and automate insights, not just deliver raw data.

As one leader put it, “The first six to twelve weeks after a contract closes are everything. If customers aren’t in production fast, they’ll churn in twelve months.”

Companies are responding with more hands-on onboarding models—embedding customer success and solution engineers directly in early deployments, emphasizing quick value demonstrations, and maintaining human-in-the-loop oversight.

The consensus: integration equals retention. Vendors that can operationalize their data faster and with less friction will win.

5. The Future Belongs to Transparent, Relationship-Driven Providers

The roundtable concluded that long-term success in the data market won’t come from locking in customers through legal terms or sheer dataset size—but through trust, transparency, and consistent value delivery.

Participants shared that while automatic renewals and contract protections have their place, they are not substitutes for genuine engagement.
As one executive summarized, “The goal isn’t to trap customers—it’s to make them not want to leave.”

Others pointed to transparency around sourcing, methodology, and performance as a growing differentiator. In an environment where AI hype often outpaces results, clarity and credibility are the real retention levers.

Key Takeaways

• Integration drives renewal. Customers who reach production are exponentially more likely to stay.

• ROI must be demonstrated early. A clear use-case win within 60 days sets the foundation for long-term success.

• Reference data is retention fuel. Anchoring internal systems to external data builds reliance and trust.

• Agentic AI requires orchestration. The new expectation is hands-on, human-guided implementation.

• Transparency wins. The most defensible vendors combine scale, compliance, and authentic relationships.

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