How Unified Data Powers Go-to-Market AI Strategies

Kelly Fanthorpe

Kelly Fanthorpe

Content Manager

Business leaders have long known that fragmented data — flowing from disconnected systems, often kept in silos — is a major obstacle to growth, consuming up to 20% of the average IT budget. 

But in the age of artificial intelligence (AI), disconnected data can cause havoc across a company’s entire go-to-market operation, leading to missed growth opportunities and wildly incorrect decision-making. 

The solution? Businesses must integrate data from first-party, second-party, and third-party sources, creating a seamless flow of information that fuels smarter, more targeted go-to-market strategies. 

Here’s how industry leaders from ZoomInfo, Google Cloud, and Bobsled approach the critical work of unifying data to help their teams and partners build customer-centric AI strategies that drive real results.


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The Challenge of Siloed Data in AI

The explosion of AI tools in business has revealed that many companies’ data strategies need an upgrade. 

Russell Levy, chief strategy officer at ZoomInfo, notes that the real power in go-to-market (GTM) AI lies in combining first-party customer data with high-quality data from providers and partners, which can provide a fuller picture and more accurate insights.

“The more data you can feed AI, the more you give it context and enable it to make smarter decisions,” Levy says. And conversely, if your first-, second-, and third-party data remain siloed, your AI-driven insights remain weaker. 

This unified data approach enables AI models to provide more accurate, context-rich insights, ultimately driving more effective go-to-market strategies. 

“Access to the data you need in real time, in one place, is a real game-changer,” says Tom Cannon, head of data ecosystem, partner engineering at Google. “Your AI needs data, and your data needs AI.”

Grounding AI Models with Integrated Data

Another crucial component of a successful AI strategy is the concept of “grounding” AI models. As Levy points out, AI models, particularly large language models (LLMs), can be prone to “hallucinations” — generating inaccurate or irrelevant information when they lack proper grounding in reliable data. 

By integrating diverse data sources, companies can ensure that AI models are working with the most accurate and relevant information available. Properly grounding data is “the key that unlocks the real value of these LLMs,” Cannon says.

Google has recently expanded the grounding capabilities of Vertex AI, its fully managed, unified AI development platform, giving customers the option to ground user queries with Google Search or with third-party datasets from providers like ZoomInfo.

By providing AI models with a robust foundation of integrated data, businesses can improve the precision and reliability of AI-generated insights, reducing the risk of errors and enhancing decision-making processes.

Leveraging Data as a Service (DaaS) for Seamless Integration

The concept of Data as a Service (DaaS) is quickly becoming an important solution for uniting siloed data. 

“As businesses invest in developing their own AI initiatives, they increasingly need access to the underlying data from not only internal, but external sources as well” says Jake Graham, founder and CEO of Bobsled, a data sharing company. “That’s why we’re seeing leading data-driven companies like ZoomInfo invest in building data-as-a-service experiences that make working with its data as easy as navigating a modern software app.”

Sneh Kakileti, a product management VP at ZoomInfo, emphasizes that businesses are no longer running their operations solely within traditional CRMs. Instead, they are leveraging cloud-based platforms and data-sharing services to centralize their data and drive more sophisticated, data-driven go-to-market strategies.

“We wanted to bring the value of our data asset to where customers actually ‘live’ and are making those data-driven decisions,” Kakileti says. By adopting a DaaS approach, companies can seamlessly integrate various data sources into a unified system, making it easier to leverage AI tools and generate meaningful insights.

Separating Hype from Reality in AI and Data Strategies

Finally, it’s important to know how to distinguish between hype and reality when it comes to AI and data strategies. With the rapid advancements in AI technology, it’s easy for businesses to get caught up in the excitement and invest in tools that promise more than they can deliver.

By uniting data and grounding AI models in reliable information, companies can avoid the pitfalls of over-hyped technologies and instead drive real, measurable results.

The Big Takeaway for Sales and Marketing Professionals

For sales and marketing professionals, the emergence of AI has underscored the critical need to break down data silos and adopt unified data strategies. By integrating first-party, second-party, and third-party data into a single, cohesive system, businesses can leverage AI tools more effectively, generating more accurate and actionable insights.

As AI continues to evolve, the ability to harness integrated data will become an increasingly important competitive advantage. Sales and marketing teams that prioritize data unification and adopt a data-centric approach to AI will be better positioned to navigate the complexities of today’s market and drive more effective go-to-market strategies.

The future of AI-driven sales and marketing lies in the power of united data. By embracing integrated data strategies and leveraging the right AI tools, businesses can unlock new opportunities for growth, efficiency, and success.

At ZoomInfo, we’re excited to bring our customers along as we explore the limitless possibilities of GenAI and Data as a Service. Learn more about our partnership with Google Cloud and how you can get instant insights from your data securely and at scale.