With ZoomInfo data such as company size, industry, geography, technology usage and buying signals, lead scoring is an efficient, resource-optimized, automated process. With ZoomInfo B2B data and recurring updates - such as ZoomInfo’s WebSights, Intent, and Scoops data - analysts run sophisticated lead-scoring calculations that enable teams to prioritize their sales efforts by custom criteria, such as best-fit accounts. Identify and Prioritize the Most Promising LeadsĪI tools can use ZoomInfo data to identify the most promising leads from a cohort of potential prospects. Predict Future Sales Trendsīy incorporating accurate firmographic data - industry, company size, location, and revenue - with relevant signals that reflect up-to-date buyer behavior, data teams are able to build AI models that can better predict future sales trends.Ĭombining historical sales patterns and customer profile data with external signals - economic indicators, news and survey data, and buyer intent - results in improved forecasts grounded in both past performance and current market conditions. The beauty of high-quality data is that it paves the way for data modeling to deliver on its promise across a number of vital areas of business, including:Ĭonsider the following AI use cases, illustrating how high-quality business data drives AI innovation, enabling data professionals for a growing wave of interest in AI applications. Here’s how adding best-in-class ZoomInfo B2B data to your data supply chain can further optimize your AI models to produce new data insight, create realistic simulations, and design novel solutions. The good news? With a foundation of the most comprehensive B2B data available, it’s possible to turn those challenges into opportunities with plenty of upside. Harnessing AI requires a strong alignment of incentives across departments, coupled with high-quality data and experienced resources to get the job done. Historically, it’s been difficult to strike a balance between our technical knowledge of AI’s potential and business leader buy-in, especially when a deep understanding of data modeling is not pervasive across a business. Yet as promising as AI looks - Goldman Sachs estimates AI could drive 7% in global GDP growth over 10 years - its application does not come without challenges. That positions data leaders at the heart of this global transformation, ushering in the next era of AI-ready data. With new developments surfacing at breakneck speed, it’s more important than ever to remember that diverse and accurate data serves as the backbone for effective AI models. There’s a growing appetite for artificial intelligence (AI) in business, and for good reason - after years of promise, new AI applications are reshaping how industries operate, from the inside out.
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