After years of promise, new AI applications are reshaping how industries operate, from the inside out.
Yet as promising as AI looks — Goldman Sachs estimates AI could drive 7% in global GDP growth over 10 years — it’s also raising a flood of new challenges.
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. Harnessing AI requires a strong alignment of incentives across departments, coupled with high-quality data and experienced resources to get the job done.
The good news? Data leaders can access the kind of real-time, high-quality, AI-ready data that turns those challenges into opportunities with plenty of upside. Here’s how adding ZoomInfo’s Go-to-Market Intelligence to your data foundation can help your team produce new insights, create realistic simulations, and design novel solutions.
8 Data Modeling Use Cases
Consider the following AI use cases, which illustrate how high-quality business data drives AI innovation, enabling data professionals for a growing wave of interest in AI applications.
Predict Future Sales Trends
By 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.
Combining historical sales patterns and customer profile data with external signals — economic indicators, news and survey data, and buyer intent signals — results in improved forecasts grounded in both past performance and current market conditions.
Identify and Prioritize the Most Promising Leads
With ZoomInfo’s Go-to-Market Intelligence and real-time signals — such as WebSights, Intent, and Scoops data — analysts can run sophisticated lead-scoring calculations that enable teams to prioritize their sales efforts by custom criteria, such as best-fit accounts.
With AI, teams can maximize speed and automation for competitive GTM strategies that are interactive and scalable. For example, sellers can be served a prioritized list of target accounts ranked by important buying signals, including intent spikes and announcements of major corporate initiatives.
Hunting down prospects no longer has to be the first thing sellers do in the morning. Instead, AI-powered applications like ZoomInfo Copilot proactively surface the accounts and contacts primed to engage — enabling frontline sellers to reach out when their buyers are ready.
Build More Personalized Marketing Campaigns
Applying AI with a foundation of clean B2B data enables more personalized marketing campaigns, regardless of whether you’re marketing to small businesses or large enterprise buying committees.
By understanding more about a prospect’s behavior and preferences, AI-powered algorithms recommend content, offers, and outreach methods that are more likely to engage each individual with the right messaging at the right time.
Using GTM Intelligence for AI-enabled customer modeling opens the door to new upsell opportunities — critical at a time when buyers are increasingly looking to consolidate tech stacks with comprehensive solution providers.
Predict Customer Churn With Precision
AI-powered models apply customer behavior analysis, usage data, and customer support history to identify at-risk accounts and proactively intervene before it’s too late.
With a data strategy that combines internal customer intelligence with ZoomInfo’s unparalleled account data and real-time signals, teams can create churn models with indicators, which help pinpoint instances like:
- Seasonal or one-time buyers
- Recent installation of a competing technology
- Recent acquisition
With an additional layer of granular data appended to each account, teams can act quickly with a personalized sales strategy.
Create Precision Risk Analysis
MarketSpark, a telecom company that helps businesses replace out-of-date copper wire phone systems, used ZoomInfo’s Company Data Cubes to enrich and expand government datasets, allowing customers and prospects to accurately envision their upgrade needs.
MarketSpark and ZoomInfo worked to create a personalized Data Cube built on comprehensive firmographics like company name, address, employee count, and revenue.
Combining that rich, accurate company data with FCC data on phone systems in Amazon S3 allowed MarketSpark to create an interactive map that visualizes a location-based risk assessment for each prospect, transforming passive data into active insights — both for the MarketSpark go-to-market team and the company’s prospects, who would be unlikely to run a sophisticated analysis on their own.
Data teams can use GTM Intelligence — accessed through sophisticated Data as a Service systems — to create their own versions of this predictive risk assessment, combining ZoomInfo data with first- or third-party data sources to generate fresh analysis and insights with unprecedented speed.
Segment Customers Based On Granular Data
By feeding their AI models ZoomInfo’s comprehensive Go-to-Market Intelligence, teams can develop finely tuned segments based on granular details including changes in technology use, the company’s specific industry, its annual revenue, the number of employees, and even nuanced behaviors like past engagement with campaigns or frequency of purchases.
Leveraging AI models, these data points can be analyzed and synthesized rapidly, ensuring accurate segmentation. By having distinct segments, businesses can further tailor their marketing messages, ensuring they’re especially relevant for each segment.
Next-level segmentation, powered by AI and high-quality data, enables more efficient and effective go-to-market processes with a more detailed understanding of the customer base.
Enable Must-Know Competitor Insights
ZoomInfo’s robust B2B data and AI capabilities enable businesses to discern market shifts, closely monitor competitor movements, and pinpoint potential growth opportunities.
ZoomInfo’s technographic data, for example, allows companies to model and identify prospective integration partners quickly and at scale — enabling them to launch strategic campaigns in collaboration with key partners, or in defense of competitive market forces.
Build a Product Recommendation System
AI models can leverage ZoomInfo’s data to build a product recommendation engine that is accurately aligned with customer behaviors, needs, and preferences. The broad array of data assembled by ZoomInfo creates a multifaceted profile of business interests, behaviors, and characteristics that are not readily available from competing data sources.
Combining a potential buyer’s firmographic data and purchase history, for example, gives product recommendation systems a foundation for understanding where a company is today.
Combining that baseline with intent data, company news, and survey responses adds a new layer of data that can help AI models identify where an account is in the buyer’s journey, enabling recommendation systems to be simultaneously proactive and precise.
GTM Intelligence: the Backbone of AI for Business
Incomplete, inaccurate, or inconsistent data quickly compromises the integrity of even the most cutting-edge AI apps.
Go-to-Market Intelligence, however, provides a critical edge for B2B leaders implementing a wide array of AI solutions — and data leaders who can illustrate the pitfalls of low-quality data will have an important seat at the table when AI strategy is discussed.Your data team is a vital driver of growth and innovation in the era of AI-enabled business. Speak to a data specialist today to learn how data from ZoomInfo’s GTM Intelligence can make the difference in your strategy.