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Ideal Customer Profiling
Keep your Ideal Customer Profile up-to-date
ZoomInfo already makes it easy for you to manually create your ICP in the platform. AI-Generated ICP takes it a step further by automating the process based on your prospecting history. As the market changes and your scoring mechanism needs to follow suit, AI-Generated ICP can create your new ICP as often and accurately as needed.
ICP Matching
Automate customer profiles
Let our artificial intelligence do the heavy lifting. You simply upload a report from your CRM of previously won and lost deals. Behind the scenes, our algorithms will learn which of ZoomInfo’s company attributes are indicative of companies that are your best targets.
Trusted by sellers, proven in pipeline
With AI-powered Copilot, teams cut prep time, book more meetings, and accelerate pipeline - while driving higher win rates and measurable ROI.
3x
Qualified pipeline increase
ZoomInfo acts as an engine that helps us drive key decisions at the executive level. Now that we understand the markets and verticals that we perform best in, we are able to strategically plan and forecast for the upcoming quarters.
86%
Of wins from scored accounts
77% of Xactly's marketing-qualified leads (MQLs) were from accounts that scored an A or B. These accounts also represent 78% of opportunities and 86% of wins.
43%
More likely to qualify
Opportunities at higher-scoring accounts were 43% more likely to turn into qualified pipeline, and on average moved 58% faster through qualification.
ZoomInfo Predictive Modeling — Frequently Asked Questions
What is predictive modeling in ZoomInfo?
Predictive modeling uses historical data and machine learning to forecast outcomes, such as which accounts are likely to convert or be in-market. Models analyze patterns using a range of data, including firmographics, technographics, and engagement signals, to surface the best target accounts or leads.
How does the Account Fit Score work?
ZoomInfo’s Account Fit Score leverages data from closed-won opportunities in your CRM, identifies common attributes such as industry, revenue, location, and more, then scores all available accounts based on how closely they match these patterns. Accounts are categorized as great, moderate, or low fit for prioritization.
What data points are used in predictive modeling?
ZoomInfo predictive models consider hundreds of attributes, including:
Firmographics (industry, company size, geography)
Technographics (technology stack)
Funding, fiscal year, year founded, and more
Engagement and intent signals (for in-market predictions)
Note: ZoomInfo does not publicly disclose the full list of attributes.
Can predictive models be customized or updated?
Yes. Account Fit Score and In-Market Score (IMS) models can be reconfigured at any time. Updates can be made by working with your ZoomInfo onboarding or support team, and changes are effective immediately.
Are multiple predictive models supported?
Currently, only one Account Fit Score model can be active at a time per account. The ability to run multiple is on the roadmap.
How is predictive modeling used in Marketing?
ZoomInfo Marketing includes a Predictive In-Market Score (IMS), assigning funnel stages to accounts based on their engagement and intent signals — including website activity and topic interest. Customers rank their key web pages and select which intent topics to monitor in the model.