D&B Hoovers is a sales intelligence and revenue workflow platform that helps organizations identify, prioritize, and act on buying signals. By combining trusted company and contact data with buyer intent, website engagement insights, trigger events, and AI-powered assistance, D&B Hoovers helps revenue teams uncover opportunities sooner and make more informed decisions throughout the sales cycle.
Built on the Dun & Bradstreet Data Cloud, D&B Hoovers provides comprehensive business intelligence, including company profiles, corporate family structures, decision-maker contacts, industry information, financial insights, company news, and market intelligence. Advanced search and segmentation capabilities allow users to identify high-potential accounts and build targeted prospect lists based on business characteristics, growth indicators, and buying signals.
D&B Hoovers integrates into existing sales and revenue workflows, helping teams reduce research time, prioritize outreach, monitor account activity, and engage buyers with greater relevance. Real-time business triggers and account intelligence help organizations understand changing customer needs, identify opportunities, and focus efforts on the accounts most likely to convert.
Whether supporting prospecting, account planning, pipeline generation, or revenue operations, D&B Hoovers provides the trusted intelligence and contextual insights needed to help teams work more efficiently and drive better business outcomes.
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Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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Gong
Gong is a robust AI-powered revenue platform that enables businesses to centralize their revenue workflows and optimize engagement strategies. It integrates with existing CRMs, providing in-depth customer insights, accurate forecasting, and improved sales execution. Gong's platform supports teams by offering data-driven intelligence on customer interactions, eliminating redundant tasks, and improving productivity. With Gong’s tools like Gong AI and Gong Data Engine, companies can streamline operations, enhance sales coaching, and drive business outcomes more effectively.
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Backstory
Backstory is an AI sales intelligence and pipeline management platform that helps revenue organizations analyze opportunities, forecast outcomes, and determine what actions to take next. It integrates with CRMs, email systems, calendars, meeting platforms, and other sales tools to automatically capture customer interactions and connect activity to the appropriate accounts and deals. This automated activity capture reduces the need for representatives to manually log meetings, calls, contacts, and engagement data. Backstory uses AI to evaluate deal health, engagement patterns, historical wins, stakeholder coverage, potential bottlenecks, and other indicators that may affect close likelihood. Sales teams can identify at-risk opportunities, uncover growth potential, and understand why particular deals are more or less likely to progress. Stakeholder mapping shows who is involved in an opportunity and highlights missing contacts or relationship gaps that could influence the buying process. AI coaching and deal-specific recommendations provide sellers with suggested next steps based on buyer activity, deal context, and established sales patterns. Forecasting, renewals and retention analysis, pipeline management, and account activity intelligence give managers a broader view of current and future revenue performance. Backstory is designed for sales teams that want to make pipeline decisions using continuously updated engagement data rather than relying primarily on manual CRM updates and rep judgment.
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