Oracle DataFox provides B2B company data points and milestones/signals to enrich your records, enabling you to easily target the right companies at the right time and personalize every interaction. Oracle DataFox’s data engine leverages AI—a combination of natural language processing (NLP), machine learning, and human-in-the-loop techniques—to automate data collection and aggregation.
In today’s marketing landscape, marketing teams are focusing on account-centric approaches to better target their go-to-market strategies. To succeed, they need to perfectly align on their target accounts and optimize engagement but often struggle as they do not have the proper account data in place.
Enrich lead management database
Prioritize accounts
Personalize marketing campaigns
Unify sales and marketing efforts
Expand campaign footprints
Oracle DataFox combines multiple sourcing methods to deliver scalability and accuracy.
Our data engine uses natural language processing to parse the public web for relevant information and structure free-form text from unstructured content—such as news articles, press releases, government filings, social media, job listings, blog posts, and more. Machine learning locates data anomalies and sends to human analysts to verify accuracy. Proprietary, trained models distill signals down to 68 predefined categories, including leadership change, IPO, funding round, acquisition, new product launch, and more, and delivers them in real time. The human analyst team also reviews many data attributes to ensure accuracy and to improve model results. Finally, these trained models pick out identifiable companies from articles or snippets of text on the web and determine the correct company entity to match that data to, even if company names are ambiguous. All data points are deduplicated and matched to a verified, legitimate company.
If there is a data vendor who specializes in a certain data type, Oracle will partner with that vendor instead of building another, redundant sourcing mechanism. These partnerships ensure the greatest possible quantity of quality of data.
We have used human analysts for years, both to verify data accuracy and provide more training data to feed back into the machine learning models. Our data verification team works to authenticate, validate, and update core data points found on company profiles such as those used for account segmentation and lead routing rules. In addition, the teams work to resolve data anomalies detected by AI-enhanced workflows and implement data enhancement/company addition requests.
Every company profile has the option to suggest an edit to a specific data point. These suggestions, along with requests to add a company, are sent to our human analyst team to verify and correct. Since Oracle DataFox Data Management is used daily by thousands, user contributions create a powerful feedback loop that ensures the data is as accurate as possible.
*Data points enriched on records in Oracle Eloqua Marketing Automation.
*Data points enriched on records in Oracle Eloqua Marketing Automation.
*Data points enriched on records in Oracle Eloqua Marketing Automation.
*Data points enriched on records in Oracle Eloqua Marketing Automation.
*Data points enriched on records in Oracle Eloqua Marketing Automation.
*Data points enriched on records in Oracle Eloqua Marketing Automation.
Oracle DataFox Data Management provides AI-sourced, human-verified company data and signals. This account intelligence platform continuously extracts detailed data on more than 8.5 million public and private businesses while adding approximately 2.2 million businesses annually.
Customers use DataFox’s insightful data to enrich leads, prioritize accounts, refresh and harmonize marketing data, and identify new prospects.
Learn more about Oracle DataFox Data Management capabilities