For most organizations, machine learning is no longer a choice. Open source machine learning algorithms, libraries, and platforms are common today, leveling the playing field and making machine learning impossible to ignore. In the B2B world, machine learning can produce insights more quickly, consider more data when doing so, and avoid issues created by human error. But for organizations to stay competitive, human expertise and intelligence still play a big role. Human analysts can make more abstract and insightful connections, recognize biases, and provide actionable recommendations that take into consideration an entire business ecosystem, rather than just the data being analyzed.
At Dun & Bradstreet, we have been using machine learning coupled with the strength of our analytics team for more than 25 years to give our customers a distinct business advantage, whether they are using our solutions for their marketing efforts, risk management, or customer discovery initiatives. From improving our scores and ratings to identifying specific industries that can benefit from new analytical methodologies, we are constantly on the cutting edge of business technology. We strive to improve both the quality and quantity of the business decisions our customers make daily and, by extension, improve business practices worldwide.
When a company can accelerate time to value with its marketing efforts, increase precision for better decisions with its risk management, and know its customers better when seeking company insights, it can improve how it does business across the organization.
To learn more about how Dun & Bradstreet and our work with machine learning can help your business, please download our ebook Machine Learning for Superior Analytics.