Leading-edge marketing organizations are shifting both strategy and culture to prioritize data storage and application to produce actionable insights. Results from a recent survey conducted by MIT Technology Review Insights in association with Google showed that “leaders” (companies that have experienced significant growth in revenue or market share) are more likely than “laggard” organizations to…
Savvy marketers in the financial services industry are in the vanguard of early adopters using machine learning (ML) to streamline operations and optimize business outcomes. A survey of 1,419 customers, including more than 150 in the financial services sector, conducted by MIT Technology Review Insights in association with Google, found that marketers in the industry…
Business-to-consumer (B2C) businesses have made it a priority to incorporate machine learning into customer-facing functions, integrating it into sales and marketing. For business-to-business (B2B) companies, however, translating data into actionable marketing strategies can be a more difficult proposition. Selling to organizations invariably requires embarking on a much longer and more complex journey, culminating in an…
A customer’s journey is as unique as her fingerprints—which explains why marketers are harnessing technology to analyze, classify, and reach customers on the basis of which actions they take before they convert. In the pre-digital past, a buyer’s journey was predictably linear; now it can involve numerous searches and site visits, traversing several different devices.…
While digitization has strained the marketing department’s traditional methods and measures in recent years, the function is regaining its energy by plugging into a rich and abundant power source: data. Existing enterprise data, as well as information gathered from engaging with consumers, has become a valuable business asset. With the advent of machine learning—a type…