Evergage’s new personalization algorithm, Contextual Bandit, is designed to leverage artificial intelligence (AI) to process vast stores of data, positioning companies to automatically deliver the most relevant and optimal content, offer or promotion to each website visitor, application user or email recipient.
B2C companies use machine learning for a wide range of use cases ranging from personalized recommendations, intelligent chatbots and hyperlocal advertising, just to name a few. While the number of B2C companies using machine learning is skyrocketing, adoption by B2B companies has yet to take off.
It’s time for B2B companies to get their game on. Here are some of the ways machine learning can make a significant difference for B2B companies.
Three questions encompass everything a c-suite or board wants to know when it checks in with its marketing organization:
Sounds simple, right? You might be shaking your head right now, having full knowledge of the scramble and stress associated with coming to that table with clear-cut answers to those questions.
Artificial intelligence (AI) and machine learning (ML) have long been on marketers’ radars, but it’s only recently that they’ve begun to show up in customer relationship management tools. AI and ML are often viewed with skepticism, but many B2B marketers will discover that these features can enhance their effectiveness in contacting the right leads, closing deals and nurturing client relationships. The underlying fear has been that machines will replace marketers, but the reality is much more promising.
SalesLoft, a sales engagement platform, announced the launch of a new mobile app, machine learning capabilities and a new reporting framework at the company’s annual Rainmaker conference in Atlanta, Ga. The new features are designed to help companies uncover insights and embed intelligence into their SalesLoft platform and CRM to optimize their sales performance and achieve new levels of engagement with prospects.