ABM 2.0 – Combining Intent Data with AI to Predict Buyer Behavior

Account-Based​‍​‌‍​‍‌​‍​‌‍​‍‌ Marketing has always been a method that is precise in nature. Target effectively the right companies. Tailor the customer journey. Gain higher conversions. Still, the most significant performance upgrade was with ABM 2.0, where intent data and AI combine to not only figure out what buyers will do next but also give marketing teams the capability to carry out the action at the absolutely right time. According to Gartner, 75% of B2B organizations will shift from traditional lead-generation models to intent-driven ABM programs by 2025. Today’s buyers do investigate by themselves and remain hush-hush. They check the product or service, ask a friend for an opinion, and at the same time, consume digital content long before they will actually take the step of filling out a form. The research on B2B markets reports t

Every buying event is followed by a trail of digital footprints. If someone is reading a cybersecurity case study, comparing cloud solutions, or is on the pricing page, it all reveals the fact that that person has an interest that deserves to be given proper attention. Studies of the market state that businesses that employ intent data in ABM have an engagement rate that is 50% higher than the engagement through static targeting. The main reason for that is that intent signals are the ones that help you identify the people who are actually thinking about the solution, rather than the ones that simply fit the ideal customer profile. Forrester found that intent-data-activated ABM programs generate 2.5× higher deal-close rates compared to ICP-only targeting. First-party intent is about the users’ actions on your website, emails, and gated co