The smartest way to approach AI in B2B, as suggested by SiriusDecisions

Monica Behncke wasn’t necessarily thinking about the potential of AI in B2B when she let her teenage son plan their vacation at an amusement park, but she was quick to recognize the parallels. Speaking at last week’s SiriusDecisions Summit Canada in Toronto, the research firm’s VP and group director noted how amusement parks involve a bevy of choices involving the selection of rides, restaurants and amenities, ways to access the attractions and more. Similarly, those making enterprise purchases can be almost paralyzed with the variables to consider. AI in B2B helps address this problem, she said, by helping organizations make use of more data, as well as seeing the connections within all that data. “It’s a way of knowing your buyer and really understanding them beyond a title,” she said. “It’s also a way to better gauge performance of what’s working — or not.” Some examples include automating processes, especially in repeatable areas such as contract renewals or approvals, as well as illuminating what Behncke described as “best-fit” market segments. “We all have limited resources and energy and people. You don’t want to waste that in places that aren’t really a good fit, but it can be really hard to tell what is the good fit,” she said. “How do you know if (customers) are looking to buy? With more processing, they can look at deals won and lost and template the wins based on a profile AI creates.” AI in B2B can also match third-party intent data to the segmented market, Behncke added. That means when those companies give off the right signals — such as web searches, third party analyst information requests and so on — a company can see that and increase marketing activity accordingly.