A Framework for Trusting AI Market Signals in B2B. - Ep.26 Said Differently

#b2bmarketing #marketresearch #marketintelligence #productmarketing #b2bstrategy #competitiveintelligence #marketingai #businessintelligence A Framework for Trusting B2B Market Signals Driven by AI B2B Practitioners and Product Marketers who previously had to rely on DIY methods and opinions to gather signals about buyers, customers, engagement, objections, competitors, messaging sentiment and more are now awash with options. AI is able to gather, analyze, and recommend at a scale and speed never seen before. Analyst firms like Gartner are producing new research guides to help B2B teams make sense of it all. In this episode of Troupe’s SAID DIFFERENTLY podcast, host Jennifer Sikora and guest Constantine Limberakis, founder and expert product marketing principal at Liberis Consulting, talk through frameworks to help teams determine which market signals sources to trust and how to prioritize the ones that matter. They also cover why human intuition still matters a lot when it comes to turning signals into actions that shape the business. Key moments in the discussion: 5:13 = Product marketing has always had a lot of opinions thrown at them, but now there are many options to access data that didn’t previously exist at scale. What are sources of market signal that Product marketers can now access? 8:17 = How do you think about what market signals to trust? Constantine looks at three key factors: Time proximity of when that data was collected, scale and statistically significant sample of the data, and the context in which it was collected to give it meaning. 12:47 = While AI tools reduce the difficulty in capturing this signal from data, prioritizing where to focus also becomes a challenge. What’s important to pay attention to vs. seeing it all as just overwhelming noise? Constantine likes to use AI to help find patterns across sets of signals, and also contradictions to may be important to look more closely at. “Use it as a feedback mechanism that we can go back and forth with… not just analysis on your own.” 16:50 = Example of combining data sets from multiple signal sources to address issues in customer retention and expansion. Combining product analytics from Pendo Novus and messaging intelligence from Troupe. 20:34 = The “Socratic method” not just in interacting with your AI, but also working across your GTM teams to vet and determine the best data sets and signals that can be brought in for any particular challenge. 22:45 = Recommendations on how to navigate all these signals include staying focused on current business challenges and strategy. You can’t address all the signals all the time. Also, look for agent-based solutions or automations that can help you monitor on your behalf and alert you when something may need attention. 25:27 = Opportunity for Product Marketing to use this to elevate their strategic value to the organization, because they can take the lead in reading the signals, finding proof points, and making recommendations back to the business vs. just simply being a taskmaster. “This is the direction that I think we should go because of all the different things I’m hearing from the different parts of the go-to-market team.” Thank you to guest Liberis Consulting: https://liberisconsulting.com/ Guide for Measuring Messaging Signal: https://www.troupe.ai/measuring-messa... Credits: Troupe.ai for sponsorship: https://www.troupe.ai Graphic and production support: 24 and Up Music: https://pixabay.com/users/backgroundm...