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If you’ve led marketing long enough, you’ve lived this moment. You’re in a quarterly review meeting. Revenue’s under pressure, the pipeline isn’t where leadership expected it to be and everyone’s looking for answers. You open the deck and walk through the slides — multi-touch attribution, channel performance, funnel conversion, dashboards glowing with influence. You explain […]

In MarTech’s “MarTechBot explains it all” feature, we pose a marketing question to our very own MarTechBot, which is trained on the MarTech website archives and has access to the broader internet. Question: How might adopting an open semantic data standard like OSI change martech vendor selection and integration RFP processes? MarTechBot’s answer: The adoption

Here’s a question every marketing leader should be asking right now: How healthy are your customer relationships? Not your campaigns, not your channels but the actual relationships.  It’s a harder question than it sounds. Most organizations have spent the last two decades building around channels.   Email had a team. Social had a team. In-store, ecommerce,

Most marketing assumes recognized pain points. Customers know they have issues, so they search for solutions. Your job as a marketer is to position your product as the best answer. But what happens when your innovation solves a problem audiences haven’t recognized yet? When customers are satisfied with the status quo, even though better alternatives

Every CDP vendor says they’re real-time. But marketers don’t buy real-time. They buy outcomes: timely personalization, smarter lifecycle messaging, cleaner suppression, fewer awkward experiences and less wasted spend. In 2026, the gap between real-time claims and real marketing impact shows up in one place: how quickly your CDP can turn fresh customer behavior into updated

AI agents are spreading quickly across organizations. They’re replacing specific components, layering on top of existing systems and introducing something fundamentally new: probabilistic decision-making inside deterministic architectures. The question isn’t whether to use agents. It’s whether you’re deliberately architecting how they operate within your business. Without clear boundaries, complexity scales faster than value. Here’s a

For marketing teams, AI is acceleration. For many customers, it’s a ride to someone else’s destination. Braze’s “Global Customer Engagement Review 2026” paints a picture that should make marketing leaders pause. On the one hand, adoption within marketing teams is nearly universal. On the other hand, consumers remain skeptical about how — and why —

One of the biggest priorities for marketing teams is managing the transition from conventional search to customers and prospects using AI for research. Although SEO remains essential, it’s critical that your brand appears in AI search summaries and chatbot answers. Marketers are being bombarded with advice and recommendations on how to run generative engine optimization

Somewhere inside your CRM is a customer who does not exist. They open emails at impossible hours. They redeem promotions with machine-like precision. They browse product pages across three devices in under five minutes. They convert, unsubscribe, re-engage and transact again. On paper, they look highly active. In reality, they may be a composite of

Most B2B marketing teams underperform because they lack audience validation. We build campaigns on untested assumptions: that buyers are in an active cycle, that they want our content or that 12 emails in six weeks will generate MQLs. We publish, promote and then stare at dashboards and ask, “Why didn’t this land?” Open rates dip.