AI News

Your CEO just decided it was time to send more emails. You have segments and even entire lists that haven’t seen an email in months — or years. Ads and organic social aren’t working like they used to, and suddenly, your CRM looks like the opportunity of a lifetime. Re-engaging dormant email lists can generate […]

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: As AI agents become more capable of comparing products and aiding purchase decisions, how should B2B vendors optimize content and structured data

Direct traffic is often interpreted as a sign of brand strength. When it increases, teams assume awareness is growing and customers are returning on their own. The metric frequently appears in board reports as evidence that people are seeking out the business directly rather than discovering it through search or ads. The logic is simple

A static annual plan is a liability in a zero-click world where AI models update their knowledge of a brand every few weeks. We must move from traffic seeker to authority source quickly. But how? For a few clients, I’m embracing the uncertain future of market behavior by developing a 90-day authority sprint content marketing

Buy-versus-build considerations are interesting martech scenarios. There’s never a clear answer, which makes martech far more an art than a science. At times, there’s also the buy-and-build option to consider. Recently, in an episode of Bloomberg’s Odd Lots podcast about vibe coding, guest Noah Brier, co-founder of Alephic, argued that AI models that produce software

Phone conversations are now one of the most important first-party data sources in modern marketing measurement. As privacy changes weaken traditional attribution signals, conversation intelligence platforms are emerging as a critical layer of marketing measurement infrastructure. Marketers have spent the better part of a decade getting serious about measurement. We’ve built attribution models, invested in

If you’ve been in marketing long enough, you’ve probably lived through a few identity crises. First, we were channel experts. Then we became integrated, growth and performance marketers. Somewhere along the way, someone added “AI” to everyone’s job description and called it a day. Now, we’re entering the era of the full-stack marketer. From where

Most organizations treat AI as a productivity upgrade. The real leverage is in how evaluation criteria are encoded into systems that increasingly shape vendor selection. As B2B buying becomes machine-mediated, CMOs have an opportunity to shape how AI evaluates vendors — and elevate marketing’s strategic influence in the process. B2B buyers are increasingly using AI

Buying AI capabilities to drive marketing is easy. Enabling marketing teams to actually use it independently, decisively, and at scale is far harder. The main culprit? Humans. Marketing teams have always had the same elusive goal: to move at the pace of the consumer. Responding to each customer’s needs in real time, delivering the relevant

HubSpot and Salesforce both recently announced major changes to their partner programs — moves that executives say will improve quality and help partners deliver better AI-driven outcomes. But analysts and partners see something bigger: a strategic reset as both companies compete to remain central platforms in an AI-driven software stack. The changes affect how partners