AI News

Brand loyalty has long been measured through familiar signals like repeat purchases, points accumulated, and tiers unlocked, all of which reflect how people traditionally browse, compare, and return over time. Those systems were designed for a world where consumers actively made decisions at every step of the journey. That foundation is eroding as AI systems […]

Salesforce signed a definitive agreement to acquire Fin, a customer agent vendor formerly known as Intercom, for approximately $3.6 billion. The deal comes only one month after Intercom adopted the Fin name. The company’s core offering is an AI agent that specializes in end-to-end resolution of complex customer queries across channels, including live chat, email,

In MarTech’s “MarTechBot explains it all” feature, we pose a question about marketing to our very own MarTechBot, which is trained on the MarTech website archives and has access to the broader internet. Q: As third-party cookies vanish and B2B journeys grow more complex, what is the role of “Marketing Mix Modeling” (MMM) vs. “Multi-Touch

Move faster. Build faster. Personalize faster. Create more content, launch more campaigns, automate more touchpoints, and prove more value with fewer resources. Now AI makes scaling almost too easy. The CMO’s next advantage lies in knowing which signals matter, which can be trusted, and how to shape growth with those signals. The enterprise is moving

Marketers have spent years asking whether consumers are ready to buy from AI. New research from Invoca suggests that question has largely been answered. The bigger issue is whether brands are ready to support the customer expectations AI has created. According to Invoca’s “B2C Buyers Experience Report,” consumers are increasingly comfortable using genAI and agents

When your sales team says the leads coming from marketing aren’t good enough, are they wrong? In most cases, the problem isn’t lead volume. It’s signal quality.  Marketing routes contacts based on activity rather than account readiness. Your sales team picks up the phone to a contact who once browsed your pricing page. Meanwhile, a

Disclosure: I’m the co-founder of Optmyzr. I’ll use one of our open-source skills as the example below, but the frameworks here apply to anything you install or build. If you’ve used Claude, ChatGPT, or Gemini for marketing work in the last six months, you’ve probably hit the same wall I have. The chat is great

Whether your marketing team can take advantage of AI agents depends less on the agent tools themselves and more on whether your existing platforms have the API infrastructure to support them. A new public dataset grades 152 B2B APIs on their agent-readiness — giving you a framework to pinpoint where your stack can support automation

If you’re reviewing a year of AI activity and still feel like nothing meaningful changed, you’re not alone. Many companies are measuring activity rather than building a strategy. That distinction matters because it is the difference between scattered experimentation and durable advantage.  You can spend real money, create real internal excitement, and still be no

Marketing teams are under growing pressure to prove that AI can deliver real value, such as generating revenue, achieving mission success, and reducing costs. The early phase of AI adoption was defined by pilots, productivity gains, and tool exploration. Those efforts helped organizations learn about the burgeoning technology, but they also created a new challenge: