Learn from the Comprend experts

Your buyers are researching, comparing, and increasingly buying from inside an AI assistant. The only question left is whether it gets your business right when the deal is decided.

I wanted to question a sentiment I keep hearing from clients whenever we discuss AI and agents. It usually arrives as a version of the same question: what will the world look like in three to five years, and how do we prepare for it? How do we plan for a future web?

Agentic content generation lets you be relevant on every page a customer might land on, at a cost that no longer scales with your ambition.

Have you ever wondered how much your website is really saying about you? Not just the words on the page but the accessibility gaps, the broken links, the security headers nobody checked, the cookie banner that doesn't quite do what it claims, and the tone of voice that drifts a little further from your brand with every new page someone publishes.

Most B2B brands are talking on social media. Very few are listening, responding, or making space for people to belong. There's a difference, and it's costing them.

78% of enterprises have an AI pilot running. Only 14% have scaled one to organisation-wide use. We find that gap worth sitting with, because it’s where most of the organisations we speak with are quietly stuck right now.

AI increases analytical capacity in your marketing team, but at the same time user privacy concerns decreases data quality. The answer is to take a new approach to marketing measurement and incorporate learnings from the golden age of advert­ising. If done right, this approach gives strategical as well as tactical insights. If you are new to these methods, you are likely to see effect increases from your marketing by at least 15-30%.

We all know the appeal of a campaign that runs itself. That's what AI-driven marketing promises, but full automation isn't the end goal. It's just a tool, and like any tool, it only works as well as the strategy guiding it.

Most marketing teams have been using generative AI for a while now. Drafting copy, brainstorming ideas, summarising research, it's become part of the workflow. But there's a shift happening that goes beyond chatting with a language model and hoping for a useful reply. We're moving from AI that helps us do our work to AI that actually does work for us.