Marketing teams have never had more customer signals, yet many still struggle to name what a customer actually wants. In a recent Conversations with MarTech episode, Malinda Sandman, global VP of marketing at Typeform, argues that AI may make marketing harder in the short term before it makes it easier.
The clickless shift
Sandman points to a shift toward a “clickless” environment, where people interact with brands without the clean click paths marketers have used for attribution and insight for years. That makes the old measurement playbook less reliable, even as martech vendors and ad platforms roll out AI tools at a furious pace.
97% adoption, but lagging follow-up
The episode highlights a stark gap: 97% of marketers use AI, but lead follow-up still lags. Sandman reframes the problem simply: marketers don’t necessarily have a data problem, they have an action problem. More data doesn’t necessarily mean knowing your customer.
Avoid the garbage in, garbage out trap
AI models learn from whatever you feed them. If the inputs are messy or shallow, the outputs can sound smart while missing real human context. Sandman cautions teams to guard against the “garbage in, garbage out” trap, and to keep human judgment in the creative process so AI scaling does not produce homogeneous outputs.
What Typeform does differently
Instead of adding more dashboards, Typeform uses AI for scalable customer interviews. Its “Always On” research approach gathers customer feedback in as little as 24 hours. Video feedback helps bridge B2B and B2C marketing mindsets, moving teams from aggregate charts to real customer voices.
For marketing professionals, the practical lesson is to close the insight-action gap before adding another tool:
- Find the largest action gap in your funnel first.
- Set up a short, always-on feedback loop instead of a one-off survey.
- Review AI-generated creative for sameness and keep a human editor in the loop.
- Turn every insight into a named next step, not another report.
The biggest lie Sandman names is that more data equals knowing your customer. The fix is not more instrumentation; it is closing the distance between what you learn and what you actually do.
Source: MarTech
