As AI enters the resolution era, marketing teams are being forced to move beyond experimentation and prove that their strategies are delivering real, measurable outcomes.
With fragmented data, a saturated AI vendor landscape, and mounting internal budget pressure, marketing teams are now struggling more than ever to build a coherent picture of their customers.
As a result, the companies that automate everything will likely be unsuccessful as they struggle to identify which activities drive results.
Emma Acton, VP of Marketing at Zendesk, spoke to CX Today at Zendesk Showcase London to discuss how the successful marketers will be smart enough to know where not to use AI, and where to include a human instead.
"It is still the human in the loop, you are allowing AI to be in the areas that need to be automated and AI agents for those tasks,” she explained.
“More valuable tasks, like a white-glove approach.”
Too Much Data Yet Too Little Clarity
As AI adoption accelerates across industries, marketing leaders are noticing the AI market has become increasingly crowded as more customer enterprises are receiving an overload of AI messaging from various technology vendors.
In fact, this constant stream of competing claims is now making it difficult for teams to separate innovation from noise as organizations are generating more customer data than ever before across systems and channels.
However, collecting more data does not automatically create better insight, as “your data sources have got to be connected to each other in order to form that picture of the customer," notes Acton.
When systems remain disconnected, marketing teams are left with fragmented views of customer behavior, making it harder for teams to make confident decisions on experiences.
Furthermore, these marketing challenges are being amplified by increasing pressure to demonstrate ROI, as more marketing leaders are expected to show clear business outcomes rather than simply report activity metrics.
Unfortunately, when it comes to ROI visibility, “there's very good, very bad, or none at all. There's a middle ground,” she points out.
