Struggling to increase user adoption and show the economic value of your ML and anlaytical data products?  

Here's the secret:

  • Users and stakeholders don't want AI and analytics—even if they asked for it.
  • You can't repeatedly create "business value" if people aren't even using your model, dashboards, or decision support applications.
  • You might have a technically right solution, but if your data product's UX is bad, users won't use it—and stakeholders won't see the value of your data solution.

If you're like many data product leaders I know, these sound familiar:

  • Low user adoption of your SAAS product, dashboards, model, or apps is a routine problem—even if you gave users what they asked for
  • Users don't trust your machine learning models
  • You get vague mandates or requests to "use AI"—especially LLMs!—but no clear business problem to solve
  • You're team is good at the analytics, ML, and engineering, but users aren't using—or buyers aren't buying
  • Your commercial/SAAS analytics product is hard to sell, hard to use, or requires a lot of explanation or change management to get adoption
  • Your internal data team wants to be the go-to source for ML and analytics expertise—but stakeholders see you mostly as dashboard-generators and model-makers.

Brian O'Neill by Liza VollMy name is Brian T. O'Neill, sometimes known as the "UX for data products guy."  I help data and product leaders turn ML and analytics usable, valuable data products by:

  • Applying UX design to data products to increase adoption
  • Adopting data product management practices to generate economic value

Ready to learn how?

Start by joining my free Insights mailing list, and subscribing to my podcast, Experiencing Data. Additional resources are here.

Need personalized help?

Learn how to work with me.

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