184 - Part III: Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change

184 - Part III: Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change

Author: Brian T. O’Neill from Designing for Analytics December 9, 2025 Duration: 14:22

In this final part of my three-episode series on accelerating sales and adoption in B2B analytics and AI products, I unpack a growing challenge in the age of generative AI: what to do when your product automates a major chunk of a user’s workflow only to reveal an entirely new problem right behind it.

Building on Part I and Part II, I look at how AI often collapses the “front half” of a process, pushing the more complex, value-heavy work directly to users. This raises critical questions about product scope, market readiness, competitive risks, and whether you should expand your solution to tackle these newly surfaced problems or stay focused and validate what buyers will actually pay for.

I also discuss why achieving customer delight—not mere satisfaction—is essential for earning trust, reducing churn, and creating the conditions where customers become engaged design partners. Finally, I highlight the common pitfalls of DIY product design and why intentional, validated UX work is so important, especially when AI is changing how work gets done faster than ever.

 

Highlights/ Skip to:

  • Finishing the journey: staying focused, delighting users, and intentional UX (00:35)
  • AI solves problems—and can create new ones for your customers—now what? (2:17)
  • Do AI products have to solve your customers’ downstream “tomorrow” problems too before they’ll pay? (6:24) 
  • Questions that reveal whether buyers will pay for expanded scope (6:45)
  • UX outcomes: moving customers from satisfied to delighted before tackling new problems  (8:11)
  • How obtaining “delight” status in the customer’s mind creates trust, lock-in, and permission to build the next solution (9:54)
  • Designing experiences with intention (not hope) as AI changes workflows (10:40)
  • My “Ten Risks of DIY Product Design…” — why DIY UX often causes self-inflicted friction (11:46)

 

Links


For enterprise data and product leaders, the real challenge often isn't building the technology-it's getting people to actually use it. Experiencing Data w/ Brian T. O’Neill digs into that persistent gap between creating powerful ML, AI, and analytical tools and seeing them drive genuine business value and informed decisions. Host Brian T. O’Neill, from Designing for Analytics, moves past pure technical discussion to explore how design, product thinking, and strategic management can bridge that divide. This podcast lives at the intersection of data and human experience, making it essential for anyone who has ever wondered why a technically sound data product failed to gain user adoption or secure stakeholder buy-in. Across conversations with practitioners and through Brian’s own analysis, episodes unpack what a "data product" approach truly means in practice. You’ll hear concrete strategies for designing analytics that people want to use, framing data work in terms of business outcomes, and leading teams to create not just outputs, but impactful solutions. It’s a resource for rethinking how data work connects to the arts of communication, design, and leadership, all to ensure that data investments lead to tangible results. Tune in for a pragmatic, human-centered perspective that is often missing from the tech conversation.
Author: Language: en-us Episodes: 100

Experiencing Data w/ Brian T. O’Neill
Podcast Episodes
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