Hosted by Unknown Host · 🇺🇸 US · EN-US · 100 episodes
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Are you an enterprise data or product leader seeking to increase the user adoption and business value of your ML/AI and analytical data products?While it is easier than ever to create ML and analytics from a technology perspective, do you find that getting users to use, buyers to buy, and stakeholders to make informed decisions with data remains challenging?If you lead an enterprise data team, have you heard that a ”data product” approach can help—but you’re not sure what that means, or whether software product management and UX design principles can really change consumption of ML and analytics?My name is Brian T. O’Neill, and on Experiencing Data—one of the top 2% of podcasts in the world—I offer you a consulting product designer’s perspective on why simply creating ML models and analytics dashboards aren’t sufficient to routinely produce outcomes for your users, customers, and stakeholders. My goal is to help you design more useful, usable, and delightful data products by better
Unknown Host hosts Experiencing Data w/ Brian T. O’Neill, a technology show with 100 episodes published.
Everyone is racing to the same place chasing a limited set of buyers—how will your “AI for BI” product stand out? I've been seeing teams heavily invest in copilots, agents, semantic layers, governance frameworks, and inc
I've been seeing a recurring pattern with companies selling APIs, MCPs, data feeds, and other developer-focused AI products. While the technology is often sound if not impressive, sales momentum sometimes slows when pros
Why do your B2B analytics or AI Products not close? Learn more in this episode with Brian O'Neill. More episode details coming soon.
If you’re hoping that adding AI to your analytics product or capabilities is going to unlock new revenue, sales, and greater user adoption, but you’re not sure what’s involved in this transformation, this episode is for
Speed is often confused with good product thinking. The idea is that if teams can ship prototypes, dashboards, and models faster, they will automatically learn faster. But execution speed alone doesn’t ensure a clearer u
I’ve seen this challenge again and again with teams building analytics and AI products: nobody can define what quality to the end user means or how to measure. The answer? “Adoption.” The problem is that “amount of usage
I'm talking with Steve Ancheta, CEO of Zig, a platform designed to free sales teams from repetitive, non-revenue-generating tasks. CRM and logistical tasks can consume up to 72% of the week of a sales team, but Zig’s AI
I’ve seen this pattern repeatedly with teams building analytics and AI products: the issue usually isn’t the quality of the models or the sophistication of the data. The technology often works just fine. The real breakdo
I’ve worked with a lot of teams building analytics and insights products and decision-support systems. The pattern I keep seeing isn’t that the math is wrong or the ML / AI models are weak. Much of the time, the technolo
I’m continuing my exploration of a hard truth many leaders of analytics software companies run into: deals don’t stall because the tech is weak. Instead, they stall because prospects can’t see the value soon enough or th
I’m digging into a frustrating reality many teams face: even technically superior analytics and AI products routinely lose deals—not because the KPIs or models aren’t good enough, but because buyers and users can’t clear
I’m back! After about 7 years (or more) of bi-weekly publishing, I gave myself a break (to have the flu, in part), but now it’s back to business! In 2026, I’ll be focusing the podcast more on the commercial side of data
Bill Saltmarsh joins me to discuss where a modern CDO gets the inspiration to “operate in the producty way” in his domain, which is healthcare. Now Vice President of Enterprise Data and Transformation and the Chief Data
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
In this second part of my three-part series (catch Part I via episode 182), I dig deeper into the key idea that sales in commercial data products can be accelerated by designing for actual user workflows—vs. going wide w
Building B2B analytics and AI tools that people will actually pay for and use is hard. The reality is, your product won’t deliver ROI if no one’s using it. That’s why first principles thinking says you have to solve the
On today's Promoted Episode of Experiencing Data, I’m talking with Lucas Thelosen, CEO of Gravity and creator of Orion, an AI analyst transforming how data teams work. Lucas was head of PS for Looker, and eventually beca
In this episode, I’m exploring the mindset shift data professionals need to make when moving into analytics and AI data product management. From how to ask the right questions to designing for meaningful adoption, I shar
Content coming soon.
In this episode, I sat down with tech humanist Kate O’Neill to explore how organizations can balance human-centered design in a time when everyone is racing to find ways to leverage AI in their businesses. Kate introduce
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Experiencing Data w/ Brian T. O’Neill is hosted by Unknown Host. The show is categorised under technology (business) and has published 100 episodes.
Experiencing Data w/ Brian T. O’Neill has published 100 episodes.
Experiencing Data w/ Brian T. O’Neill regularly covers technology, business, management. It sits in the technology category, with a business focus.
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Episodes of Experiencing Data w/ Brian T. O’Neill average 37 minutes. a focused format where a clear narrative arc and tight preparation matter most.
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