195 Buyers Block: Why Your B2B Analytics or AI Product's POC Didn't Close
May 26, 202627mEp. 1950
Why do your B2B analytics or AI Products not close? Learn more in this episode with Brian O'Neill. More episode details coming soon.
Show notesUpdated 11 days ago · Refreshed hourly
technologybusiness
Experiencing Data w/ Brian T. O’Neill
Hosted by Unknown Host · 🇺🇸 US · EN · 100 episodes
Where this show ranks
Episodes
100
Last ep.
12 days ago
Avg length
38m
Booking Probability™
34
Stretch.
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Estimated audience
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Listen Score
28
Niche reach.
Virality (30d)
52
Steady cadence.
Pitch Analysis
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Required Pod Score
80/ 100
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About this podcast
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
technologybusinessmanagement
About the host
Unknown Host hosts Experiencing Data w/ Brian T. O’Neill, a technology show with 100 episodes published.
Recent episodes
Our AI reads these to draft pitches194 - AI for BI: Juan Sequeda on Preparing Your Analytics to Work With LLMs
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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
Show notes193 - Faster…or Better? Creating Value with Blue Ocean Thinking and AI-Powered Product Development
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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
Show notes192 – Product Usage Does Not = Value: Why “Adoption” Metrics Are Misleading You
Apr 15, 202646mEp. 1920
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
Show notes191 - Turning Agents into Software that Sells [Smarter!] with Zig.ai CEO Steve Ancheta
Mar 31, 202642mEp. 1910
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
Show notes190 - Why Discovering Valuable Analytics Use Cases for Your Product Is So Hard (Even with AI)
Mar 17, 202643mEp. 1900
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
Show notes189 - The Invisible Intelligence Gap
Mar 4, 202625mEp. 1890
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
Show notes188 - Can’t Close the Sale? Why Your Product’s UX and Workflow Misalignment Are Killing Sales (Part 2)
Feb 17, 202646mEp. 1880
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
Show notes187 - Can’t Close the Sale? The Invisible Reasons Prospects Aren’t Buying Your Technically Superior Analytics or AI Product (Part 1)
Feb 3, 202620mEp. 1870
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
Show notes186 - Why Powerful AI & Analytics Products Feel Useless to Buyers
Jan 20, 202638mEp. 1860
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
Show notes185 - Driving Healthcare Impact by Aligning Teams Around Outcomes with Bill Saltmarsh
Dec 22, 202541mEp. 1850
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
Show notes184 - Part III: Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change
Dec 8, 202514mEp. 1840
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
Show notes183 - Part II: Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change
Nov 26, 202535mEp. 1830
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
Show notes182 - Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change
Nov 10, 202522mEp. 1820
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
Show notes181 - Lessons Learned Designing Orion, Gravity’s AI, AI Analyst Product with CEO Lucas Thelosen (former Head of Product @ Google Data & AI Cloud)
Oct 28, 202550mEp. 1810
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
Show notes180 - From Data Professional to Data Product Manager: Mindset Shifts To Make
Oct 14, 202545mEp. 1800
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
Show notes179 - Foundational UX principles for data and AI product managers
Sep 30, 202551mEp. 1790
Content coming soon.
Show notes178 - Designing Human-Friendly AI Tech in a World Moving Too Fast with Author and Speaker Kate O’Neill
Sep 16, 202550mEp. 1780
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
Show notes177 - Designing Effective Commercial AI Data Products for the Cold Chain with the CEO of Paxafe
Sep 3, 202549mEp. 1770
In this episode, I talk with Ilya Preston, co-founder and CEO of PAXAFE, a logistics orchestration and decision intelligence platform for temperature-controlled supply chains (aka “cold chain”). Ilya explains how PAXAFE
Show notes176 - (Part 2) The MIRRR UX Framework for Designing Trustworthy Agentic AI Applications
Aug 19, 202529mEp. 1760
This is part two of the framework; if you missed part one, head to episode 175 and start there so you're all caught up. In this episode of Experiencing Data, I continue my deep dive into the MIRRR UX Framework for design
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Audience demographics
Age
22-44
Consumer type
Tech professionals
Topics covered
technologybusinessmanagement
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Frequently asked questions
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Experiencing Data w/ Brian T. O’Neill has a verified contact on file. Create a free PitchCentric account to access it and generate a personalised pitch in seconds. Research at least 3 recent episodes first and lead with a specific angle that serves their technology audience.
Who is the host of Experiencing Data w/ Brian T. O’Neill?
Experiencing Data w/ Brian T. O’Neill is hosted by Unknown Host. The show is categorised under technology (business) and has published 100 episodes.
How many episodes does Experiencing Data w/ Brian T. O’Neill have?
Experiencing Data w/ Brian T. O’Neill has published 100 episodes.
What topics does Experiencing Data w/ Brian T. O’Neill cover?
Experiencing Data w/ Brian T. O’Neill regularly covers technology, business, management. It sits in the technology category, with a business focus.
Is it hard to get booked on Experiencing Data w/ Brian T. O’Neill?
Experiencing Data w/ Brian T. O’Neill is accessible for guests with genuine technology expertise. A personalised, episode-aware pitch will still outperform a generic one every time.
Is Experiencing Data w/ Brian T. O’Neill currently accepting guest pitches?
Experiencing Data w/ Brian T. O’Neill hasn't explicitly signalled guest openness in recent episodes. That doesn't rule out pitching. your hook just needs to be especially compelling and relevant to their recent content.
How long are Experiencing Data w/ Brian T. O’Neill episodes?
Episodes of Experiencing Data w/ Brian T. O’Neill average 38 minutes. a focused format where a clear narrative arc and tight preparation matter most.
What guest credentials does Experiencing Data w/ Brian T. O’Neill typically look for?
Our data rates Experiencing Data w/ Brian T. O’Neill's guest bar at 80/100 (Premium tier). Established thought leaders with verified media credentials. Sign in to PitchCentric to see how your own Pod Score compares against this show.
Methodology. Booking Probability™ blends Listen Score, 30-day Virality, open-to-guests detection, and Apple ratings. Data refreshed every 60 minutes. Listen Score and Booking Probability are calculated by PitchCentric. Last enriched 11 days ago.
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