Experiencing Data w/ Brian T. O’Neill
Technology
About
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 a...
Episodes
- 193 - Faster…or Better? Creating Value with Blue Ocean Thinking and AI-Powered Product Development
This episode discusses how blue ocean thinking and AI-powered product development can help teams create true value instead of getting stuck in cycles of validating surface-level solutions. It explores using AI to find overlooked opportunit…
- 192 – Product Usage Does Not = Value: Why “Adoption” Metrics Are Misleading You
This episode discusses why product usage metrics may not accurately reflect product value. It explores alternative qualitative and quantitative approaches to measure user experience and ensure product success and retention. The importance…
- 191 - Turning Agents into Software that Sells [Smarter!] with Zig.ai CEO Steve Ancheta
Brian T. O’Neill interviews Zig.ai CEO Steve Ancheta about designing AI agents for sales teams. The discussion focuses on creating user-centric software that prioritizes tasks, integrates with CRM systems, and maintains institutional knowl…
- 190 - Why Discovering Valuable Analytics Use Cases for Your Product Is So Hard (Even with AI)
Brian T. O’Neill discusses why analytics and AI products often struggle to provide value, emphasizing that teams should focus on user decision-making rather than data availability. The episode explores how to design tools that fit into rea…
- 189 - The Invisible Intelligence Gap
Brian T. O’Neill discusses the "Invisible Intelligence Gap," where analytics and AI products fail to deliver value to customers despite technical success. He introduces frameworks like CED, FOWA, and MIRRR to help product teams address val…
- 188 - Can’t Close the Sale? Why Your Product’s UX and Workflow Misalignment Are Killing Sales (Part 2)
Brian T. O’Neill continues his discussion on Flow-of-Work Alignment (FOWA), addressing how aligning product UX and workflows can help software companies close more sales. The episode covers practical steps for implementation, including tai…
- 187 - Can’t Close the Sale? The Invisible Reasons Prospects Aren’t Buying Your Technically Superior Analytics or AI Product (Part 1)
This episode explores why technically superior analytics and AI products often fail to sell, focusing on the disconnect between product capabilities and user workflows. Brian T. O’Neill introduces Flow of Work Alignment (FOWA) as a strateg…
- 186 - Why Powerful AI & Analytics Products Feel Useless to Buyers
Host Brian T. O’Neill discusses the importance of translating AI and analytics capabilities into clear, actionable value for B2B buyers and users. He explores the challenges of aligning technical products with user workflows and the need f…
- 185 - Driving Healthcare Impact by Aligning Teams Around Outcomes with Bill Saltmarsh
Bill Saltmarsh, CDO at Children’s Mercy Kansas City, discusses adopting a product-oriented mindset in healthcare data teams. He emphasizes moving away from generating reports to focusing on organizational outcomes, data literacy, and align…
- 184 - Part III: Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change
In this final installment of a three-part series, Brian T. O’Neill discusses how AI-driven automation impacts user workflows and product design. He explores the challenges of addressing newly surfaced problems, building trust through custo…
- 183 - Part II: Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change
In this episode of Experiencing Data, Brian T. O’Neill discusses how aligning B2B analytics and AI product design with actual user workflows can accelerate sales. The discussion covers defining UX outcomes, establishing quality baselines,…
- 182 - Designing with the Flow of Work: Accelerating Sales in B2B Analytics and AI Products by Minimizing Behavior Change
Brian T. O’Neill discusses how designing B2B analytics and AI products around existing user workflows can increase adoption and sales. He explains why minimizing behavior change and prioritizing user needs over complex features leads to be…
- 181 - Lessons Learned Designing Orion, Gravity’s AI, AI Analyst Product with CEO Lucas Thelosen (former Head of Product @ Google Data & AI Cloud)
Brian T. O’Neill interviews Lucas Thelosen, CEO of Gravity and former Google Data & AI Cloud executive, about the development of the Orion AI analyst product. They discuss the importance of a data product management mindset, achieving mark…
- 180 - From Data Professional to Data Product Manager: Mindset Shifts To Make
This episode outlines the mindset shifts necessary for data professionals transitioning into analytics and AI data product management. Brian T. O’Neill explores how to focus on problem-solving, meaningful adoption, and identifying latent u…
- 179 - Foundational UX principles for data and AI product managers
This episode of Experiencing Data with Brian T. O’Neill focuses on foundational UX principles for data and AI product managers.
- 178 - Designing Human-Friendly AI Tech in a World Moving Too Fast with Author and Speaker Kate O’Neill
Tech humanist Kate O'Neill joins the podcast to discuss balancing human-centered design with the rapid adoption of AI. The conversation explores the "Now–Next Continuum" framework, ethical decision-making, and the importance of aligning or…
- 177 - Designing Effective Commercial AI Data Products for the Cold Chain with the CEO of Paxafe
Ilya Preston, CEO and co-founder of PAXAFE, discusses the development of a logistics orchestration platform for cold chain supply chains. The conversation covers the challenges of designing AI-driven data products for sensitive shipping an…
- 176 - (Part 2) The MIRRR UX Framework for Designing Trustworthy Agentic AI Applications
In the second part of a deep dive into the MIRRR UX Framework, host Brian T. O’Neill explores the concepts of Redirect, Rerun, and Rollback for designing trustworthy agentic AI applications. The episode provides strategies for data product…
- 175 - The MIRRR UX Framework for Designing Trustworthy Agentic AI Applications (Part 1)
Brian T. O’Neill introduces the first part of the MIRRR UX framework, designed to help build trust and adoption for agentic AI applications. This episode focuses on the Monitor and Interrupt control points, using insurance claims processin…
- 174 - Why AI Adoption Moves at the Speed of User Trust Irina Malkova on Lessons Learned Building Data Products at Salesforce
Irina Malkova, VP of AI Engineering and Data and Analytics at Salesforce, discusses her approach to building data products. She covers scaling AI, the importance of user trust, organizational structure, and implementing Slack-based AI agen…
- 173 - Pendo’s CEO on Monetizing an Analytics SAAS Product, Avoiding Dashboard Fatigue, and How AI is Changing Product Work
Pendo CEO Todd Olson discusses simplifying analytics dashboards, balancing power user needs with broader accessibility, and integrating AI into product management workflows. He also shares his approach to hiring product managers and tracki…
- 172 - Building AI Assistants, Not Autopilots: What Tony Zhang’s Research Shows About Automation Blindness
AI researcher Tony Zhang discusses his study on user decision-making, comparing traditional recommendation AIs with a forward-reasoning approach. The conversation covers research involving pilots selecting airports and investors rebalancin…
- 171 - Who Can Succeed in a Data or AI Product Management Role?
Brian T. O’Neill discusses the skills required for success as a data or AI product manager. He analyzes the strengths and weaknesses of professionals transitioning from design, data science, engineering, and software product management rol…
- 170 - Turning Data into Impactful AI Products at Experian: Lessons from North American Chief AI Officer Shri Santhnam (Promoted Episode)
Brian T. O’Neill interviews Shri Santhanam, EVP of Software Platforms and Chief AI Officer of Experian North America, about building AI products for consumers and B2B clients. The discussion covers AI team structures, initiative prioritiza…
- 169 - AI Product Management and UX: What’s New (If Anything) About Making Valuable LLM-Powered Products with Stuart Winter-Tear
Stuart Winter-Tear joins host Brian T. O’Neill to discuss the practical aspects of building and launching commercially valuable LLM-powered products, emphasizing the importance of focusing on user problems rather than just AI technology it…
- 168 - 10 Challenges Internal Data Teams May Face Building Their First Revenue-Generating Data Product
In this episode, Brian T. O’Neill discusses ten common challenges faced by internal enterprise data teams when developing their first revenue-generating data product. The episode provides insights for teams looking to monetize data-driven…
- 167 - AI Product Management and Design: How Natalia Andreyeva and Team at Infor Nexus Create B2B Data Products that Customers Value
Natalia Andreyeva, Senior Director of Product Management for Infor Nexus, discusses AI/ML product management in supply chain software. The episode covers the role of user experience, customer discovery, and value creation when designing B2…
- 166 - Can UX Quality Metrics Increase Your Data Product's Business Value and Adoption?
Brian T. O’Neill explores why product leaders should look beyond quantitative analytics to measure user experience. He discusses the importance of qualitative research and subjective user feedback in increasing business value and adoption…
- 165 - How to Accommodate Multiple User Types and Needs in B2B Analytics and AI Products When You Lack UX Resources
Brian T. O’Neill discusses strategies for designing B2B data and AI products that serve multiple user types, especially when UX resources are limited. He explores research methods, prioritization techniques, and design approaches for meeti…
- 164 - The Hidden UX Taxes that AI and LLM Features Impose on B2B Customers Without Your Knowledge
Brian T. O’Neill discusses the UX challenges and hidden complexities of integrating AI and LLM features into B2B products. The episode explores how product teams can ensure AI implementations deliver genuine value and improve outcomes for…
- 163 - It’s Not a Math Problem: How to Quantify the Value of Your Enterprise Data Products or Your Data Product Management Function
Brian T. O’Neill discusses why data teams struggle to quantify the value of their products and suggests moving away from treating valuation as an objective math problem. He explains that value is often subjective and provides strategies fo…
- 162 - Beyond UI: Designing User Experiences for LLM and GenAI-Based Products
Brian T. O’Neill hosts a panel with Simon Landry, Greg Nudelman, and Paz Perez to discuss designing user experiences for LLM and GenAI products. They explore the impact of AI-first thinking, designer-engineer collaboration, and the importa…
- 161 - Designing and Selling Enterprise AI Products [Worth Paying For]
Brian T. O'Neill explores the challenges of designing and selling B2B AI products, focusing on the interplay between GenAI, customer trust, and UX. He discusses how product teams can balance technological potential with delivering tangible…
- 160 - Leading Product Through a Merger/Acquisition: Lessons from The Predictive Index’s CPO Adam Berke
Adam Berke, Chief Product Officer at The Predictive Index, discusses his experiences leading product through the merger with Charma. He covers the challenges of integrating product teams, the role of behavioral science, and managing legacy…
- 159 - Uncorking Customer Insights: How Data Products Revealed Hidden Gems in Liquor & Hospitality Retail
Andy Sutton of Endeavour Group discusses his transition to a product-led approach for data and analytics. He explores how this strategy has created measurable financial value and improved personalization for liquor and hospitality retail c…
- 158 - From Resistance to Reliance: Designing Data Products for Non-Believers with Anna Jacobson of Operator Collective
Anna Jacobson of Operator Collective joins Brian T. O’Neill to discuss strategies for designing data products and securing adoption from resistant or apathetic users. The episode also covers her professional background and her work within…
- 157 - How this materials science SAAS company brings PM+UX+data science together to help materials scientists accelerate R&D
Ori Yudilevich, Chief Product Officer at MaterialsZone, discusses how his company integrates product management, UX, and data science to create software that helps materials scientists accelerate R&D using machine learning. The episode exp…
- 156-The Challenges of Bringing UX Design and Data Science Together to Make Successful Pharma Data Products with Jeremy Forman
Jeremy Forman, from Pfizer's R&D department, discusses the challenges and successes of integrating UX design with data science to build data products for the pharmaceutical industry. The episode explores team structure, the role of domain…
- 155 - Understanding Human Engagement Risk When Designing AI and GenAI User Experiences
Brian T. O’Neill and Ovetta Sampson discuss the ethical considerations, risks, and design challenges involved in developing AI and Generative AI user experiences. The conversation covers team composition, the impact of AI on product roles,…
- 154 - 10 Things Founders of B2B SAAS Analytics and AI Startups Get Wrong About DIY Product and UI/UX Design
Brian T. O’Neill discusses common pitfalls for B2B SaaS analytics and AI startup founders regarding DIY product design. The episode outlines root causes for issues such as sales friction, low user adoption, and lack of product progress.
- 153 - What Impressed Me About How John Felushko Does Product and UX at the Analytics SAAS Company, LabStats
John Felushko, a product manager at LabStats, discusses the company's approach to product management, user experience, and analytics. He covers topics such as the importance of customer relationships, the role of user research, and lessons…
- 152 - 10 Reasons Not to Get Professional UX Design Help for Your Enterprise AI or SAAS Analytics Product
Brian T. O’Neill explores 10 reasons companies might choose not to hire professional UX design help for enterprise AI or SaaS analytics products. He discusses these common perspectives alongside counterarguments and considers the various t…
- 151 - Monetizing SAAS Analytics and The Challenges of Designing a Successful Embedded BI Product (Promoted Episode)
In this replay of a previous conversation, host Brian T. O’Neill discusses the monetization of SaaS analytics and the challenges of designing an embedded BI product with Zalak Trivedi.
- 150 - How Specialized LLMs Can Help Enterprises Deliver Better GenAI User Experiences with Mark Ramsey
Brian T. O’Neill hosts Mark Ramsey to discuss the evolution of LLMs and creating effective GenAI user experiences in the enterprise. They cover topics including pilot projects, re-ranking for accuracy, privacy, human testing, and the futur…
- 149 - What the Data Says About Why So Many Data Science and AI Initiatives Are Still Failing to Produce Value with Evan Shellshear
Brian T. O’Neill and guest Evan Shellshear discuss why many data science and AI initiatives continue to fail, focusing on human factors rather than technology. They explore the disconnect between data scientists and decision-makers, emphas…
- 148 - LLMs need UX: How to Increase Your B2B Product’s Value with AI (Part 2)
In this second part of a series on UX for LLMs, host Brian T. O’Neill explores how enterprise software can leverage AI for internal tasks like qualitative user research. He discusses design implications, data quality, and managing AI hallu…
- 147 - LLMs need UX: How to Increase Your B2B Product’s Value with AI (Part 1)
Brian T. O'Neill explores the intersection of user experience design and LLM integration in B2B products. He discusses the risks of FOMO-driven AI deployment and emphasizes the need for outcome-oriented thinking, context, and proper benchm…
- 146 - (Rebroadcast) Beyond Data Science - Why Human-Centered AI Needs Design with Ben Shneiderman
Ben Shneiderman, Professor at the University of Maryland, discusses his perspectives on human-centered artificial intelligence. He covers the importance of designing safe, reliable, and controllable AI systems, the need for independent ove…
- 145 - Data Product Success: Adopting a Customer-Centric Approach With Malcolm Hawker, Head of Data Management at Profisee
Malcolm Hawker, Head of Data Management at Profisee, joins Brian T. O’Neill to discuss the importance of a customer-centric and product-oriented approach to data products. The conversation covers the role of empathy in design, building bus…
- 144 - The Data Product Debate: Essential Tech or Excessive Effort? with Shashank Garg, CEO of Infocepts (Promoted Episode)
Shashank Garg, CEO of Infocepts, joins host Brian T. O’Neill to discuss the value of taking a product-oriented approach to data, analytics, and machine learning initiatives. They explore definitions of data products, user-centric design, a…