Venture capitalist Ellen Chisa discusses the impact of AI on SaaS and data/developer products in 2024. Topics include democratizing software creation, streamlining backend coding, and future prospects for developer tools and SaaS platforms. The podcast explores the evolution of AI prototypes, BoldStart Ventures' focus on early-stage companies, and insights gained from previous experiences in product management.

Karen Meppen, Data Product Architect, discusses challenges of immature data and tech in data product development. She explains what data products are and the importance of executive buy-in. Karen highlights conflicts between shadow data teams and tech teams, providing insights on effective strategies in adopting a product and UX-driven methodology.

Caroline Zimmerman, Director of Data Products and Strategy at Profusion, discusses the importance of UX research in data product design. She shares her journey and the pivotal moment that changed her approach, as well as the significance of exploring the 'why' behind decisions. They also explore challenges in UX design for B2B SaaS products and navigating politics in larger companies.

In this episode, Brian T. O'Neill chats with Steve Portigal, Principal of Portigal Consulting and the Author of Interviewing Users. They discuss the changes in user research over the past 10 years. They explore the best practices for implementing effective data product UX research, emphasizing the importance of understanding the business value and not just having a list of research questions. They provide role-play examples and discuss the impact of taking imperfect action towards user research. Overall, they highlight the value of user research in driving data product adoption and business value.

Former Gartner analyst and Co-Author of Data Products for Dummies, Sanjeev Mohan, discusses the evolution of data products, implementing practices for business value, and new approaches to organizational structure. They also explore challenges of product adoption and responsibility for user experience. A conversation with different perspectives on the data product space.

Today I am sharing some highlights for 2023 from the podcast, and also letting you all know I’ll be taking a break from the podcast for the rest of December, but I’ll be back with a new episode on January 9th, 2024. I’ve also got two links to share with you—details inside!   Transcript Greetings everyone - I’m taking a little break from Experiencing Data over December of 2023, but I’ll be back in January with more interviews and insights on leveraging UX design and product management to create indispensable data products, machine learning apps, and decision support tools.  Experiencing Data turned this year five years old back in November, with over 130 episodes to date! I still can’t believe it’s been going that long and how far we’ve come.  Some highlights for me in 2023 included launching the Data Product Leadership Community, finding out that the show is now in the top 2% of all podcasts worldwide according to ListenNotes, and most of all, hearing from you that the podcast, and my writing, and the guests that  I have brought on are having an impact on your work, your careers, and hopefully the lives of your customers, users, and stakeholders as well!  So, for now, I’ve got just two links for you: If you’re wondering how to either: support the show yourself with a really fast review on Apple Podcasts, to record a quick audio question for me to answer on the show,  or if you want to join my free Insights mailing lists where I share my bi-weekly ideas and thoughts and 1-page episode summaries of all the show drops that I put out here on Experiencing Data. …just head over to designingforanalytics.com/podcast and you’ll get links to all those things there. And secondly, if you need help increasing customer adoption, delight, the business value, or the usability of your analytics and machine learning applications in 2024, I invite you to set up a free discovery call with me 1 on 1.  You bring the questions, I’ll bring my ears, and by the end of the call, I’ll give you my best advice on how to move forward with your situation – whether it’s working with me or not. To schedule one of those free discovery calls, visit designingforanalytics.com/go And finally, there will be some news coming out next year with the show, as well as my business, so I hope you’ll hop on the mailing list and stay tuned, that’s probably the best place to do that. And if you celebrate holidays in December and January, I hope they’re safe, enjoyable, and rejuvenating. Until 2024, stay tuned right here - and in the words of the great Arnold Schwarzenegger, I’ll be back.

Klara Lindner, Service Designer at diconium data, discusses leveraging behavioral science to increase data product adoption. She shares insights on user research, human-centered design, and the disconnect between data professionals and their own advice. Klara explores easy user research techniques, responsibility for user adoption, and upcoming webinars on behavioral science frameworks. Topics also include service design, renewable energy technologies, and challenges faced by B2B SaaS product leaders.

Brian T. O’Neill, data product development expert, discusses 15 ways to increase user adoption of data products. Highlighted topics include designing behavior change, exposing team members to end users, changing funding models, defining intended benefits and outcomes, and approaching data product creation as a user experience.

Nick Zervoudis, Data Product Manager at CKDelta, discusses his approach to developing internal and external data products, the UX design course he took, thoughts on dashboard design, common mistakes made by data product teams, and how he manages imposter syndrome in his career.

Marnix from Coolblue shares the story of why he threw out 18 months of data science work and shifted to a human-centered, product approach. He discusses the impact on his team, stakeholders, and his personal career. The podcast also explores the challenges of building a data product culture and improving data literacy.