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If you’re a leader tasked with generating business and org. value through ML/AI and analytics, you’ve probably struggled with low user adoption. Making the tech gets easier, but getting users to use, and buyers to buy, remains difficult—but you’ve heard a ”data product” approach can help. Can it? 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 designer’s perspective on why creating ML and analytics outputs isn’t enough to create business and UX outcomes. How can UX design and product management help you create innovative ML/AI and analytical data products? What exactly are data products—and how can data product management help you increase user adoption of ML/analytics—so that stakeholders can finally see the business value of your data? Every 2 weeks, I answer these questions via solo episodes and interviews with innovative chief data officers, data product management leaders, and top UX professionals. Hashtag: #ExperiencingData. PODCAST HOMEPAGE: Get 1-page summaries, text transcripts, and join my Insights mailing list: https://designingforanalytics.com/ed ABOUT THE HOST, BRIAN T. O’NEILL: https://designingforanalytics.com/bio/
Episodes
Tuesday Apr 30, 2024
Tuesday Apr 30, 2024
Welcome to a special edition of Experiencing Data. This episode is the audio capture from a live Crowdcast video webinar I gave on April 26th, 2024 where I conducted a mini UI/UX design audit of a new podcast analytics service that Chris Hill, CEO of Humblepod, is working on to help podcast hosts grow their show. Humblepod is also the team-behind-the-scenes of Experiencing Data, and Chris had asked me to take a look at his new “Listener Lifecycle” tool to see if we could find ways to improve the UX and visualizations in the tool, how we might productize this MVP in the future, and how improving the tool’s design might help Chris help his prospective podcast clients learn how their listener data could help them grow their listenership and “true fans.”
On a personal note, it was fun to talk to Chris on the show given we speak every week: Humblepod has been my trusted resource for audio mixing, transcription, and show note summarizing for probably over 100 of the most recent episodes of Experiencing Data. It was also fun to do a “live recording” with an audience—and we did answer questions in the full video version. (If you missed the invite, join my Insights mailing list to get notified of future free webinars).
To watch the full audio and video recording on Crowdcast, free, head over to: https://www.crowdcast.io/c/podcast-analytics-ui-ux-design
Highlights/ Skip to:
- Chris talks about using data to improve podcasts and his approach to podcast numbers (03:06)
- Chris introduces the Listener Lifecycle model which informed the dashboard design (08:17)
- Chris and I discuss the importance of labeling and terminology in analytics UIs (11:00)
- We discuss designing for practical use of analytics dashboards to provide actionable insights (17:05)
- We discuss the challenges podcast hosts face in understanding and utilizing data effectively and how design might help (21:44)
- I discuss how my CED UX framework for advanced analytics applications helps to facilitate actionable insights (24:37)
- I highlight the importance of presenting data effectively and in a way that centers to user needs (28:50)
- I express challenges users may have with podcast rankings and the reliability of data sources (34:24)
- Chris and I discuss tailoring data reports to meet the specific needs of clients (37:14)
Quotes from Today’s Episode
- “The irony for me as someone who has a podcast about machine learning and analytics and design is that I basically never look at my analytics.” - Brian O’Neill (01:14)
- “The problem that I have found in podcasting is that the number that everybody uses to gauge whether a podcast is good or not is the download number…But there’s a lot of other factors in a podcast that can tell you how successful it’s going to be…where you can pull levers to…grow your show, or engage more with an audience.” - Chris Hill (03:20)
- “I have a framework for user experience design for analytics called CED, which stands for Conclusions, Evidence, Data… The basic idea is really simple: lead your analytic service with conclusions.”- Brian O’Neill (24:37)
- “Where the eyes glaze over is when tools are mostly about evidence generators, and we just give everybody the evidence, but there’s no actual analysis about how [this is] helping me improve my life or my business. It’s just evidence. I need someone to put that together.” - Brian O’Neill (25:23)
- “Sometimes the data doesn’t provide enough of a conclusion about what to do…This is where your opinion starts to matter” - Brian O’Neill (26:07)
- “It sounds like a benefit, but drilling down for most people into analytics stuff is usually a tax unless you’re an analyst.” - Brian O’Neill (27:39)
- “Where’s the source of this data, and who decided what these numbers are? Because so much of this stuff…is not shared. As someone who’s in this space, it’s not even that it’s confusing. It’s more like, you got to distill this down for me.” - Brian O’Neill (34:57)
- “Your clients are probably going to glaze over at this level of data because it’s not helping them make any decision about what to change.”- Brian O’Neill (37:53)
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