How to Research Attention in Streaming TV with Todd Nicolini, Research and Insights Contributor

How Direct-To-Consumer Streaming Gives Sports Franchises and Creators Revenue Control with Wim Sweldens, Co-Founder of Kiswe

Have a question? Send us a text! [https://www.buzzsprout.com/2512452/fan_mail/new] Wim Sweldens [https://www.linkedin.com/in/wimsweldens/], co-founder of Kiswe [https://www.kiswe.com/], built a direct-to-consumer (D2C) streaming company because he unplugged his cable box — and never plugged it back in. Twelve years later, the technology he knew was coming has arrived, and the sports organizations smart enough to own the relationship with their fans are the ones pulling ahead. The RSN Collapse Created a Blueprint Problem, Not Just a Revenue Problem When regional sports networks (RSNs) fell apart, teams didn't just lose a distribution partner — they lost the only model they knew. Kiswe's answer isn't to replace one middleman with another. It's to cut them out entirely. * 0:55 – The origin story: a crashed cable box, a 4G network, and a company * 3:16 – Why being early to mobile video wasn't a mistake — it was timing * 4:43 – What "don't sell your rights, sell your content" actually means in practice When You Own the Platform, You Own the Data Subscription, pay-per-view, dynamic ad insertion — the monetization model matters less than who controls it. Wim breaks down how Kiswe's revenue share structure aligns incentives and why direct fan data is the asset teams are finally realizing they've been giving away. * 6:30 – The three monetization models Kiswe enables and how teams use each * 8:00 – Why influencers selling 50,000 tickets at $20 each is the proof of concept * 14:03 – Why sports teams see less churn than general streaming apps — and what drives it SEG+ Is the Case Study. Utah Built It First. Smith Entertainment Group (SEG) — owners of the Utah Jazz (NBA) and Utah Mammoth (NHL) — needed one platform for two leagues, two fan bases, and games that sometimes overlap. The result: 40% subscriber growth over two years, 75% Mammoth+ growth in year one, and a MultiView feature that lets fans watch both games simultaneously. * 10:10 – How the SEG+ platform unified two franchises under a single login * 12:02 – The à la carte argument: why fans shouldn't have to buy butter to get milk * 13:27 – The retention thesis: engaged fans churn less, buy more, and bring friends Download the full SEG+ case study [https://podcast.stateofstreaming.com/downloads/kiswe-seg-case-study/] to see the numbers. Connect with Wim Sweldens on LinkedIn [https://www.linkedin.com/in/wimsweldens/] · Kiswe [https://www.kiswe.com/] Support the show [https://www.buzzsprout.com/2512452/support]

How to Measure Sports Viewership in a Streaming World with Russell Fink, Regional Sports Network (RSN) Expert

Have a question? Send us a text! [https://www.buzzsprout.com/2512452/fan_mail/new] Tim sits down with Russell Fink [https://www.linkedin.com/in/russell-fink-72832448/], a two-decade veteran of regional sports networks, to dig into the measurement crisis hiding in plain sight inside sports streaming. The conversation pairs directly with Russell's piece published in State of Streaming this week — Too Much of a Good Thing: Sports' Measurement Problem [https://www.stateofstreaming.com/articles/too-much-of-a-good-thing-sports-measurement-problem] — and uses Jurassic Park to explain why having the data isn't the same as using it. The RSN Era Was the Last Time Everyone Won at Once  Russell started at SNY in 2007, when regional sports networks were ascendant and the model was simple: hyperlocal content, cable affiliate fees, happy leagues, happy fans, happy advertisers. The streaming wars didn't just disrupt that model — they exposed that no one had a replacement. * 2:14 – What RSNs looked like at their peak and why the economics worked for everyone * 4:47 – Why the shift to streaming put RSNs into survival mode almost overnight * 6:22 – The cable bundle déjà vu: Congress wanted à la carte then, too The Streamers Inherited Linear's Habits and Called It Innovation  When Amazon, Apple, and Facebook took sports rights, Russell expected them to reinvent the viewing experience. Instead, they replicated what fans already knew — and measured it the same way. The lesson: fan behavior is stickier than distribution format. * 8:10 – Why Russell was wrong to expect streaming platforms to blow up the format * 9:33 – What Facebook's live chat experiment revealed about fan tolerance for experimentation * 11:05 – Why linear strategies persist inside streaming sports — and what that says about where the money still lives 16.7 Billion Minutes. Nobody Knows What That Means.  The NBC Olympics touted 16.7 billion minutes viewed. Russell spent his career in research and can't tell you what it means — and that's the problem. When a metric requires twenty minutes to unpack, it's not doing its job. The industry's love of big numbers is actively impeding advertiser confidence. * 14:38 – How the streaming measurement land grab produced a world where everyone is number one * 17:02 – Why "16.7 billion minutes" is a perfect example of a metric that defeats itself * 19:44 – What the better headline would have been — and why total viewers still wins Your Scientists Were So Preoccupied With Whether They Could…  The Jurassic Park thesis: the industry built fifty to a hundred new metrics it didn't have nineteen years ago, fell in love with all of them, and forgot to ask which ones actually move the business. Russell's piece is a call to simplify — not because the data is wrong, but because complexity is a sales problem. * 21:15 – Where the Jurassic Park framing came from and what it has to do with Tuesday 3:30 PM engagement spikes * 23:08 – How to think about which metrics actually serve programming, marketing, sales, and affiliate * 25:44 – Why measurement complexity is part of why the advertiser shift to digital is still stalling Part two is coming. Read the full piece at State of Streaming [https://www.stateofstreaming.com/articles/too-much-of-a-good-thing-sports-measurement-problem]. Connect with Russell Fink on LinkedIn [https://www.linkedin.com/in/russell-fink-72832448/] Support the show [https://www.buzzsprout.com/2512452/support]

How the Home Screen Became the Most Valuable Real Estate in Streaming with Looper Insights CEO, Lucas Bertrand

Have a question? Send us a text! [https://www.buzzsprout.com/2512452/fan_mail/new] Tim sits down with Lucas Bertrand [https://www.linkedin.com/in/lucas-bertrand-14782a/], CEO of Looper Insights [https://looperinsights.com/], to break down what Looper's Q1 Media Placement Value ($MPV) data reveals about how connected TV home screens are being used — and misused — heading into the biggest sports quarter in recent memory. Recorded the day the FIFA World Cup kicked off, the conversation pairs directly with the Preston Smalley/Roku episode released earlier that week. The CTV Home Screen The Arbitrage of Streaming  Looper's $MPV metric assigns a dollar value to placements across Roku, Fire TV, Samsung, Xfinity, and others — factoring in local CPM rates, device footprint, and engagement. The result is a comparable framework that lets streamers, advertisers, and platforms understand what a homepage placement is actually worth before they negotiate for it. * 4:06 – What $MPV is and the three variables that drive it: CPM, device count, and engagement * 5:59 – Why Roku's 100M device footprint makes its homepage one of the most valuable digital surfaces in media * 6:49 – The home screen as one of the most valuable websites in the world The Winter Olympics Set the Template. The World Cup Is the Stress Test.  Roku's Milan-Cortina Winter Olympics hub generated $36M in $MPV in Q1 — one of the first major hub executions on the platform and a proof of concept for what coherent sports signposting can do. With the World Cup now live across half a dozen broadcasters, multiple languages, and fragmented rights windows, the question is whether that template scales. * 14:11 – How the Milan-Cortina Winter Olympics hub performed in Q1 $MPV data * 15:43 – Why the Olympics hub is a model for Peacock, Roku, and other OEMs to build on * 16:07 – World Cup fragmentation: Telemundo, YouTube first-ten-minutes windows, and the signposting problem Live Sports Errors Are Already Appearing in the World Cup Data.  Looper monitors CTV interfaces in real time and is already surfacing errors to partners in the early days of the tournament — wrong match times, missing delay notifications, outdated location data. When a game gets rained off and every platform needs to update simultaneously, the gap between what's on screen and what's actually happening becomes a real fan experience problem. * 17:18 – How Looper monitors live event signposting in real time * 18:02 – The types of errors already appearing in World Cup data: times, locations, delays * 19:09 – Why "it's available everywhere" is sometimes no answer at all Q2 $MPV report expected mid-July. We'll have Lucas back to break it down when it drops. Connect with Lucas Bertrand on LinkedIn [https://www.linkedin.com/in/lucas-bertrand-14782a/] · Looper Insights [https://looperinsights.com/] Support the show [https://www.buzzsprout.com/2512452/support]

How to Build a $22B Home Screen with Roku VP of Viewer Product, Preston Smalley

Have a question? Send us a text! [https://www.buzzsprout.com/2512452/fan_mail/new] Tim sits down with Preston Smalley [https://www.linkedin.com/in/prestonsmalley/], VP of Viewer Product at Roku [https://www.roku.com/], unpacking the first new Roku home screen in a decade — how it was designed for 100 million+ households, what the hub methodology means for sports fragmentation, and why "delight" isn't just a brand word at Roku. It's a measured KPI. 82% of streaming viewers want you to read their mind  Roku built a home screen with a billion possible configurations to get closer to doing exactly that — and they're measuring whether it's working. Preston breaks down how Roku balances personalization with customization, why quick access felt "wrong" to users at first and indispensable a week later, and how a fictional city on your screensaver became one of the platform's most measurable loyalty drivers. * 1:51 – Designing for 100M+ households: how surveys, diary studies, and a billion possible configurations shaped the new home screen * 4:42 – What "personalization" actually means: familiar content, adjacent discovery, trending signals, and human curators working together * 6:55 – AI in practice: how Roku layers large language models on top of its proprietary TV-specific models — and why general AI alone doesn't know what episode just dropped * 8:36 – The diary study insight: why users hated quick access on day one and couldn't live without it a week later Sports on streaming is more fragmented than cable ever was Roku's answer isn't aggregation — it's destination design. Preston explains how the Roku hub methodology works: one place for a fan to find their league, their team, their game — and the app they need to stream it, or free highlights if they don't have it. The NHL hub just launched. All four major leagues are now covered. World Cup planning is underway. * 11:38 – The hub methodology: why sports fragmentation is a discovery problem, not a rights problem * 13:25 – World Cup and the Olympics playbook: medal counts, bracket tracking, and what "cultural moment" infrastructure looks like on a home screen * 14:37 – The global Roku business: #1 in the US, Mexico, and Canada — and why free live TV and antenna-blending are the growth story in Brazil Why Roku City is a screensaver It's also a brand platform, a live event venue, a trivia game host, and one of Roku's top two sources of measured user delight. * 16:55 – Roku City as loyalty infrastructure: IP partnerships, live events, Roku Dash, and why users don't experience it as advertising * 17:52 – How Roku actually measures delight — and what it has to do with finding a show you didn't know you liked Connect with Preston Smalley on LinkedIn [https://www.linkedin.com/in/prestonsmalley/] Learn more about Roku [https://www.roku.com/]at roku.com For more on how Roku is monetizing the home screen as a media property, read our full breakdown of the $MPV methodology from Looper Insights here. [https://www.stateofstreaming.com/articles/the-streaming-shelf-looper-insights-report] Support the show [https://www.buzzsprout.com/2512452/support]

How Telecom-Grade AI Personalization Can Solve Streaming Retention with Hemant Soni, AI Architect

Have a question? Send us a text! [https://www.buzzsprout.com/2512452/fan_mail/new] The conversation is a companion to Hemant's recent piece on AI personalization at scale [https://www.stateofstreaming.com/articles/hemant-soni-ai-personalization-at-scale]. Hemant Soni [https://www.linkedin.com/in/hemantsoniatlanta/], AI Architect and SOS. contributor, joins Tim Rowe [https://www.linkedin.com/in/troweactual/] to unpack what streaming platforms can learn from the infrastructure telecom companies built under survival pressure — and how to start applying it now.  On Combatting Churn Streaming platforms collect mountains of behavioral data — what you watch, what you skip, when you disengage — and respond days or weeks later with a generic retention email. By then, the subscriber has already left. The model that actually works isn't coming from Netflix or Spotify. It's coming from telecom. * 1:32 – About how telecom is mastering personalization — and why it matters for streaming * 3:05 – T-Mobile's customer decision hub: processing 140M+ subscriber signals in under 200 milliseconds * 5:33 – Comcast's convergence advantage: telecom-grade AI infrastructure applied directly to Peacock's 32M broadband customers Why "Feeling Understood" Matters Most The shift Hemant describes — from responding after a customer cancels to predicting intent before they act — is the key unlock. Customers don't feel retained. They feel understood. That's the difference between a churn intervention and a relationship. * 6:08 – What Comcast is actually deploying: not experiments, proven telecom intelligence * 7:32 – The four pillars of AI personalization and what each one means for a streaming operator * 11:17 – Where to start: a practical framework for media companies beginning the AI journey Get Hemant's 90-day Fast Start Framework  Start with personalization. It's the highest ROI use case, and once you show impact there, scaling AI gets easier everywhere else. Hemant closes with the most actionable thing in the episode — month one: identify use cases and clean your data. Month two: build and test AI models at small scale. Month three: optimize and scale what worked. * 12:42 – Building a unified data foundation: what to connect, clean, and make reusable * 13:56 – Why personalization is the highest ROI AI use case * 14:30 – Language barriers, content hypergrowth, and what AI-enabled localization actually unlocks Connect with Hemant Soni on LinkedIn [https://www.linkedin.com/in/hemantsoniatlanta/] and read his full article here [https://www.stateofstreaming.com/articles/hemant-soni-ai-personalization-at-scale]. Support the show [https://www.buzzsprout.com/2512452/support]