I’m doing things a bit differently for this episode of Experiencing Data. For the first time on the show, I’m hosting a panel discussion. I’m joined by Thomson Reuters’s Simon Landry, Sumo Logic’s Greg Nudelman, and Google’s Paz Perez to chat about how we design user experiences that improve people’s lives and create business impact when we expose LLM capabilities to our users. 

With the rise of AI, there are a lot of opportunities for innovation, but there are also many challenges—and frankly, my feeling is that a lot of these capabilities right now are making things worse for users, not better. We’re looking at a range of topics such as the pros and cons of AI-first thinking, collaboration between UX designers and ML engineers, and the necessity of diversifying design teams when integrating AI and LLMs into b2b products. 

Highlights/ Skip to 

Thoughts on how the current state of LLMs implementations and its impact on user experience (1:51)  The problems that can come with the "AI-first" design philosophy (7:58)  Should a company's design resources be spent on go toward AI development? (17:20) How designers can navigate "fuzzy experiences” (21:28) Why you need to narrow and clearly define the problems you’re trying to solve when building LLMs products (27:35) Why diversity matters in your design and research teams when building LLMs (31:56)  Where you can find more from Paz, Greg, and Simon (40:43)

Quotes from Today’s Episode

“ [AI] will connect the dots. It will argue pro, it will argue against, it will create evidence supporting and refuting, so it’s really up to us to kind of drive this. If we understand the capabilities, then it is an almost limitless field of possibility. And these things are taught, and it’s a fundamentally different approach to how we build user interfaces. They’re no longer completely deterministic. They’re also extremely personalized to the point where it’s ridiculous.” - Greg Nudelman (12:47) “ To put an LLM into a product means that there’s a non-zero chance your user is going to have a [negative] experience and no longer be your customer. That is a giant reputational risk, and there’s also a financial cost associated with running these models. I think we need to take more of a service design lens when it comes to [designing our products with AI] and ask what is the thing somebody wants to do… not on my website, but in their lives? What brings them to my [product]? How can I imagine a different world that leverages these capabilities to help them do their job? Because what [designers] are competing against is [a customer workflow] that probably worked well enough.” - Simon Landry (15:41) “ When we go general availability (GA) with a product, that traditionally means [designers] have done all the research, got everything perfect, and it’s all great, right? Today, GA is a starting gun. We don’t know [if the product is working] unless we [seek out user feedback]. A massive research method is needed. [We need qualitative research] like sitting down with the customer and watching them use the product to really understand what is happening[…] but you also need to collect data. What are they typing in? What are they getting back? Is somebody who’s typing in this type of question always having a short interaction? Let’s dig into it with rapid, iterative testing and evaluation, so that we can update our model and then move forward. Launching a product these days means the starting guns have been fired. Put the research to work to figure out the next step.” - (23:29) Greg Nudelman “ I think that having diversity on your design team (i.e. gender, level of experience, etc.) is critical. We’ve already seen some terrible outcomes. Multiple examples where an LLM is crafting horrendous emails, introductions, and so on. This is exactly why UXers need to get involved [with building LLMs]. This is why diversity in UX and on your tech team that deals with AI is so valuable. Number one piece of advice: get some researchers. Number two: make sure your team is diverse.” - Greg Nudelman (32:39) “ It’s extremely important to have UX talks with researchers, content designers, and data teams. It’s important to understand what a user is trying to do, the context [of their decisions], and the intention. [Designers] need to help [the data team] understand the types of data and prompts being used to train models. Those things are better when they’re written and thought of by [designers] who understand where the user is coming from. [Design teams working with data teams] are getting much better results than the [teams] that are working in a vacuum.” - Paz Perez (35:19)

Links

Milly Barker’s LinkedIn post Greg Nudelman’s Value Matrix Article Greg Nudelman website  Paz Perez on Medium Paz Perez on LinkedIn Simon Landry LinkedIn

Ready for more ideas about UX for AI and LLM applications in enterprise environments? In part 2 of my topic on UX considerations for LLMs, I explore how an LLM might be used for a fictitious use case at an insurance company—specifically, to help internal tools teams to get rapid access to primary qualitative user research. (Yes, it’s a little “meta”, and I’m also trying to nudge you with this hypothetical example—no secret!) ;-) My goal with these episodes is to share questions you might want to ask yourself such that any use of an LLM is actually contributing to a positive UX outcome  Join me as I cover the implications for design, the importance of foundational data quality, the balance between creative inspiration and factual accuracy, and the never-ending discussion of how we might handle hallucinations and errors posing as “facts”—all with a UX angle. At the end, I also share a personal story where I used an LLM to help me do some shopping for my favorite product: TRIP INSURANCE! (NOT!) 

Highlights/ Skip to:

(1:05) I introduce a hypothetical  internal LLM tool and what the goal of the tool is for the team who would use it  (5:31) Improving access to primary research findings for better UX  (10:19) What “quality data” means in a UX context (12:18) When LLM accuracy maybe doesn’t matter as much (14:03) How AI and LLMs are opening the door for fresh visioning work (15:38) Brian’s overall take on LLMs inside enterprise software as of right now (18:56) Final thoughts on UX design for LLMs, particularly in the enterprise (20:25) My inspiration for these 2 episodes—and how I had to use ChatGPT to help me complete a purchase on a website that could have integrated this capability right into their website

Quotes from Today’s Episode “If we accept that the goal of most product and user experience research is to accelerate the production of quality services, products, and experiences, the question is whether or not using an LLM for these types of questions is moving the needle in that direction at all. And secondly, are the potential downsides like hallucinations and occasional fabricated findings, is that all worth it? So, this is a design for AI problem.” - Brian T. O’Neill (8:09) “What’s in our data? Can the right people change it when the LLM is wrong? The data product managers and AI leaders reading this or listening know that the not-so-secret path to the best AI is in the foundational data that the models are trained on. But what does the word quality mean from a product standpoint and a risk reduction one, as seen from an end-users’ perspective? Somebody who’s trying to get work done? This is a different type of quality measurement.” - Brian T. O’Neill (10:40)

“When we think about fact retrieval use cases in particular, how easily can product teams—internal or otherwise—and end-users understand the confidence of responses? When responses are wrong, how easily, if at all, can users and product teams update the model’s responses? Errors in large language models may be a significant design consideration when we design probabilistic solutions, and we no longer control what exactly our products and software are going to show to users. If bad UX can include leading people down the wrong path unknowingly, then AI is kind of like the team on the other side of the tug of war that we’re playing.” - Brian T. O’Neill (11:22) “As somebody who writes a lot for my consulting business, and composes music in another, one of the hardest parts for creators can be the zero-to-one problem of getting started—the blank page—and this is a place where I think LLMs have great potential. But it also means we need to do the proper research to understand our audience, and when or where they’re doing truly generative or creative work—such that we can take a generative UX to the next level that goes beyond delivering banal and obviously derivative content.” - Brian T. O’Neill (13:31) “One thing I actually like about the hype, investment, and excitement around GenAI and LLMs in the enterprise is that there is an opportunity for organizations here to do some fresh visioning work. And this is a place that designers and user experience professionals can help data teams as we bring design into the AI space.” - Brian T. O’Neill (14:04)

“If there was ever a time to do some new visioning work, I think now is one of those times. However, we need highly skilled design leaders to help facilitate this in order for this to be effective. Part of that skill is knowing who to include in exercises like this, and my perspective, one of those people, for sure, should be somebody who understands the data science side as well, not just the engineering perspective. And as I posited in my seminar that I teach, the AI and analytical data product teams probably need a fourth member. It’s a quartet and not a trio. And that quartet includes a data expert, as well as that engineering lead.” - Brian T. O’Neill (14:38)

Links Perplexity.ai: https://perplexity.ai  Ideaflow: https://www.amazon.com/Ideaflow-Only-Business-Metric-Matters/dp/0593420586  My article that inspired this episode

Let’s talk about design for AI (which more and more, I’m agreeing means GenAI to those outside the data space). The hype around GenAI and LLMs—particularly as it relates to dropping these in as features into a software application or product—seems to me, at this time, to largely be driven by FOMO rather than real value. In this “part 1” episode, I look at the importance of solid user experience design and outcome-oriented thinking when deploying LLMs into enterprise products. Challenges with immature AI UIs, the role of context, the constant game of understanding what accuracy means (and how much this matters), and the potential impact on human workers are also examined. Through a hypothetical scenario, I illustrate the complexities of using LLMs in practical applications, stressing the need for careful consideration of benchmarks and the acceptance of GenAI's risks. 

I also want to note that LLMs are a very immature space in terms of UI/UX design—even if the foundation models continue to mature at a rapid pace. As such, this episode is more about the questions and mindset I would be considering when integrating LLMs into enterprise software more than a suggestion of “best practices.” 

Highlights/ Skip to:

(1:15) Currently, many LLM feature  initiatives seem to mostly driven by FOMO  (2:45) UX Considerations for LLM-enhanced enterprise applications  (5:14) Challenges with LLM UIs / user interfaces (7:24) Measuring improvement in UX outcomes with LLMs (10:36) Accuracy in LLMs and its relevance in enterprise software  (11:28) Illustrating key consideration for implementing an LLM-based feature (19:00) Leadership and context in AI deployment (19:27) Determining UX benchmarks for using LLMs (20:14) The dynamic nature of LLM hallucinations and how we design for the unknown (21:16) Closing thoughts on Part 1 of designing for AI and LLMs

Quotes from Today’s Episode

“While many product teams continue to race to deploy some sort of GenAI and especially LLMs into their products—particularly this is in the tech sector for commercial software companies—the general sense I’m getting is that this is still more about FOMO than anything else.” - Brian T. O’Neill (2:07) “No matter what the technology is, a good user experience design foundation starts with not doing any harm, and hopefully going beyond usable to be delightful. And adding LLM capabilities into a solution is really no different. So, we still need to have outcome-oriented thinking on both our product and design teams when deploying LLM capabilities into a solution. This is a cornerstone of good product work.” - Brian T. O’Neill (3:03)

“So, challenges with LLM UIs and UXs, right, user interfaces and experiences, the most obvious challenge to me right now with large language model interfaces is that while we’ve given users tremendous flexibility in the form of a Google search-like interface, we’ve also in many cases, limited the UX of these interactions to a text conversation with a machine. We’re back to the CLI in some ways.” - Brian T. O’Neill (5:14) “Before and after we insert an LLM into a user’s workflow, we need to know what an improvement in their life or work actually means.”- Brian T. O’Neill (7:24) "If it would take the machine a few seconds to process a result versus what might take a day for a worker, what’s the role and purpose of that worker going forward? I think these are all considerations that need to be made, particularly if you’re concerned about adoption, which a lot of data product leaders are." - Brian T. O’Neill (10:17)

“So, there’s no right or wrong answer here. These are all range questions, and they’re leadership questions, and context really matters. They are important to ask, particularly when we have this risk of reacting to incorrect information that looks plausible and believable because of how these LLMs tend to respond to us with a positive sheen much of the time.” - Brian T. O’Neill (19:00)

Links

View Part 1 of my article on UI/UX design considerations for LLMs in enterprise applications:  https://designingforanalytics.com/resources/ui-ux-design-for-enterprise-llms-use-cases-and-considerations-for-data-and-product-leaders-in-2024-part-1/

In this episode, I’m chatting with former Gartner analyst Sanjeev Mohan who is the Co-Author of Data Products for Dummies. Throughout our conversation, Sanjeev shares his expertise on the evolution of data products, and what he’s seen as a result of implementing practices that prioritize solving for use cases and business value. Sanjeev also shares a new approach of structuring organizations to best implement ownership and accountability of data product outcomes. Sanjeev and I also explore the common challenges of product adoption and who is responsible for user experience. I purposefully had Sanjeev on the show because I think we have pretty different perspectives from which we see the data product space.

Highlights/ Skip to:

I introduce Sanjeev Mohan, co-author of Data Products for Dummies (00:39) Sanjeev expands more on the concept of writing a “for Dummies” book   (00:53) Sanjeev shares his definition of a data product, including both a technical and a business definition (01:59) Why Sanjeev believes organizational changes and accountability are the keys to preventing the acceleration of shipping data products with little to no tangible value (05:45) How Sanjeev recommends getting buy-in for data product ownership from other departments in an organization (11:05) Sanjeev and I explore adoption challenges and the topic of user experience (13:23) Sanjeev explains what role is responsible for user experience and design (19:03) Who should be responsible for defining the metrics that determine business value (28:58) Sanjeev shares some case studies of companies who have adopted this approach to data products and their outcomes (30:29) Where companies are finding data product managers currently (34:19) Sanjeev expands on his perspective regarding the importance of prioritizing business value and use cases (40:52) Where listeners can get Data Products for Dummies, and learn more about Sanjeev’s work (44:33)

Quotes from Today’s Episode “You may slap a label of data product on existing artifact; it does not make it a data product because there’s no sense of accountability. In a data product, because they are following product management best practices, there must be a data product owner or a data product manager. There’s a single person [responsible for the result]. — Sanjeev Mohan (09:31)

“I haven’t even mentioned the word data mesh because data mesh and data products, they don’t always have to go hand-in-hand. I can build data products, but I don’t need to go into the—do all of data mesh principles.” – Sanjeev Mohan (26:45)

“We need to have the right organization, we need to have a set of processes, and then we need a simplified technology which is standardized across different teams. So, this way, we have the benefit of reusing the same technology. Maybe it is Snowflake for storage, DBT for modeling, and so on. And the idea is that different teams should have the ability to bring their own analytical engine.” – Sanjeev Mohan (27:58)

“Generative AI, right now as we are recording, is still in a prototyping phase. Maybe in 2024, it’ll go heavy-duty production. We are not in prototyping phase for data products for a lot of companies. They’ve already been experimenting for a year or two, and now they’re actually using them in production. So, we’ve crossed that tipping point for data products.” – Sanjeev Mohan (33:15)

“Low adoption is a problem that’s not just limited to data products. How long have we had data catalogs, but they have low adoption. So, it’s a common problem.” – Sanjeev Mohan (39:10)

“That emphasis on technology first is a wrong approach. I tell people that I’m sorry to burst your bubble, but there are no technology projects, there are only business projects. Technology is an enabler. You don’t do technology for the sake of technology; you have to serve a business cause, so let’s start with that and keep that front and center.” – Sanjeev Mohan (43:03)

Links Data Products for Dummies: https://www.dataops.live/dataproductsfordummies “What Exactly is A Data Product” article: https://medium.com/data-mesh-learning/what-exactly-is-a-data-product-7f6935a17912 It Depends: https://www.youtube.com/@SanjeevMohan Chief Data Analytics and Product Officer of Equifax: https://www.youtube.com/watch?v=kFY7WGc-jFM SanjMo Consulting: https://www.sanjmo.com/ dataops.live: https://dataops.live dataops.live/dataproductsfordummies: https://dataops.live/dataproductsfordummies LinkedIn: https://www.linkedin.com/in/sanjmo/ Medium articles: https://sanjmo.medium.com

Highlights  Australian singer-songwriter Tones and I and North Carolina-born/Eastern Europe-raised rapper Ashnikko are some of the first notable case studies in TikTok virality. How are they capitalizing on it?Mission   Good morning, it’s Rutger here at Chartmetric with your 3-minute Data Dump where we upload charts, artists, and playlists into your brain so you can stay up on the latest in the music data world.We’re on the socials at “chartmetric” — that’s Chartmetric, one word and no “S.” Follow us on LinkedIn, Instagram, Twitter, or Facebook, and talk to us! We’d love to hear from you.DateThis is your Data Dump for Friday, Oct. 18, 2019.The Young Female Artists Capitalizing on Their TikTok ViralityAs TikTok’s popularity intensifies, so does the scrutiny, which is why the National Music Publishers’ Association recently claimed the platform “consistently violated US copyright law and the rights of songwriters and music publishers.”Whether or not this is true, it’s clear the platform-on-the-rise, which is making its mark as a new breeding ground for discovery, is benefiting some creatives substantially.We first noticed 19-year-old Australian singer-songwriter Tones and I’s “Dance Monkey,” for instance, on the TikTok charts a couple of months back. At the time, the Sony artist’s Spotify footprint was promising, but not exactly huge.When “Dance Monkey” first came out in May, she had around 3.5K Followers.Once July hit and the TikToks started pouring in, her Spotify Follower stats rose precipitously, from 15K in July to 30K in August, 70K in September, and 150K this month.Four of the Top 44 TikTok videos are still sporting “Dance Monkey” soundtracks, and the song is still in the Top 200 on TikTok’s track charts. There’s a similar story happening with North Carolina-born and Eastern Europe-raised rapper Ashnikko, aka Ashton Casey.23-year-old Ashnikko, who embraces Japanese anime and video game references, recently dropped the collaborative track “STUPID” with Yung Baby Tate, and her TikTok climb is stunning. Six of the Top 44 TikTok videos are already using her track, and she’s also in the Top 200 on TikTok’s track charts.Right now, her stats across other platforms like Spotify are exhibiting a growth pattern similar to Tones and I’s when she first started carving out her TikTok niche, so all indications point to Ashnikko being an artist to watch going into 2020 — and not just on TikTok.With edgy, stylish teenage phenom Billie Eilish having worked wonders for Universal — are Tones and I and Ashnikko, respectively, Sony and Warner’s rebuttal? OutroThat’s it for your Daily Data Dump for Friday, Oct. 18, 2019. This is Rutger from Chartmetric.Free accounts are available at chartmetric.com And article links and show notes are at: podcast.chartmetric.comIf you haven’t downloaded 6MO, our Global Music Industry Data Report, yet, you can find it all across our socials and in our show notes!Happy Friday, have a great weekend, and we’ll see you next week! 

Highlights  Streaming might favor frontline singles, but some tracks buck the trend. Looking at Spotify, Apple, Amazon, and Deezer’s Top 100 charts, we examine what tracks and artists are able to ride the wave of longevity.Mission   Good morning, it’s Rutger here at Chartmetric with your 3-minute Data Dump where we upload charts, artists, and playlists into your brain so you can stay up on the latest in the music data world.We’re on the socials at “chartmetric” — that’s Chartmetric, no “S.” Follow us on LinkedIn, Instagram, Twitter, or Facebook, and talk to us! We’d love to hear from you.DateThis is your Data Dump for Wednesday, Sept. 18th, 2019.Post Malone Leads Track Longevity on Streaming ChartsWhen it comes to streaming, we’re trained to think immediacy and expendability, because, let’s face it, those are the kinds of qualities that characterize today’s digital singles-driven industry.On the streaming charts, however, things aren’t that simple, and some tracks can ride out their Top 100 position for more than a year. Pulling up Spotify’s Daily Global Chart on our charts tab, for example, we can scroll down a little to see chart summaries according to many different variables, including “By Time on Chart.” Within Spotify’s Top 100, Post Malone’s “Rockstar” might only be sporting a No. 81 spot, but it’s been on the chart for 508 days — that’s almost a year and a half.If we extend the Daily Global Chart to include the next 100 tracks, “Closer,” by the Chainsmokers and Halsey, might be in a precarious position at No. 199, but the track has enjoyed some 1,103 days on Spotify’s Top 200.To be clear, that’s three years.Toggling Apple’s Top 100, at No. 58, Travis Scott’s “Sicko Mode” claims the top spot, in terms of time on chart, with 361 days, or just short of a year.Meanwhile, Amazon’s Top 100 features a four-way tie at 210 days. At No. 20, it’s “High Hopes,” by Panic! At The Disco.No. 41 is Bebe Rexha’s “Meant to Be (featuring Florida Georgia Line).”No. 56 is “Youngblood” by 5 Seconds of Summer.And No. 60 is “Better Now,” by, guess who? Post Malone.Interestingly, Deezer’s Top 100 has a six-way tie at 195 days.At No. 10, it’s “Con Calma” by Daddy Yankee and Snow, while No. 19 is “Calma” by Pedro Capó and Farruko — ¾ of whom are Puerto Rican who all like to keep it cool.No. 27 is once again Post Malone, but this time, with “Sunflower,” from the Spider-Man: Into the Spider-Verse soundtrack.No. 66 is “Te Vi” by Piso 21 and Micro Tdh, No. 68 is “Adan Y Eva” by Paulo Londra, and No. 70 is “Giant” by Calvin Harris and Rag'n'Bone Man.So, while Amazon and Deezer’s track longevities might be a bit more evenly spread, they’re also significantly lower than the longest lasting tracks on Apple’s and Spotify’s charts.Another takeaway here is that Posty has managed to keep tracks from two separate releases, Beerbongs & Bentleys and the Spider-Man soundtrack, relevant — and that’s irrespective of his new album, Hollywood’s Bleeding, dominating the top of those same charts.OutroThat’s it for your Daily Data Dump for Wednesday, Sept. 18th, 2019. This is Rutger from Chartmetric.Free accounts are available at chartmetric.com And article links and show notes are at: podcast.chartmetric.comHappy Wednesday, and we’ll see you on Friday!

Highlights  On Part 1 of our streaming manipulation series, we took you on a wild ride into depths of playlist fixing. Today, on Part 2, we’re zeroing in on fake artists.Mission   Good morning, it’s Rutger here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Monday, July 1st, 2019.Enter the World of Streaming Manipulation, Part 2 - Fake ArtistsFor Part 1 of our streaming manipulation series, we covered some funny business in the playlisting world. On Part 2, we’re scratching a different part of streaming’s underbelly: fake artist accounts.Last November, Pop Buzz and others covered a mysterious account uploading ostensibly unreleased Ariana Grande tracks under the name Zandhr.As it turned out, the tracks had been available online for some time, but that didn’t change the fact that a streaming account reportedly not linked to Ariana Grande, according to the BBC, was uploading her intellectual property to potentially profit off of.While the Zandhr account has since been taken down, our data suggests the fake artist accrued 9.5K Spotify followers and almost 30K monthly Spotify listeners, in addition to landing an “Ariana Grande - Every Song” playlist with some 20K+ followers of its own.Playboi Carti found himself in a similar predicament when three different fake accounts — Lil Kambo, Unocarti, and Unocompac — started uploading his tracks, with some pitch-shifting his songs in an attempt to disguise the illegitimate uploads.While both Lil Kambo and Unocarti’s profiles appear to have been taken down, the former amassed a 50K+ playlist reach from 37 playlists and the latter almost a 20K playlist reach from 19 playlists.Unocompac, meanwhile, appears to still have at least one Playboi Carti song up, enjoying 14K Spotify followers and a 30K playlist reach from 54 playlists.The best — or worst — part is that Unocompac’s artist gallery on Spotify includes three out-of-focus nighttime shots of a white suburban teenager posing and throwing up fake gang signs.Shaking my damn head.While this all might seem rather innocuous, as most of these accounts never amass more than a couple of thousand followers, it’s important to remember ...One, fake artist accounts effectively steal intellectual property and income from the legitimate artists they’re “impersonating.”And two, fake artist accounts devalue the work of all legitimate artists who have put their blood, sweat, and tears into making and marketing their art. While this phenomenon probably isn’t something to worry about in the short-term, how it’s handled now will determine how big of a problem it becomes in the long-term.With so many metadata errors, artist-song mismatches, and unclaimed blackbox royalties as a result, the last thing artists need is an army of mysterious impersonators gaming the system. OutroThat’s it for your Daily Data Dump for Monday, July 1st, 2019. This is Rutger from Chartmetric.Free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.comHappy Monday, and we’ll see you tomorrow!

2019-06-19 // A2IM Indie Week, Day 2: Spotify’s Indie Curators HighlightsSpotify and major label curators always move the needle, but with Day 2 of A2IM’s Indie Week in the bag, we’re looking at important indies of the bunch.Mission    Good morning, it’s Rutger here at Chartmetric with your 3-minute Data Dump where we upload charts, artists, and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Wednesday, June 19, 2019.A2IM Indie Week, Day 2With Day 2 of A2IM’s Indie Week in the bag, we’re looking at important indie curators moving the needle on Spotify.Way up at the top is PopFiltr, with nearly 5 million playlist followers across 13 playlists.Boasting a 13 percent follower growth rate over the last 28-day period, PopFiltr has plenty to brag about, and artists or labels can submit their songs for consideration at popfiltr.com. Indiemono is another hidden gem, with 2.2 million playlist followers across a jaw-dropping 252 playlists, which a little something for everyone.In the last 28 days, Indiemono experienced a 3 percent follower growth rate, and they also offer an easy song submission process at indiemono.com.There’s also the indie indies, or the individual curators who are so good at what they do, they continue to kill it flying solo. Take Ignatious Pop, for example, whose 451 playlists have just over 2 million followers and a 4 percent growth rate in the last 28 days.Or Jesuss Vargas Gonzalez, whose 93 playlists have 1.5 million followers and an 11 percent growth rate in the last 28 days.Landing their playlists is probably going to be a bit harder, as they’re less about submissions and more about discoveries.Also keep an eye on up-and-comers Playlist Pop, with a 71 percent growth rate…. Independent Hits, with a 539 percent growth rate, meaning they’re probably new and growing really fast….And ambitious LA-based indie label and playlist network Plvylists (who’ve swapped out the “A” for a “V”), with a 125 percent growth rate.The more that major streaming platforms corral the radio market, the more important curators will become as promoters of what’s hot, what’s new, and what’s never been heard.OutroThat’s it for your Daily Data Dump for Wednesday, June 19, 2019. This is Rutger from Chartmetric.Free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.com.Happy Wednesday, and we’ll see you tomorrow from Indie Week!

Highlights  Do you know what a playback singer is? Or how about that Mexican Norteño music has German polka in it? I sure didn’t, but our A&R tool did!Mission   Good morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Friday, June 14th, 2019.Found on Friday: 4 Indian Playback Singers and 2 Norteño BandasSo checking into our A&R tool which roams the Interwebs for the biggest delta, or change, in between now and 28 days ago, we focus on the singular metric of total YouTube views via their artist channel.Looking at the Top 20 biggest gains, what’s not surprising? Billie Eilish at #5, that’s cool, Will Smith at #7 after the new Aladdin movie releasing, that’s also awesome…But you know what’s really hot? Indian playback singers, because they occupy positions 1 through 4!A playback singer in Bollywood masterfully records world-class vocals for songs for the on-camera actors to lip-sync to during shooting. For us Westerners who are obsessed with authenticity, let’s just imagine a publicly accepted form of lip-sync that not only helps create great Indian movies, but also celebrates the playback singers themselves.In the #1 spot is Calcutta-born Kumar Sanu with 30% YouTube view growth to 16.5M, who also just appeared on TV show Sa Re Ga Ma Pa L'il Champs, which pits 5-15 year olds against each other in a singing competition.In the #2 position is Arijit Singh who saw 20% YouTube view growth to 18.7M, and just released “Bekhayali” from Indian dramatic film Kabir Singh on June 3rd.Coming #3 on our list, but #1 in the Bollywood industry, is Lata Mangeshkar with 19% view growth to 9M, but it’s honestly a footnote to one of the most well-known and highly-respected playback singers ever.Mangeshkar has been listed in the Guinness Book of World Records as the most recorded artist with over 30K tracks in 20 different languages, the recipient of the Bharat Ratna,    India’s highest civilian honor (equivalent to the US Presidential Medal of Freedom), recipient of France’s Legion of Honour, and publicly selected as 10th Greatest Indian of modern times.How’s that for achievement? I really don’t think she cares about her YouTube views right now, nor should she. Hats off to her.Moving to Mexico, Norteño music is a genre of Northern Mexico that blends German polka and waltz traditions with Mexican ones.For all of us not familiar with Mexican music, the key instruments that define Norteño is the accordion (gracias a los europeos) and the bajo sexto, which translates to “sixth bass”, and looks like a 12-string guitar, but is used as a bass instrument.Now in the #6 position is Los Invasores De Nuevo León, with 10% YouTube view growth to 26M.The Latin Grammy-nominated Los Invasores, or “The Invaders of Nuevo León”, formed in 1978, and are currently on tour in south Texas,In the #16 position is Los Tucanes De Tijuana, with 5% view growth to 132M.“Los Tucanes”, or “The Toucans of Tijuana”, made history this year as first norteño act to play Coachella, also getting keys to the city.And if you want to catch up with some meme action, look up the “La Chona” challenge...their fast-paced 1994 record received a revival last year when uploaders recorded themselves dancing to “La Chona” outside their moving vehicles, a la Drake’s “In My Feelings”.OutroBueno! That’s it for your Daily Data Dump for Friday, June 14th, 2019. This is Jason from Chartmetric.Please give us a shout-out on iTunes. If you’re on an iPhone, dodge those crafty notifications and just scroll down on the Daily Data Dump page in your Apple Podcasts app or in the Ratings and Review tab in your iTunes app on your laptop, and show some love, Rutger and I appreciate it.Free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.comHappy Friday, have a great weekend, and see you on Monday!

2019-06-06 // Excursion Thursday: Honoring D-Day With Popular Normandy Locals in Rouen, France HighlightsIt’s Excursion Thursday, and in honor of D-Day, we’re heading to Rouen, France, to see which Normandy locals are the most popular right now.Mission   Good morning, it’s Rutger here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Thursday, June 6th, 2019.Excursion Thursday: Honoring D-Day With Popular Normandy Locals in Rouen, FranceOn this D-Day edition of Excursion Thursday, which marks 75 years since the Normandy landings during World War II, we’re heading to Normandy’s capital, Rouen, France, to see which Normandy locals are the most popular right now.During the Middle Ages, Rouen was one of the most important cities in Europe, and in 1944, it was left in ruins in the aftermath of D-Day operations. Today, the city has a population of somewhere around 112,000, and its most notable current or former local from the music world is 19-year-old tropical house DJ and producer Petit Biscuit — remember him from Monday’s episode?He’s currently the 685th most popular artist on Spotify according to monthly listeners and is ranked a bit more than 2,000th across Spotify, YouTube, Deezer, SoundCloud, Instagram, Facebook, Wikipedia, and Twitter, according to our new Cross-Platform Performance, or CPP, score. While Kanka’s “deep and hypnotic bass” has him at around 36,000th when it comes to monthly Spotify listeners, across all platforms, the dub star is at around 89K, according to CPP.Indie pop outfit Tahiti 80, who formed while students at the University of Rouen, are arguably the more popular locals, with a Spotify monthly listener rank that’s barely higher than Kanka’s, but with a CPP ranking of around 25K, that puts them some 63,000 spots ahead of fellow compatriot Kanka and almost 23,000 spots behind Rouen comrade Petit Biscuit.Rouen indie rockers La Maison Tellier seem to have a bit more uniformity between their Spotify monthly listener rank of 48K and their CPP ranking of around 59K.Outside of Normandy, Parisian DJ David Guetta is ranked 18th on Spotify but 9th according to CPP, and Parisian legend Serge Gainsbourg is in the mid 5,000s and around 3,000th.And for a little global perspective, Taylor Swift is ranked 16th on Spotify but 5th according to CPP, Beyonce is 46th and 15th, Ariana Grande is 9th and 2nd, and the Beatles are 114th and 103rd. Keep in mind, however, that there are an estimated 1.5 million artists in this data pool, so even Kanka’s CPP rank of almost 89,000 puts him in the top 6 percent.Not too shabby.OutroThat’s it for your Daily Data Dump for Thursday, June 6th, 2019. This is Rutger from Chartmetric.Free accounts are at app.chartmetric.com/signupAnd article links and show notes are at: podcast.chartmetric.com.Happy Thursday, thank you to all of our veterans out there, and see you tomorrow!

Highlights  It’s New Music Friday Monday, and we’re checking out some do-it-yourself artists on Deezer’s Radar Weekly playlist with 141K global fans.Mission   Good morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists, and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Monday, June 3rd, 2019.New Music Friday Monday: Deezer’s Radar Weekly DIY artistsWelcome back to the work week! Today we’re checking out not Spotify’s “New Music Friday” nor Apple’s “Best of the Week”, but Deezer’s Radar Weekly playlist with 40 new releases.Taking the top three playlist positions are the 808-driven track “Mother’s Daughter” from Miley Cyrus and Sony, the electropop record “Never Really Over” from Katy Perry and Universal and then the mid-tempo “Find U Again” track by Mark Ronson and Camila Cabello, also from Sony.But as Radar Weekly is Deezer’s 149th most followed playlist, these leading positions might not mean much to Deezer’s wider audience...the platform’s most popular playlists are geographic-specific featuring more domestic repertoire.So even though Radar Weekly is self-described as having the “biggest new releases of the week”, Deezer’s listeners seem to prefer music that speaks to their own culture without outside influence.However, since this playlist’s 141K fans probably come to Radar Weekly for more of a global sound, we thought it’d be worth checking out some DIY artists who also prefer doing their own thing, without the influence of a label. So in the #8 slot is DIY pop star Lauv living up to the sadboi persona with the melancholy anthem “Sad Forever,” marking the 2nd single off of his upcoming sophomore LP, “How I’m Feeling.”On Spotify, Lauv has a Popularity Index of 88 out of 100 and 26M Monthly Listeners, and remains an independent artist thanks to a licensing deal with Kobalt’s AWAL.Check out the mostly Asian-driven playlist evolution of his 2017 hit track “I Like Me Better” in a recent article we’ve written in the show notes.In the 23rd spot on Radar Weekly is “We Were Young,” by French DJ and music producer Petit Biscuit, who self releases his music on his own label, aptly titled Petit Biscuit Music.His soul-infused tropical house comes from a mind only 19 years old, already collecting some 320K Deezer fans, with a Spotify Popularity of 77 out of 100. Last but not least is dodie, an English singer-songwriter and YouTuber who also self-releases her music, including the minimal-sounding and intimate track “Guiltless” in the #30 position this week.She’s racked up over 8K Deezer fans, over 1M Twitter and IG followers and over 1.8M YouTube subscribers, sans label. So while major pop stars might seem to outshine the do-it-yourselfers at the top of playlists like Deezer’s Radar Weekly, take a chance and hit shuffle play, cause you just might find a few new DIY artists to follow. Outro That’s it for your Daily Data Dump for Monday, June 3rd, 2019. This is Jason from Chartmetric.Free accounts are at app.chartmetric.com/signupAnd article links and show notes are at: podcast.chartmetric.comHappy Monday, see you tomorrow!

HighlightsIt’s Winner Wednesday and we’re looking at who got added to the most Apple Music playlists in the past 30 days...and the winner is the polar opposite of Taylor Swift!Mission   Good morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Wednesday May 15th 2019.Winner Wednesdays: Apple Music “Trending on Playlists”One chart that we like to check out occasionally is the “Trending on Playlists” chart that we compile here at Chartmetric.Trending on Playlists finds the tracks that were added to the most playlists in the past 30 days and sorts them in descending order.So we’re essentially looking at not just what the editorial playlists are doing, but also what the 3rd party curators are including to see what the platform’s entire user base is favoring. This is useful because it’s theoretically closer to what “the people” are interested in, as opposed to just what the platform itself is trying to promote.But in addition to that, it tends to uncover interesting mini-trends that are underway yet likely unnoticed. Let’s check this out for Apple Music. For yesterday, May 14th, we see a few things that are totally expected.For example, of the top 200 trending in playlists tracks, the #1 most popular genre tag is “pop” at 52 instances. Hardly surprising. Neither is the #2 genre tag, “hip-hop/rap” at 28 instances.When we look at the top most added tracks, we find familiar faces: Taylor Swift leads in the #1 slot with “ME! (feat. Brendon Urie)”, which was released about 3 weeks ago and added to 236 Apple Music playlists since then.Ed Sheeran and Justin Bieber’s new “I Don’t Care” single was barely in 2nd place with 234 playlist adds and only released last week, and Shawn Mendes’ 2-week-old “If I Can’t Have You” comes in 3rd place with 223 playlist adds.The #4 and #5 entries show a significant dropoff at 123 and 101 adds respectfully, which go to Kygo and Rita Ora’s single off the new Pokémon movie soundtrack and Madonna’s recent Latin collaboration with Maluma.The rest of the top 200 are below 100 playlist adds and slope down more gently...this shows that at least for yesterday, the cumulative playlist adds are very focused on only a handful of tracks. A few spot checks earlier in 2019 show the same trend on Apple Music. So it’s good to be in the limelight….if you’re one of the chosen few.Another neat trend is about ¾ of the top 200 trending in playlists tracks are 1 week to 1 month old, and if you include the really new releases within 1 week, you are looking at 90% of the list.This is certainly expected as new releases would tend to be what’s added to the most playlists in the past 30 days.But what might be surprising is that 21 of these tracks are pre-releases, which is an Apple Music exclusive feature to date: Madonna and Maluma’s track, Mark Ronson’s new release with Lykke Li and 19 other tracks haven’t been officially released with their album, because those dates are still in the future.This goes to show that Apple is clearly using this new pre-release mechanism to great effect with some of the industry’ biggest names as something that helps Apple promote Apple, as well as artists pump up their stream counts and saves upon official album release.Last but not least, a third cool insight about trending on playlists are some of the lesser known music that gets highlighted: for example, the label with the most playlist adds yesterday was not a major, but indie label Moon Blanket Records with 25 tracks, far ahead of the second place label with only 10.Moon Blanket runs music for the two most added artists yesterday- Cover Kid with 15 adds and Filtered Light with 10- who respectively make relaxation music.Cover Kid’s playlist adds include piano soundtrack renditions from popular American animated films like “Up”, “Mulan” and “Inside Out”, while Filtered Light produces religious flute-oriented instrumental tracks.And if you think their adds don’t sound like much, Cover Kid has 518 unique track-playlist instances throughout the Apple Music ecosystem while Filtered Light has 859...which is pretty awesome for any act, let alone an indie label.So if you’re looking for some unique playlist behavior, feel free to check out any of our Trending on Playlist charts...and in the meantime, I’m going to go learn the flute.OutroThat’s it for your Daily Data Dump for Wednesday May 15th 2019. This is Jason from Chartmetric.Free accounts are at app.chartmetric.com/signupAnd article links and show notes are at: podcast.chartmetric.com.Happy Wednesday, see you tomorrow!