Diesel Labs

Our CEO Anjali Midha spoke to The Streamr about integrating AI into the entertainment industry in an ethical and sustainable way. https://lnkd.in/ePM2vG3f

2,402: the number of new TV shows and movies currently scheduled for release throughout 2024. How can we possibly know that? Because our proprietary Content Calendar is the best source for every premiere date of all content launching in the US every day. Where can you find the latest release date information when content platforms aren’t even up to date themselves? And even when you do find them, launch dates shift constantly sometimes right up to the premiere! Enter Diesel’s Content Calendar. Built on a continuous machine learning and human data curation process, our talented Data Engineering team builds and maintains the most up to date release calendar across all new content. Want a list of upcoming Horror releases? Filter by genre. Curious to know upcoming releases for an individual streamer? Search by network or platform. Want to separate TV releases from movie releases? Sort by media type. Track historical releases to understand previous release strategies and their relative performance. Make the most topical media recommendations by weighting content by release date and genre - and merge the Content Calendar data with Top TV Shows & Movies to rank by popularity. So whenever release data gets you down, plan on using our Content Calendar! For all the latest content analytics news, keep your calendars marked for Diesel Labs. Check out our data storefronts on Amazon and Snowflake for the upcoming release of this data!

Can you hear that? It’s the sound of thousands and thousands of music fans expressing their appreciation for their favorite musical artists. Today, we’re singing the praises of one of Diesel’s latest data hits: Diesel’s music dataset! Our Musical Artist dataset provides a comprehensive view of cross-platform, daily audience attention statistics for Billboard Top 200 artists of the year at any given time. A unification of all the major social media platforms, it’s the only report of its kind that truly surmises the online popularity for every top artist at any time. Speaking of top artists, the data show that on April 22, Taylor Swift had the most audience attention of any musical artist with over 51.2 million total engagements! Video killed the radio star and is definitely here to stay. Streaming video still remains a major source of attention for musicians. So Diesel’s Musical Artist data includes total engagement rollups with and without video views. For example, on the week of April 22, only 25.9% of Billie Eilish’s audience attention came from video views as opposed to Steve Aoki’s 99.7% over the same period. There’s so many applications for this golden oldie of a dataset. Social media managers for major artists can easily determine which social platforms they’re excelling on, how they’re measuring up against the competition, and if balance of engagement across video / non video is healthy or if fresh video content would be beneficial. This data set is ideal for data scientists looking to train models using engagement and popularity variables or even to optimize consumer facing results. Brands can discover partnerships with the most popular artists (especially when coupled with Diesel’s affinity data). Did you know the top beauty brand for Swifties is CoverGirl, and Make Up For Ever for Billie’s fans? All of this data is accessible for engineers and non engineers alike. Find it in our data storefronts, via API, or even via Daisy, our AI sidekick designed for media professionals We can’t help but to sing the praises of our latest data source, and we know you will too. For more data classics, keep it tuned to Diesel Labs!

What if chatGPT could reply to your live media performance questions? Now it can - Diesel Labs is excited to introduce Daisy, our new AI sidekick! Diesel’s AI sidekick (Daisy! 🌼) is a fusion of chatGPT with our vast array of real-time audience data, able to answer nearly any question about content engagement. From "what were the most popular pieces of content yesterday" to "what are people going to watch tonight" and "what did everyone think about the last episode of Doctor Who" - it's all at your fingertips. Instant access to query what people are saying about content and why, on the fly! In addition to this rich qualitative capability, we’ve also layered in all of Diesel’s quantitative knowledge, so our AI sidekick can now also answer questions like “what were the top 10 engaged with titles yesterday”, “how many engagements did Rebel Moon - Part 2: The Scargiver achieve yesterday” and even “what was Amazon’s content share of voice last week”. Diesel’s latest solution delivers answers to all your qualitative and quantitative questions immediately, giving teams back valuable time for other critical work streams. Laborious, hand-generated reports that get skimmed are a thing of the past! Daisy completely changes the process of analytics and reporting, reducing the time and manual effort it takes to sort through vast amounts of data and pulling out only insights relevant to your most urgent questions. Contact Diesel Labs today (support@diesellabs.com) for a demo or to learn how you can add Daisy, our AI media expert, to your team.

How do you know when something is truly transcending the norm? Share of Voice (SOV) attempts to get at the answer. Let’s take a look into how SOV gives insight into show and movie distribution methods. SOV gets at the question of audience share by calculating the proportion of audience engagement for a given title over total engagement from across the entire entertainment landscape. In short, it quantifies how much one particular piece of content is capturing audience attention at any given moment. One neat aspect of SOV is that we can group content in different ways to define different insights. Distribution is one of those methods, dividing content by four categories: linear, streaming, multichannel and theatrical release. Linear covers the more traditional methods of TV distribution, specifically broadcast, cable and premium. You’ll often find your favorite live sports or special events on linear, and these types of events tend to do really well with audiences. For example, the Oscars captured 93.5% share voice the day of its airing this year. Streaming covers any and all content premiering on streaming platforms. Streaming attention tends to coalesce around major original content, premieres, finales, as well as controversial episodes. Tentpole shows like Love is Blind, True Detective and Apartment 404 push the upper bounds of the list every week. Theatrical includes any major film released and distributed in theaters. Blockbuster releases garner major attention that peaks on weekends around premieres. Dune 2 for example earned a 19.08% SOV on the Friday of its opening and declined slightly to 4.18% by the second Friday. Multichannel is the newest addition to our methodology, reserved for pieces of content distributed in multiple ways simultaneously (most commonly on cable and streaming). 44 different pieces of content were considered multichannel this year including the FX / Hulu hit Shōgun. Distribution share voice can help with a wide variety of analysis and understanding. It can help you figure out optimum times to schedule content releases, either through historical analysis or anticipatory projections. It can also help with general distribution strategies like if you should release your movie to theaters or directly to streaming. It can also help to narrow or widen the lens of analysis, like contextualizing why one piece of content may not be garnering as much attention as expected. Distribution is just one of the many flavors of share of voice. For more info about SOV or other Diesel metrics, check out our data marketplaces or visit our website.

Each streaming platform boasts its own form of viewing measurement and its own methods by which to judge success. But how do you measure the impact of a piece of content? Today we look at Diesel’s Netflix data set to investigate further. Streaming performance metrics traditionally existed behind closed doors. That changed in December 2023, when Netflix publicly released viewership stats for the first time (as we’ve discussed in previous threads). But viewing hours isn’t the only way to measure performance. Diesel’s Netflix data set provides additional clarity into the success of Netflix content, coupling streaming hours from the Netflix streaming report with attention indicators to pair consumption stats with social measurement. This gives an entirely new perspective to Netflix’s self-reported viewership figures. For example, the popular drama “You” ranked 6th overall in viewership but #1 in Diesel’s measured Wikipedia page views. Meanwhile, action adventure adaptation “The Witcher” ranked number one in Diesel’s Twitter engagements but ranked 39th in Netflix’s hours viewed. While viewership will always remain a critical KPI in evaluating the impact of content, it’s important to also understand the impact it has on the zeitgeist (which is what ultimately leads to subscription activity and other desirable outcomes). This data set aims to quantify that impact. The Netflix data set is just one flavor of analysis - we’re measuring all content all the time! To learn more about Diesel’s offerings, visit our data marketplaces or visit www.diesellabs.com.

We're digging a little deeper into Netflix "What We Watched" report! This graphic compares Diesel's Attention metric to Netflix's Viewing Hours to see how they measure up against one another. While viewing hours may be a source truth for what people are watching, audience data reveals the why. Both approaches are crucial in a wholistic understanding of the media landscape." 

While fans were watching the game, Diesel Labs was grooving to the music! Here are the musicians with the highest share of voice during this year and last year’s #superbowl: 2024 1️⃣Taylor Swift - 19.5% SOV 2️⃣Beyoncé- 13.2%  3️⃣Usher- 11.6% 4️⃣Ice Spice- 3.6% 5️⃣Alicia Keys- 3.6% 2023 1️⃣Rihanna - 39.3% 2️⃣Sam Smith- 2.3% 3️⃣Stray Kids- 2.1% 4️⃣Chris Stapleton- 1.8% 5️⃣Ye- 1.8% In 2023, halftime performer Rihanna (and her baby reveal) enraptured fans almost exclusively while this year the pendulum swung the other way, with an ensemble of artists present or performing at the game sharing audience attention. Last year, Taylor Swift was 7th on the list with 1.35% share of voice while Beyoncé was 8th with 1.08%. Usher was 50th with 0.24% and Alicia Keys was 130th with 0.09%. Diesel’s share of voice is calculated across nearly 1500 of the top musicians releasing new music or notable figures in the cultural zeitgeist over the last two to three years, in this case providing insight into how specific artists captured audiences attention during the big game. 🏈 🎆 For more touchdowns and less fumbles, keep tuning in to Diesel Labs!

Sharing is caring! We’re giving the gift of one of Diesel’s most unique offerings: content share of voice (SOV) for media & entertainment! Designed for industry analysts and AI / advanced modeling alike, let's dig into what makes this insight special. We all feel the seismic pull when a piece of media truly captures our collective attention. The Grammy’s, the Women’s FIFA World Cup, Barbie – these are cultural touchstones across our shared social experience. But how do we quantify the effect of these topics? The 2024 Grammy’s generated 71.4% SOV on the day of its airing. The Women’s FIFA World Cup finals match captured 6.6% SOV the day of the finals match behind social juggernaut Big Brother at 13.8%. Barbie drove 28.97% SOV on its opening weekend. Share of voice quantifies how much of the public attention swirls around a particular topic. This level of insight requires a comprehensive representation of the zeitgeist at any given moment, something uniquely Diesel. Our unique combination of machine learning coupled with human curation measures each and every piece of content that people talk about, view, share, like and comment across every major social platform. Besides settling debates with friends, what are the practical use cases for SOV? For data scientists looking to forecast the performance of a piece of content prior to its premiere, it’s an incredible predictor of success. Given viewership intel is not available until after something airs, it’s a very valuable pre-launch KPI. Media and entertainment marketing professionals can benchmark media releases over time. For example, Fast and the Furious fans can compare #Fast9 to #FastX to #Fast1000! It also allows for some interesting micro and macro variations. We break out SOV at the title level (e.g., Barbie v Oppenheimer, streaming platforms (e.g., Max v Netflix) or distribution type (e.g., linear v streaming). The possibilities for SOV applications are endless! Share the love, and check out a free sample of Share of Voice on Snowflake today! And keep checking in on Diesel Labs to learn more about our data offerings in the future. https://lnkd.in/enAUWYGb

The cream also rises! We’ve been exploring some of Diesel’s newest data offerings. Today, we’ll be taking a look at Audience Attention Top Content for A.I. and data engineering professionals! In December 2023, Netflix launched “What We Watched”, an engagement report outlining hours watched for their titles over the past 6 months. It’s a great step towards data transparency for Netflix, but viewership statistics only paint part of the picture. Enter Diesel’s Top Content metric, a ranking of the most popular shows and movies by audience attention across. It’s the best way to understand what media is capturing audience attention regardless of social platform or streaming service. Spanning four different separate categories including All Content, TV, Movies and Top Anticipated, Top Content illuminates what’s capturing audience attention before and after premiere. The Attention metric is a favorite amongst Diesel clients because of its simplicity and comprehensive nature. It keys off of our proprietary “Attention” metric which sums all engagement types across every major social platform including YouTube, X (Twitter), Facebook, Instagram, Wikipedia and TikTok. It has a deep level of granularity, providing individualized metrics by engagement type with Video Views, Page Views, Shares, Engagements and Comments broken out individually. Not only can it help understand WHAT is popular but also WHY. The lasting power of a piece of content is easily measurable over time, as Audience Attention extends week over week for over a three year extended historical period. It also allows for easy comparison between titles even across content types, like movies v shows! Our clients utilize these insights for a variety of use cases. Research professionals within media and entertainment can expand the breadth of their data as way to expand their internal measurements and benchmarks. AI and data engineering professionals seeking to infuse their models can summarize real-time media and entertainment trends with ease. What was more popular: Barbie or Oppenheimer? Age old questions like this and more will be answered with ease! Marketing professionals wanting to know where to increase their conversation share or how to toggle spend across social platforms, look no further. Of course for those looking to go beyond the top 10 in Top Content, the extended version is available by request! Suffice it to say, Audience Attention Top Content is tops in our book! To learn more about Diesel’s latest offering, check out our data store. Or see a sample of the data on our homepage!