BACK TO ALL BLOGS Elevate Sports Ventures and Hive: Super Bowl LVI Telecast Generates $170 Million in Equivalent Media Value for In-Game Sponsors Top sponsors are expected to receive an additional 3.5 to 4.5 minutes of televised screen time from Super Bowl-related news and highlights per minute of in-game exposure earned HiveFebruary 14, 2022July 4, 2024 At a glance While commercials typically dominate water cooler conversation following the big game, brand exposure within the Super Bowl telecast can earn league, broadcast, and stadium naming rights sponsors as much, and in some cases more, visibility.According to analysis by Elevate Sports Ventures and Hive, in-game exposure translated to $170 million in Equivalent Media Value earned by brand sponsors.Excluding commercials, more than 75 minutes of cumulative in-game brand exposure was earned by brands during the Super Bowl LVI telecast, and 19 brands earned more than 10 seconds of screen time.The cumulative screen time of in-game brand exposures was down 28% compared to last year’s Super Bowl. The reduced exposure was primarily driven by less camera-visible in-stadium signage, most notably including branded tarps covering the lower seats of the stadium during last year’s game which had limited attendance due to the pandemic.According to analysis using Hive’s logo detection and brand mentions models, Nike was the most visually exposed brand with more than 46 minutes of time on screen, while Pepsi received the most verbal mentions during the telecast with 11.The value from in-game exposure will be amplified across TV from Super Bowl-related coverage in news and highlights; based on analysis of last year’s Super Bowl, top sponsors should expect to receive an additional 3.5 to 4.5 minutes of televised logo exposure for every 1 minute of in-game exposure earned.Historical analysis suggests that SoFi, which holds the host stadium’s naming rights, will likely receive the most televised brand amplification relative to the brand’s in-game exposure, led by an outsized share of coverage on news and entertainment programming likely to film outside of the stadium. As is the case every year, the Super Bowl is not just the pinnacle of the NFL season but also the tentpole event for brands looking to capture the attention of fans in and around the game. On the field there was only one winner on Sunday but, off the field, a host of brands will claim victory from their roles within TV’s biggest night. While commercials typically dominate water cooler conversations among viewers, brands know not to overlook the value earned from brand exposure generated within the telecast itself. With 30-second spot costs for Super Bowl LVI reported to be as high as $7 million, the value generated from in-game brand exposure can be massive. Elevate Sports Ventures, a best-in-class sports and entertainment consulting firm, and Hive, a leading provider of cloud-based AI solutions, teamed up to analyze in-content brand exposure within and around Super Bowl LVI. The following next-day insights were generated using Hive’s AI-powered media intelligence platform, Mensio, which provides always-on measurement of in-content brand exposure for more than 7,000 brands across 24/7 programming from national TV channels and regional sports networks. Mensio is trusted by a diverse set of leading brands, rights holders, and agencies to measure the value of and share of voice from sponsorship activations, product placement, and other in-content exposures. Brands earn $170 million in equivalent media value from in-game exposure… Excluding commercials as well as the official pre-game and post-game shows, more than 75 minutes of cumulative in-game brand exposure was earned by brands during the Super Bowl LVI telecast, and 19 brands earned more than 10 seconds of identifiable screen time. Coupled with the value from verbal mentions within the telecast, this translated to $170 million in equivalent media value, according to Mensio’s proprietary valuation methodology. The total value earned by brands was roughly in-line with the $169 million earned from in-game brand exposure in last year’s Super Bowl but was generated with 28% less cumulative in-game screen time for brands compared to last year’s Super Bowl. The reduced exposure was primarily driven by less camera-visible in-stadium signage, most notably including branded tarps covering the lower seats of the stadium during last year’s game which had limited attendance due to the pandemic. Predictably, a subset of top league, broadcast, and stadium naming rights sponsors dominated the in-game share of voice (see Figure 1). Figure 1 – Cumulative Time on Screen Within Super Bowl LVI Telecast (Excluding Commercials) Nike, the league’s on-field apparel sponsor, led the pack with a staggering 46 minutes and 37 seconds of cumulative screen time from TV-visible brand exposure from swooshes on jerseys and cleats. Two of the NFL’s official sideline sponsors – Gatorade and Bose – were the next most exposed brands in the telecast, earning more than 8 and 5-and-a-half minutes of in-game brand exposure, respectively. Pepsi again headlined the star-studded Super Bowl LVI Halftime Show, of which related in-game references contributed most of the brand’s 3 minutes and 49 seconds of visual exposure within the game, along with some in-stadium signage on the stadium’s second level. Broadcaster NBC provided the most opportunities for in-game exposure, with 15 brands being exposed through digital billboards and set signage – in addition to a broader set of brands featured in the official pre-game and post-game shows. Toyota, which sponsored the network’s halftime report, led the group with almost 2 minutes of in-content exposure within the game. Stadium naming rights sponsor, SoFi, made headlines for reportedly paying more than $30 million in fees annually as part of a 20-year naming rights deal. The brand ranked 8th in total visual exposure and 3rd in verbal mentions during Super Bowl LVI, with whistle-to-whistle exposure within last night’s telecast alone worth more than $3.5 million in equivalent media value, based on Mensio’s valuation methodology. However, the brand received noticeably less identifiable exposure than last year’s stadium naming rights holder, Raymond James, which earned roughly three times as much exposure in the 2021 game. While season-long league sponsors led the pack in visual exposure in-game, the leaderboard for verbal mentions told a different story (see Figure 2). Halftime show sponsor Pepsi, NBC’s halftime report sponsor Toyota, and stadium naming rights holder SoFi captured more than half of all brand mentions, with 11, 6, and 5 whistle-to-whistle mentions during the telecast, respectively, excluding commercials and promotional units for the halftime show. Figure 2 – Visual vs. Verbal In-Game Brand Exposures Within Super Bowl LVI Telecast (Feb 13, 2022; Excluding Commercials) While we can close the book on brand exposure within last night’s official telecast, the value of media exposure earned by featured brands will continue to accumulate in the days ahead as Super Bowl LVI remains topical in content across television and social media. Using Hive’s Mensio platform, which provides always-on measurement of brand exposure across 24/7 television programming, a comprehensive view of the incremental value from televised brand exposure can be understood. Based on analysis of last year’s Super Bowl LV, top sponsors should expect to earn an additional 3.5 to 4.5 minutes of televised logo exposure next-day for every 1 minute of in-game exposure (see Figure 3). Although those equivalent ad units are not valued at the same spot cost as the game itself, they produce a meaningful amplification of brand exposure beyond the whistle-to-whistle measurement. “The amplification from in-game exposure in highlights and news coverage has long been notoriously undermeasured, namely due to limitations from legacy measurement solutions that have relied on largely manual processes,” said Dan Calpin, President, Hive – Enterprise AI. “The ability to measure the amplification of sponsorship placements accurately and at scale provides brands and rights holders alike the opportunity to more fully value their placements.” Figure 3 – 2021 Case Study: Increase in Total Time on Screen from Super Bowl-Related Exposure As measurement capabilities have further developed in recent years, marketers have jockeyed not just for which sports and programming to align their brands with but also for how to increase both the impact and efficiency of their investments. “There are many ways for brands to deliver content, ranging from official league partnerships, team partnerships, broadcast partnerships, athlete endorsements, to name a few. Across sports, brands are looking for what will deliver the most connectivity and relevancy to its target audience. The data now allows us to help brand’s decide where to invest to yield the greatest return.” said Cameron Wagner, Chief Client Officer at Elevate Sports Ventures who leads the company’s brand-specific consulting services. In Super Bowl LVI, apparel brands commanded two-thirds of total screen time among brands within the telecast. This group was led by ubiquitous Nike swooshes, but also included exposure by Oakley-branded helmet visors and New Era-branded hats as well as a handful of native exposures for Adidas, Under Armour, and Air Jordan. Among the other asset types, league sideline sponsorships earned the greatest exposure with 57% of the remaining screen time, followed by promotion for the Super Bowl LVI Halftime Show (15%), and broadcaster-controlled assets (13%). Interestingly, the amplification of sponsorship assets appears to be non-linear, according to data from Mensio on Super Bowl-related exposures across all nationally televised programming following 2021’s Super Bowl LV (see Figure 4). These trends are expected to be representative of expected brand exposure following 2022’s Super Bowl LVI. While exposure for 2021’s stadium naming rights holder Raymond James earned only 9% of all visual brand exposure within the game (excluding apparel sponsors like Nike), the brand earned a staggering 45% of the amplification within non-sports programming across national television, led by numerous news and entertainment programs across TV networks filming coverage onsite on the night of and the day following 2021’s Super Bowl LV. This year’s stadium naming rights holder, SoFi, is likely to earn a similar boost in exposure in the days to follow. Within sports programming, including the official post-game show as well as SportsCenter and other sports highlights shows on the night of and day following the game, post-game amplification favored the sponsorship assets on and nearest to the field. The league’s three official sideline sponsors (Gatorade, Bose, and Microsoft) and a handful of other in-stadium sponsors amassed 89% of the Super Bowl-related exposure among non-Apparel brands within sports programming through the Monday after the 2021 game, compared to 68% in-game. While attention paid to broadcast sponsors – which typically include paired visual exposures and verbal mentions – may well be higher within game, those types of sponsorship placements typically earn less post-game amplification since those placements predominantly occur in between plays. Figure 4 – 2021 Case Study: Cumulative Time on Screen from Super Bowl-Related Exposures, Mix by Asset Type (Feb 7-12, 2021; Excluding Commercials and Apparel Brands) In-game signage and product placement may not make you laugh or cry in the same way that Super Bowl commercials do, but it’s hard to argue the volume of in-game exposure earned by top sponsors doesn’t help brands break through. About Hive Hive is the leading provider of cloud-based enterprise AI solutions, helping companies use AI to interpret video, image, audio, and text. The company offers end-to-end AI services, including pre-trained AI models served via API and a suite of enterprise applications. Hive’s technology enables use cases including automated content moderation, brand protection and platform integrity, content-based ad targeting, advertising and sponsorship measurement, and more. Hive processes billions of API requests per month, with industry-leading accuracy enabled by Hive’s full-stack approach. For more information, visit thehive.ai or follow on LinkedIn. About Elevate Sports Ventures Elevate Sports Ventures is a best-in-class sports and entertainment consulting firm, providing proven, innovative solutions to organizations across the global sports and entertainment landscape. Elevate taps into the extensive resources, relationships, and expertise of its partners to innovate and execute comprehensive strategies and solutions in Venue Renovations, Sales and Marketing, Stadium Licenses, Premium Ticketing, Corporate Hospitality, Customer Research, Strategy and Analytics, Sales Training, and more. Formed in partnership between the San Francisco 49ers and Harris Blitzer Sports & Entertainment (HBSE) in 2018, Elevate welcomed Oak View Group (OVG), Ticketmaster and Live Nation as partners in June, 2018. For more information, visit: www.ElevateSportsVentures.com or follow @ElevateSV on Twitter or LinkedIn.
BACK TO ALL BLOGS Ads More Expensive Than Ever on Superbowl Sunday Hive President Dan Calpin joins Bloomberg Business of Sports Podcast hosts Michael Barr, Scarlet Fu, and Mike Lynch. They break down the big winners of Superbowl Sunday, where ads were more expensive than ever. HiveFebruary 14, 2022January 23, 2025 Listen to the episode at the Bloomberg Business of Sports Podcast. [TRANSCRIPT] This is Bloomberg Business of Sports with Michael Barr, Scarlet Fu, and Mike Lynch from Bloomberg Radio MB: This is the Bloomberg Business of Sports show, where we explore the big money issues in the world of sports. I’m Michael Barr, SF: I’m Scarlet Fu, ML: and I’m Mike Lynch, MB: And today we are talking big money. I mean big, big, big, big money, with Super Bowl ads more expensive than ever. Let’s break down the big winners of the night with Hive Enterprise AI President, Dan Calpin. Dan, welcome to the podcast. MB: First of all, there were a lot of ads out there, but it seems to me the one that really dominated, and caught my eye because I’m an old man, looked like an old pong game. And I didn’t get it at first, but I guess it was like for Coinbase or something? DC: Hi and thanks for having me. And yeah, that will probably go down in history as maybe the best direct response ad ever put on television. That was definitely a fun one. SF: You’re referring to the one with the QR code, where people kind of stared at it and couldn’t believe that it was still on 15 seconds later and finally took a picture of it and decided they needed to do something about it. What does that say about advertisers’ need to rely on star power? Because when I was watching the ads, which I enjoyed, I saw a lot of big names – Gwyneth Paltrow, Scarlet Johansson, Lebron James, the Joneses, the various Joneses – and I couldn’t remember what company they were advertising for. I just remember seeing them and thought that it was really funny, but I couldn’t tell you which company made the pickup truck that Leslie Jones, Rashida Jones, and Tommy Lee Jones were driving for. DC: It’s a great point, Scarlet. And I think different brands have different approaches for both what they’re trying to achieve with their ads, but also who they’re trying to connect with, and I think so much of the value of the commercial isn’t, anymore, just the 30 or 60 seconds that you’re in the program itself, but all of the amplification before and after on social media, cetera. I think the other opportunity though that you bring up is, if I were to say “What is the headphone sponsor of the NFL?” or “Which company produces the jerseys?,” I bet all three of you or the folks out in the audience would know that, and that’s the angle that we at Hive and our partners at Elevate Sports Ventures covered looking at yesterday’s game, which moved beyond the traditional ad – the 15 and 30 seconds – and actually looked at the brands that were exposed in the content. And that’s a massive amount of value. So we ended up estimating that there’s north of 170 million dollars of value generated inside the game from the brands that were exposed during yesterday’s telecast, excluding commercials. ML: Hey Dan, this is Mike Lynch in Boston. I’m fascinated at all this data that you people have accumulated over here. So are you saying that maybe going forward that the best return might not be that 30 or 50 second spot? DC: I think the interesting thing with marketing is, unlike the game where they’re one winner on the field, there’s lots of brands that can claim victory, and depending on what you’re looking for, there’s different ways to connect with your audience and get value from the game. But with traditional commercials, those have been understood and well-measured for decades, and the opportunity that we see with sponsorship and branded content is that it represents billions of dollars of investments, but historically there’s never been a consistent or scalable way to measure that. Most brands have looked at, kind of, whistle-to-whistle measurement, from the time a game starts to the time a game ends, but no one really has put all those pieces together to truly value how much that exposure is worth, both across brands, but also across every second of every program of television or other types of media. MB: We’re talking with Dan Calvin with Hive Enterprise. The prices of a Super Bowl ad on TV are just going up and up and up and up and it is not going to stop. The NFL obviously is king, and as long as they have a product – and a great product that they have delivered so far this season that has just ended – the ads are going to continue to climb. DC: Yeah, I think that’s right. In general, brands want to be associated with both where audiences are and where they find value with the content, and I think the NFL and live sports in general will always be a place that brands find heavily-engaged audiences and value in associating. And I think in the same way that, if you were to go to an electronics store and wanted to find a good set of headphones, very likely if you’ve watched NFL games Bose would be in your consideration set, because every Sunday and, you know, every Thursday and Monday, you’re exposed to that brand within the game that you love, and if it’s good enough for your coaches to hear, there’s probably that presumption that it’s good enough for you. SF: So now that you collect all this data from companies that have brand exposure in the actual game rather than during the commercial breaks, what is the takeaway for some of the smaller companies who may not have the budget to do their traditional advertising, but have an opportunity to be part of the game itself, the content itself? What is the takeaway for them in coming Super Bowls or live sports events? DC: It’s a great question Scarlet, and I think that our friends that Elevate Sports Ventures who we published the report along with today work with brands and right holders on this question every day. And I think if you think of the question which is as simple as, “I want to be a part of the NFL,” there’s a lot of different ways you can do that. You can buy an ad in an NFL game. You could be an official league sponsor like a Microsoft or a Gatorade or a Bose. You could be a team sponsor at any of the local stadiums. Or you could be a broadcast sponsor with NBC and CBS and Fox. And so I think increasingly, with those options, you actually need data to make those choices. And so for us at Hive, being able to produce the data that isn’t just whistle-to-whistle measurement on where your brand is, but actually the landscape of sponsorship and branded content more broadly – being able to put a value on how much that is worth helps companies like Elevate work with their clients to able to make better decisions that are more informed with data. ML: So Dan, some of these exposures are pretty much by accident. Let’s say there’s a bumper shot. We’re going to commercial break and they go outside and there’s a drone or a blimp that’s showing and you see “SoFi, SoFi, SoFi” all over the place. That’s just bonus on top of what they pay for the naming rights, correct? DC: It’s a good question. I don’t know if it’s necessarily – or said differently, it’s not necessarily committed in contracts, but you can bet that SoFi I think paid 625 million dollars for 30 year naming rights and a big piece of that was knowing that that brand would be front and center on screen with obviously a game like yesterday being the largest exposure. SoFi is actually an interesting story. Given the profile of both the beautiful stadium in Los Angeles, but also all of the funds that went into naming it, if you look at the exposure that SoFi got during the game yesterday whistle-to-whistle, it was actually only about a third of what last year’s stadium naming rights sponsor Raymond James received in Tampa. And to your point Mike, I think that you can’t control that perfectly, but what’s actually really interesting, and I think probably the most compelling part of the data set and platform that we built, is that there’s no doubt that SoFi is going to be a winner from this week. We’ve already seen it with all the pre-game game coverage where not just sports, but news and entertainment are broadcasting outside of the stadium and essentially presenting a billboard for SoFi. And so that ability, even if it’s not specifically committed, but to be able to understand and value how much equivalent media value you’re getting from sponsorship placement – for brands, can help them essentially both measure your return on investment and return on objectives, but also pay the right amount of money and help make those decisions. And then for the rights holder, if you know how much value is being created from your asset, even if it’s not specifically what you’ve committed to delivering, that can actually help inform how you price your assets. [ad] MB: Is it a mistake for advertisers to show off their ad online before you see it on the Super Bowl? Because part of the excitement of seeing the ads is that hey, I want to see it debuted, but sometimes it sneaks over onto certain websites and it kind of takes the luster away from it. Am I right or am I wrong? DC: I think the answer is probably in the respective brand. The challenge with the Super Bowl, and especially with commercials, even though they’re kind of a second game in and of themselves, there’s still lots of brands competing for attention, and you’re counting on that one 30-second moment in time to be able to capture the attention of the world. And so the benefit of pre-releases and post-releases is that it creates reach and exposure so that you have more opportunities to meet folks, but I think there’s a broader, interesting point of, if you’re kind of placing your bet on exposure on those 30 seconds, that does key up again the value in relative terms of sponsorship placement. So if you look at yesterday’s game, the top 8 brands by duration, if you take commercials and/or time in the game, actually didn’t air a commercial in the game. So if you take a brand like Nike, they had a cumulative amount of minutes that were more than 46 minutes of duration, that there were swooshes on jerseys, on sleeves, on gloves, and if you go down the list, I think in total we had 8 or 9 brands had more than a minute of exposure. And obviously you don’t have the sight and sound in a theater of telling a commercial, but if you think of opportunities to associate your brand with the NFL and just be top of mind with the world’s audience, there’s a really compelling opportunity with sponsorships and branded content. SF: Do companies reach out to you to say or to ask, “How can I be the next Nike to affiliate myself, align myself more closely with the NFL?“ DC: Yeah, so at Hive, our business is really focused. So one step back – we’re predominantly a technology company in the AI space. Hive helps companies use AI to interpret video, image, text, and audio, and historically clients have built their own solutions around our technology for a diverse set of use cases, whether that’s out of domain, like content moderation for social networks, or content-based ad targeting for video publishers. And part of our focus over the last couple of years has been selectively building an application for ourselves for select use cases. And in this space specifically, we saw a market where the adoption of quote unquote AI was early, and the demand for data and insights AI produced was very underserved. And so the media and advertising industry broadly was an area that we saw opportunity in, and within it, sports sponsorship was an area that was ripe for disruption – historically characterized by very ad hoc and mostly manual measurement, which was frustrating clients who would have to wait weeks long for data and still only have part of the picture. And so we took our core technologies of world-class logo detection, object detection, speech-to-text models as building blocks, and then actually set up our own content ingestion pipeline so that we could feed always-on data into those models, and then built out a point-and-click platform to put more comprehensive and granular data in the hands of brands, agencies, and right holders. So today we work with a broad and diverse set of rights holders and TV networks like Disney, some of the world’s largest and most active brands and sponsorships like Anheuser Busch or Walmart, and a whole host agencies and consultancy partners, including Elevate sports Ventures who we published last night’s report with, who can kind of take our data, but then use that with their clients to turn it into really actionable insights. ML: Dan, can you put a value on the promotional spots run by NBC last night promoting Peacock and primetime shows – SF: Oh, good question. ML: – their newscasts I saw were promoted, the Olympics, and anything else that’s going to run – and Telemundo? You know, they’re giving up 7 million dollars every 30 seconds to run a promotional spot for which they receive no monetary value immediately, but is there a long term uptick for them? DC: It’s a great question, and that’s always the opportunity cost of promotional units is, the opportunity to advantage your own platform versus to realize revenue. I think historically – and it has probably only become even more the case in a streaming world with Peacock and Disney Plus and HBO Max – but many shows launched through the Super Bowl. And historically – you know, last night NBC let us see the Olympics – but for many decades, networks have taken their biggest bets on essentially the show that follows the Super Bowl. So it’s a delicate balance between what you sell versus what you use, but definitely something that creates value either way. MB: Dan Calpin who is with Hive Enterprise. Dan, you are just full of knowledge when it comes to advertising, and I appreciate you for just taking the time out and giving me a good education. We appreciate it. Thank you so much, Dan. DC: Thank you so much. Appreciate talking with you all and enjoyed the game last night and fun to get to extend it into Monday morning. MB: Thank you. This is the Bloomberg Business of Sports Podcast, catch us here each and every Monday, Wednesday, and Thursday, exploring the world of money and sports.
BACK TO ALL BLOGS Hive Completes SOC 2 Type 1 Audit HiveFebruary 7, 2022July 4, 2024 At Hive, we understand that our customers continually put their trust in us to provide the best quality of service possible. We take this trust seriously and we work hard to ensure that we’re able to provide the highest level of security we can. As a first step to showing our commitment to security, we’re proud to announce that Hive has successfully completed a SOC 2 Type 1 audit with the Trust Service Criteria of Security, Availability, and Confidentiality. SOC 2 is the most accepted information security audit for North America, and we believe that passing this audit reinforces our commitment to maintaining best-in-class internal controls for safeguarding our customers’ data.We recognize that data security is a critical concern for our customers. This is why we have ingrained security into all of our engineering processes at Hive. With a host of preventative, detective, and restorative measures, we believe we have enabled 360 degrees of security around our infrastructure and critical customer data. What is a SOC 2 Audit? The SOC 2 Audit is designed for organizations that provide services to other entities while interacting with their data. It provides a consistent set of criteria by which to measure the security, confidentiality, availability, processing integrity, and/or privacy practices of an organization. An independent third party CPA firm must conduct the audit, after which it issues an audit report with the findings. There are two types of SOC 2 audits conducted: Type 1 – Report on management’s description of a service organization’s system and the suitability of the design of controls. Type 2 – Report on management’s description of a service organization’s system and the suitability of the design and operating effectiveness of controls. The SOC 2 audit is conducted on an annual basis to measure continued success in the defined criteria. What’s Next? We believe that continuous innovation is key to providing the best service possible. As Hive grows in size and complexity, we recognize that it is critical for our security practices to grow as well. On top of continuously monitoring and adapting our security practices, we will move forward with a SOC 2 Type 2 in 2022, and have ISO 27001 on the compliance roadmap.For more information on our security practices and plans, please contact our security team at security@thehive.ai.
BACK TO ALL BLOGS How Native Brand Exposure on TV Illustrates 2021’s Pop Culture & Lifestyle Trends HiveJanuary 12, 2022September 12, 2024 In our increasingly data-driven world, “Year in Review” publications have captivated us as consumers with insightful (and sometimes embarrassing) individual summaries of the past year as defined by the songs we listened to, the workouts we completed, and the travel we embarked upon. This Year in Review analysis looks at the collective: how analyzing every second of television content in 2021 provides insight into key trends in pop culture.Hive powers Mensio, a media intelligence platform that provides always-on, AI-powered measurement of in-content exposure for 7,000+ brands across 24/7 programming on 100+ national TV networks and major regional sports networks. Mensio enables monitoring of brand exposure from sponsorship activations, product placement, and other in-content exposures, reporting occurrences, share of voice, and valuation.To focus on “earned” exposure, this analysis excludes brand exposure within sports programming and commercial breaks. Here are the trends we saw in 2021. 1. We continued to be reminded that we were still in a pandemic COVID propelled Purell into the public conversation in 2020, earning $1.3M in equivalent media value from product exposure on tables everywhere from news to reality TV. While the value of exposures dropped by a third in 2021, Purell remained a part of the conversation – including as a featured subject in multiple Saturday Night Live skits during the year. The almost $900K in equivalent media value Purell earned in 2021 was still almost 3X what the brand earned in 2019. Vaccine manufacturers such as Pfizer, Moderna, and Johnson & Johnson also earned significant in-content media exposure as vaccines were rolled out. Among the set, Pfizer earned the most value from in-content exposure with ~$3.2M in 2021 after earning ~$4.2M in 2020. Like Purell, Pfizer and other vaccine manufacturers became part of the zeitgeist with increasing integration into comedy programs like Saturday Night Live and Adam Ruins Everything. 2. You weren’t the only one on Zoom From branded video interviews on news programs to native integrations captured on reality TV, Zoom’s logo achieved ~8.5x as much TV presence in 2021 compared to 2019. Zoom’s exposure in 2021 dropped 13% from 2020, however, perhaps as an indicator of the slow return to in-person life. You also weren’t the only one who upgraded your video conferencing equipment. Audio manufacturer Shure was a beneficiary of this trend: though Shure saw a 2.6x increase in exposures from 2019 to 2020, their high-tech microphones really took off in 2021 with a 6.7x increase over 2019. 3. You also weren’t the only one on TikTok TikTok continued its explosive growth, achieving a ~270x increase in exposures on TV from 2019 to 2021. This appears to have come at the expense of other social media platforms, with TikTok posts increasingly supplanting posts from other sites. While the total estimated value of TikTok’s TV exposures in 2021 still greatly lags incumbent platforms (i.e., only 20% of the value of Facebook’s in-content brand exposure), all other major social platforms decreased in total exposures during those same 2 years. Both Facebook and Instagram decreased TV exposure by ~40% compared to 2019, suggesting that we are watching a social media revolution unfold. 4. You weren’t the only one with new at-home hobbies either Peloton was the biggest winner in the at-home workout category. While some of the ~54% year-over-year increase in onscreen exposure came from news coverage of the company’s treadmill recall and financial performance, exposure in reality shows increased by 90% in 2021 vs. 2020, illustrating the brand’s integration into everyday life. 2021 could also be characterized as the year of the “retail investor”. Storylines included the rise of ‘meme stock’ GameStop, which had one of the highest increases in estimated on-TV value across all brands, from $96K in 2020 to $3.1M in 2021 (~32x). Trading platform Robinhood benefited with a 11x increase in exposures, with most chatter surrounding its role in enabling GameStop and AMC trades. Interested in learning more about Mensio? Using AI powered by Hive, the Mensio product suite provides faster and more granular measurement of branded content and sponsorship intelligence across media platforms, in addition to cross-platform ad intelligence. Request Demo
BACK TO ALL BLOGS Why We Worked with Parler to Implement Effective Content Moderation HiveMay 17, 2021March 5, 2025 Earlier today, The Washington Post published a feature detailing Hive’s work with social network Parler, and the role our content moderation solutions have played in protecting their community from harmful content and, as a result, earning their app reinstatement in Apple’s App Store.We are proud of this very public endorsement on the quality of our content moderation solutions, but also know that with such a high-profile client use case there may be questions beyond what could be addressed in the article itself about why we decided to work with Parler and what role we play in their solution. For detailed answers to those questions, please see below. Why did Hive decide to work with Parler? We believe that every company should have access to best-in-class content moderation capabilities to create a safe environment for their users. While vendors earlier this year terminated their relationships with Parler after believing their services were enabling a toxic environment, we believe our work addresses the core challenge Parler faced and enables a safe community for Parler’s users to engage.As outlined in our recent Series D funding announcement, our founders’ precursor to Hive was a consumer app business that itself confronted the challenge of moderating content at scale as the platform quickly grew. The lack of available enterprise-grade, pre-trained AI models to support this content moderation use case (and others) eventually inspired an ambitious repositioning of the company around building a portfolio of cloud-based enterprise AI solutions.Our founders were not alone. Content moderation has since emerged as a key area of growth in Hive’s business, now powering automated content moderation solutions for more than 75 platforms globally, including prominent dating services, video chat applications, verification services, and more. A December 2020 WIRED article detailed the impact of our work with iconic random chat platform Chatroulette.When Parler approached us for help in implementing a content moderation solution for their community, we did not take the decision lightly. However, after discussion, we aligned on having built this product to provide democratized access to best-in-class content moderation technology. From our founders’ personal experience, we know it is not feasible for most companies to build effective moderation solutions internally, and we therefore believe we have a responsibility to help any and all companies keep their communities safe from harmful content. What is Hive’s role in content moderation relative to Parler (or Hive’s other moderation clients)? Hive provides automated content moderation across video, image, text, and audio, spanning more than 40 classes (i.e., granular definitions of potentially harmful content classifications such as male nudity, gun in hand, or illegal injectables).Our standard API provides a confidence score for every content submission against all our 40+ model classes. In the instance of Parler, model flagged instances of hate speech or incitement in text are additionally reviewed by members of Hive’s 2.5 million plus distributed workforce (additional details below).Our clients map our responses to their individual content policies – both in terms of what categories they look to identify, how sensitive content is treated (i.e., blocked or filtered), and the tradeoff between recall (i.e., the percentage of total instances identified by our model) and precision (i.e., the corresponding percentage of identifications where our model is accurate). Hive partners with clients during onboarding as well as on an ongoing basis to provide guidance on setting class-specific thresholds based on client objectives and the desired tradeoffs between recall and precision.It is the responsibility of companies like Apple to then determine whether the way our clients choose to implement our technology is sufficient to be distributed in their app stores, which in the case of Parler, Apple now has. What percentage of content is moderated, and how fast? 100% of posts on Parler are processed through Hive’s models at the point of upload, with latency of automated responses in under 1 second.Parler uses Hive’s visual moderation model to identify nudity, violence, and gore. Any harmful content identified is immediately placed behind a sensitive content filter at the point of upload (notifying users of sensitive content before they view).Parler also uses Hive’s text moderation model to identify hate speech and incitement. Any potentially harmful content is routed for manual review. Posts deemed safe by Hive’s models are immediately posted to the site, whereas flagged posts are not displayed until model results are validated by a consensus of human workers. It typically takes 1-3 minutes for a flagged post to be validated. Posts containing incitement are blocked from appearing on the platform; posts containing hate speech are placed behind a sensitive content filter. Human review is completed using thousands of workers within Hive’s distributed workforce of more than 2.5 million registered contributors who have opted into and are specifically trained on and qualified to complete the Parler jobs.In addition to the automated workflow, any user-reported content is automatically routed to Hive’s distributed workforce for additional review and Parler independently maintains a separate jury of internal moderators that handle appeals and other reviews.This process is illustrated in the graphic below. How effective is Hive’s moderation of content for Parler, and how does that compare to moderation solutions in place on other social networks? We have run ongoing tests since launch to evaluate the effectiveness of our models specific to Parler’s content. While we believe that these benchmarks demonstrate best-in-class moderation, there will always be some level of false negatives. However, the models continue to learn from their mistakes, which will further improve the accuracy over time. Within visual moderation, our tests suggest the incidence rate of adult nudity and sexual activity content not placed behind a sensitive content filter is less than 1 in 10,000 posts. In Facebook’s Q4 2020 Transparency Report (which, separately, we think is a great step forward for the industry and something all platforms should publish), it was reported that the prevalence of adult nudity and sexual activity content on Facebook was ~3 to 4 views per 10,000 views. These numbers can be seen as generally comparable with the assumption that views of posts with sensitive content roughly average the same as all other posts. Within text moderation, our tests suggest the incidence rate of hate speech (defined as text hateful towards another person or group based on protected attributes, such as religion, nationality, race, sexual orientation, gender, etc.) not placed behind a sensitive content filter was roughly 2 of 10,000 posts. In Q4 2020, Facebook reported the prevalence of hate speech was 7 to 8 views per 10,000 views on their platform. Our incidence rate of incitement (defined as text that incites or promotes acts of violence) not removed from the platform was roughly 1 in 10,000 posts. This category is not reported by Facebook for the purposes of benchmarking. Does Hive’s solution prevent the spread of misinformation? Hive’s scope of support to Parler does not currently support the identification of misinformation or manipulated media (i.e., deepfakes). We hope the details above are helpful in further increasing understanding of how we work with social networking sites such as Parler and the role we play in keeping their environment (and others) safe from harmful content. Learn more at https://thehive.ai/ and follow us on Linkedin Press with additional questions? Please contact press@thehive.ai to request an interview or additional statements. Note: All data specific to Parler above was shared with explicit permission from Parler.
BACK TO ALL BLOGS Series D Funding: Hive Announces $85M in New Capital and $2B Valuation HiveApril 21, 2021March 4, 2025 Today, I’m excited to announce that Hive has raised $85M in new capital, inclusive of a $50M Series D financing round at a $2B valuation and a previously unannounced $35M Series C financing round which closed last year at a $1B valuation. Our Series D round was led by Glynn Capital, with participation from our other major existing investors, including General Catalyst, Tomales Bay Capital, Bain & Company, and Jericho Capital. This funding is an important milestone for the company, accelerating our ambition to be the leading provider of enterprise AI solutions to power the next wave of intelligent automation. Disruption triggered by the COVID-19 pandemic has pushed companies across industries to rethink how work is done, and this has resulted in an increased ambition and accelerated roadmap for the use of AI in enterprise automation. This capital infusion gives us the ability to meet the near-term market opportunity without constraints. The use of AI in enterprise automation is still at its infancy. In recent years, companies across industries have embraced robotic process automation (RPA) to realize efficiencies from automating repetitive and lower-value tasks. A November 2020 Deloitte survey reported current use of RPA by 78% of companies and expected use of the technology by 94% of companies within the next three years. While RPA has delivered significant value across industries (and to the providers enabling these solutions), there is a ceiling on the types of activities that can be addressed with that technology‒generally limited to highly transactional activities such as application log in, data extraction, and form filling. We aim to unlock the full potential of enterprise automation, spanning a set of more “intelligent” manual processes and new processes not feasible to scale with manual labor. Deep learning, the discipline of AI that we focus on at Hive, enables human-like interpretation of video, image, text, and audio‒newly enabling a next wave of intelligent automation. The market is ready. That same Deloitte study found that only 34% of companies report use of AI for automation today, but an incremental 52% of companies now plan to implement it over the next three years. While the potential of AI models is endless, making them effective in a production setting is a separate matter altogether. We experienced this ourselves viscerally 4 years ago‒at the time as consumer app developers struggling to find out-of-the-box AI models accurate enough to handle processes such as content moderation. Forced to develop these models ourselves, we realized that other companies likely faced a similar dearth of high quality, publicly accessible models for common problems. From this challenge, the vision for Hive was born: performant, cloud-based and pre-trained AI models that are accessible via a simple API. Over the past three and a half years, we have earned the trust of now more than 100 enterprise customers through an obsessive focus on accuracy‒rooted in pre-trained models that consistently and significantly outperform comparable solutions. The foundation of our model accuracy is predicated upon a belief that vast amounts of high quality training data is the most important factor of a performant model. We put such importance on this that we took the unusual step of building out our own distributed human workforce for the sole purpose of generating annotations for machine learning datasets at scale. Our Hive workforce has grown to be one of the largest in the world, with over 2.5M contributors and more than 4B human judgments generated. What began as a purely internal tool quickly became a valuable product in its own right, and today many of the world’s largest and most innovative companies rely on our platform to source and label raw data for developing their own AI models. Being our own largest data annotation customer, we have the luxury of building AI models trained on unprecedented amounts of data. For instance, our visual content moderation model alone is trained on more than 600M judgments across 30+ classes; this is several orders of magnitude larger than any open source data set available. The resulting best-in-class model accuracy across our portfolio of solutions has driven significant growth in all our core company metrics. Over the past year, we’ve increased our customer base and revenue by more than 300% and are now processing billions of API calls a month. Since Q1 2018, we’ve increased API calls by nearly 60x: What Makes Us Different Our differentiation is in our industry-leading accuracy, enabled by the combination of our best-in-class ML technology with training data produced by our distributed labeling workforce of 2M+ contributors Specifically, content moderation has been a key driver of our growth in the past year. This suite of models is now trusted by more than 75 customers globally, including content platforms such as Reddit, Yubo, Chatroulette, Omegle, Tango, and more, as well as leading dating sites, gaming platforms, verification services, and more. Our models provide real-time inference of video, image, text, and audio content, enabling clients to automatically identify and remove prohibited content across more than 40 classes, including sexual content, violence, gore, drugs, and hate speech. Companies that have integrated with Hive’s content moderation APIs have consistently increased the amount of content proactively reviewed and significantly reduced the level of human exposure to sensitive content, across both moderators and users. Our portfolio of AI solutions for the media & entertainment industry has been another key driver of our recent growth, earning the trust of major media companies including NBCUniversal, large media agencies including Interpublic Group, and established brands including Walmart and Anheuser-Busch InBev. Our suite of AI models for the media space are collectively trained on more than 1B pieces of hand-labeled data and bring transformative new capabilities to areas such as contextual advertising and brand safety, advertising intelligence, measurement of sponsorship and branded content, and more. Finally, we’re fortunate to have established a diverse set of marquee partnerships to accelerate our go-to-market on a global scale. Over the past year, we expanded our partnership with Bain & Company, which was also an investor in our Series C and Series D financing, to support a broader set of use cases across the firm’s practice areas. We partnered with Cognizant, one of the world’s leading professional services companies, to expand Cognizant’s use of automation across a diverse set of use cases across industries. And earlier this year, we announced a partnership with Comscore, a leading media measurement and analytics company, that will integrate Hive’s technology into Comscore’s product portfolio, including the launch of a reinvented branded content measurement solution enhanced with next-day, AI-powered data from Hive. These partners have complemented our internal sales team in driving revenue for our business, but more importantly, they have also provided valuable guidance that has influenced our product roadmap and priorities. We look forward to announcing several other partnerships in the coming months. Despite everything we’ve built over the past few years and all of the early commercial successes, we’re still scratching the surface of what’s possible. Like other major technology shifts in the past, AI will continue to permeate virtually all aspects of our lives, and all companies will have to adopt an AI strategy sooner than they would expect. While this additional capital gives us the resources to accelerate our growth to full potential, we will ultimately measure our success not by our funding figures‒or even our revenue‒but rather by the transformative impact that our clients’ products will have on the world. If you’d like to join us on this mission, please check out our open roles here: thehive.ai/careers Learn more about Hive Try our models Key product pages: Content ModerationContextual Advertising & Brand SafetyLogo & Brand ExposureData Sourcing & Annotation