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.
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.
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
Hive is excited to participate in Advertising Week 2020, kicking off Tuesday, September 29th. Watch our promotional video to learn more about how Hive is working with media owners, brands, agencies, and others in the media ecosystem.
Social media platforms increasingly play a pivotal role in both spreading and combating hate speech and discrimination today. Now integrated into Hive’s content moderation suite, Hive’s hate model enables more proactive and comprehensive visual and textual moderation of hate speech online.
Year over year, our content moderation suite has emerged as the preeminent AI-powered solution to both help platforms keep their environments protected from harmful content, and to dramatically reduce the exposure of human moderators to sensitive content. Hive’s content moderation models have consistently and significantly outperformed comparable models, and we are proud to currently work with more than 30 of the world’s largest and fastest-growing social networks and digital video platforms.
Today we are excited to officially integrate our hate model into our content moderation product suite, helping our current and future clients combat racism and hate speech online. We believe that blending our best-in-class models with the significant scale of our clients’ platforms can result in real step-change impact.
Detecting hate speech is a unique challenge that is dynamic and evolving rapidly. Context and subtle nuances vary widely across cultures, languages, and regions. Additionally, hate speech itself isn’t always explicit. Models must be able to recognize subtleties quickly and proactively. Hive is committed to taking on that challenge and, over the past months, we have partnered with several of our clients to ready our hate model for today’s launch.
How We Help
Hate speech can occur both visually and textually with a large percentage occurring in photos and videos. Powered by our distributed global workforce of more than 2 million registered contributors, Hive’s hate model is trained on more than 25 million human judgments and supports both visual classification models and text moderation models.
Our visual classification models classify entire images into different categories by assigning a confidence score for each class. These models can be multi-headed, where each group of mutually exclusive model classes belongs to a single model head. Within our hate model, some examples of heads include the Nazi and KKK symbols, and other terrorist or white supremacist propaganda. Results from our model are actioned according to platform rules. Many posts are automatically actioned as safe or restricted; others are routed for manual review of edge cases where a symbol may be present but not in a prohibited use. Our visual hate models will typically achieve >98% recall and a <0.1% false positive rate. View our full documentation here.
Our text content moderation model is a multi-head classifier that will now include hate speech. This model automatically detects “hateful language” – defined, with input from our clients, as any language, expression, writing, or speech that expresses / incites violence against, attacks, degrades, or insults a particular group or an individual in a particular group. These specific groups are based on protected attributes such as race, ethnicity, national origin, gender, sex, sexual orientation, disability, and religion. Hateful language includes but is not limited to hate speech, hateful ideology, racial / ethnic slurs, and racism. View our full documentation here.
We are also breaking ground on solving the particularly challenging problem of multimodal relationships between the visual and textual content, and expect to be adding multi-modal capabilities over the next weeks. Multimodal learning allows our models to understand the relationship between both text and visual content in the same setting. This type of learning is important to better understand the meaning of language and the context in which it is used. Accurate multimodal systems can avoid flagging cases where the visual content on its own may be considered hateful, but the presence of counterspeech text — where individuals speak out against the hateful content — negates the hateful signal in the visual content. Similarly, multimodal systems can help flag cases where the visual and textual content independently are not considered to be hateful, but in the context of one another are in fact hateful, such as hateful memes. Over time, we expect this capability to further reduce the need for human reviews of edge cases.
What’s Next?
Today’s release is a milestone we are proud of, but merely the first step in a multi-year commitment to helping platforms filter hate speech from their environments. We will continue to expand and enhance model classification with further input from additional moderation clients and industry groups.
TV advertising has been arguably more dynamic than ever during the COVID-19 pandemic. How will the lingering uncertainty around the 2020-2021 school year impact how marketers approach Back-to-School campaigns? Research using Mensio, a media analytics platform developed by Hive and Bain Media Lab, highlights how advertisers approached Back-to-School campaigns in 2019 and what to expect in 2020.
Trends to watch for Back-to-School 2020
Back to Advertising? Many specialty retailers typically active with Back-to-School campaigns have stepped down TV ad spend while stores have been closed; Back-to-School campaigns may bring those brands back to TV
New to School? Potential for “classrooms at home” may drive new advertisers and messages focused on home office furniture and technology
Geographical Flexibility Brands may increase the use of digital platforms and /or local advertising to better align messages with geographic variance in timing and conditions for the re-opening of schools
This year’s NFL Draft stole headlines with record ratings. Viewers saw not only a new format with cameras in homes, but also significant changes in the brands who advertised.
Hive
At a Glance:
The 2020 NFL Draft shattered ratings records and was an unqualified success for viewers, brands, and the airing networks – all starved for live sports content
Amidst an altered TV advertising landscape, viewers were exposed to a different mix of brands compared to the 2019 event – across the three airing networks, only 61 of 150 advertisers also had spots in last year’s event
Ads from travel & leisure, automotive, media & entertainment, and retail advertisers decreased most significantly year-over-year; ads from quick service restaurants, insurers, tech companies, and streaming video platforms increased the most
Coronavirus-related messages made up more than one-third of all ad spots across networks, almost twice as frequent as the 19 percent of all national TV airings focused on similar messages
AI-powered measurement of brand exposure in content highlighted the long tail of college football sponsorship values. ESPN’s presenting sponsor, Lowe’s, achieved the most equivalent media value from logo exposure within the programming; however, Nike was next most with swooshes visible in highlights, and four other on-field apparel brands ranked in the top 15 of brands with in-content exposure
With reported year-over-year viewership gains of roughly forty percent, the 2020 NFL Draft was an unqualified success for viewers, brands, and the airing networks – all starved for live sports content as the COVID-19 disruption persists.
For those who watched in 2019, this year’s event looked different. Notably, more than 600 camera feeds enabled a “virtual draft” format featuring teams, players, and commentators connecting from their homes. Beyond the altered format, viewers were also exposed to a much different set of brands.
Of the 150 advertisers who ran spots across ESPN, ABC, and NFL Network during this year’s event, only 61 also advertised in the 2019 NFL Draft (see Figure 1). This overlapping group was led by brands including Verizon, Lowe’s, Pizza Hut, Taco Bell, and State Farm.
Several major automakers including GMC, Nissan, and Honda were among the 96 brands sitting out this year’s draft after being active in the 2019 event. Filling the gaps were 89 brands not active in last year’s event, with IBM, BMW, John Deere, and DoorDash among the new-to-Draft brands with heavy presence.
The carousel of brands impacted category-level share of voice as well. Last year, ads from travel & leisure, automotive, media & entertainment, and retail advertisers made up 43 percent of airings across ESPN, ABC, and NFL Network; this year, that number decreased to 27 percent (see Figure 2). Growing share of voice year-over-year were quick service restaurants, insurers, tech companies, and streaming video platforms.
Over the past month, Hive and Bain Media Lab have monitored the continued increase in TV ad campaigns related to COVID-19, tracking the flighting and messaging of the more than 160 brands who have released bespoke campaigns. Across the TV universe, these campaigns made up 19 percent of all airings during the past week. This concentration was significantly higher during the NFL Draft, with 35 percent of all spots featuring coronavirus-related campaigns (see Figure 3). This peaked at 41 percent of national TV ad airings on the NFL Network feeds, 34 percent on ABC, and 29 percent on ESPN.
A host of league and broadcast sponsors achieved additional exposure in-content with logo presence in the telecast. In total across the three days, 33 brands received 15 or more seconds of in-content logo exposure, excluding league, team, and network logos (see Figure 4). This analysis was completed using Hive’s logo model, using a computer vision model trained with more than two million manhours of human-labeled training data and able to automatically detect and value the presence of logos from more than 5,000 brands.
Visible brands included Lowe’s as the presenting sponsor and other broadcast sponsors scattered into the broadcasts (e.g. “Autotrader Trade Alerts”). League sponsors including Microsoft and Gatorade had visible product placement in the telecast, as did Bose which monopolized the headphones and earphones used by players and teams during the event (albeit without camera-visible branding).
Interestingly, many of the top brands visible within the 2020 NFL Draft programming earned their exposure primarily through highlight footage from past events. This included Nike, which had the second-most total exposure, as well as four other on-field apparel brands which ranked among the top 15. College bowl sponsors including Chick-Fil-A and Allstate also made the list, making the case for always-on measurement of sponsorship exposures. While the NFL Draft is one example of this, separate research from Hive has found that shoulder programming and highlights consistently amplify valuations for sports sponsorships – sometimes by as much as twice the value of whistle-to-whistle measurement.
With the intrigue of draft selections passed, the key question in the sports world now returns to when and how games will resume. If this weekend was any indication, changes to the format shouldn’t have any negative impact on the demand from viewers or brands.
Note: Published Bain Media Lab research relies solely on third-party data sources and is independent of any data or input from clients of Bain & Company
123 brands and counting have now launched national TV ad campaigns messaging around COVID-19; 20 brands released their first coronavirus-related campaigns in the past week
In aggregate, coronavirus-related ads have stabilized at around 15 percent of total national TV ad airings, now led by airings from restaurants and retailers
COVID-19 campaigns make up more than half of all national TV ad airings within the restaurant, automotive, and telecom categories; conversely, coronavirus-related airings make up less than five percent of CPG category airings
Coronavirus-related spots have exceeded 80 percent of total airings for more than half of the brands who have released COVID-19 campaigns to date
COVID-19 also seemed to have an impact on Easter messaging; four of the eight retail brands who had Easter-focused campaigns in 2019 were not present on TV in 2020, and two others reduced airings by more than 80 percent year-over-year
Bain & Company and Hive continue to offer free trial access to the Mensio platform for any national TV advertiser, full-service media agency, or U.S. TV ad sales team to enable competitive intelligence and monitoring of trends in creative messaging during the period of disruption; interested parties can request access at: https://mensio.com/covid-19
The number of brands releasing TV ad campaigns specific to the coronavirus has continued to grow, starting with Verizon on Sunday, March 15, and reaching 123 brands and counting four weeks later. COVID-19 campaigns composed just 2.5 percent of all national TV ad airings on Sunday, March 22; this increased to 13 percent by Sunday, March 29, and just above 15 percent by Sunday, April 5. For now, the mix has stabilized around 15 percent of all national TV ad airings even as 21 additional brands released new campaigns in the past week (see Figure 1).
Changing Mix
While automakers and telecom providers grabbed two-thirds of all airings in the week ending March 22, the first week of COVID-19 campaigns, they represented just over 20 percent of airings in the week ending April 12 – dwarfed by a surge in airings from restaurants and retailers that now make up more than half of the week’s coronavirus-related ad airings (see Figure 2).
While a diverse set of brands have released COVID-19 campaigns, industry verticals are not uniform in if and how brands are choosing to message about COVID-19 on television.COVID-19 campaigns now make up more than half of all national TV ad airings within the restaurant, automotive, and telecom categories; conversely, coronavirus-related airings still make up less than five percent of total CPG category airings (see Figure 3).
While the difference across categories is significant, the brands that have chosen to release COVID-19 campaigns tend to make them the majority of their messaging. Coronavirus-related spots have exceeded 80 percent of total airings for more than half of the brands who have released COVID-19 campaigns to date (see Figure 4).
Evolving Messages
What brands are saying continues to vary across categories and, increasingly, within them. More than 88 percent of restaurant airings message product and offering changes, such as “contactless” delivery and pickup options. Conversely, more than 83 percent of airings from financial services & insurance companies communicate general support and empathy. As more brands join the conversation, messages within some categories are starting to become more diverse. Airings from retailers, primarily driven by “big box” brands, are roughly split between messages of general support, communication of product and offering changes, and thematic marketing (i.e. messaging existing offerings in the context of the COVID-19).
Impact on Easter Advertising
Stay-at-home orders impacted how Americans celebrated Easter this year, and COVID-19 also appeared to impact how much TV advertising is focused on Easter-related messaging. In 2019, 16 brands released Easter-themed campaigns – led by eight retailers and six chocolate manufacturers.
The number of brands with Easter ad campaigns on TV dropped to 11 brands this year. Four of the eight retailers with Easter campaigns on TV in 2019 were not at all active with TV advertising in the two weeks leading up to Easter this past Sunday, and two of the remaining four decreased national ad airings by more than 80 percent compared to 2019. In aggregate, this resulted in a year-over-year decrease of almost 50 percent in total Easter campaign airings by retailers.
Conversely, the environment did not reduce campaigns from chocolate makers. All six brands were active across years, with airings roughly equal year-over-year Easter-themed airings (See Figure 5).
Free Mensio Access for Any National TV Brand, Media Agency, or U.S. TV Ad Sales Team During COVID-19 Crisis
Earlier this month, as an investment in industry relationships during the disruption, Bain & Company and Hive announced that a no-cost trial version of Mensio will be made available upon request to any national TV brand, full-service media agency, or U.S. TV ad sales team. The trial version of Mensio will include:
Access to Mensio’s commercial library to monitor and view new creatives from brands across industries
Access to competitive intelligence to measure changes in airings, estimated spend, flighting, and mix across brands
The ability to filter all data by creative groups, enabling more granular analysis of trends in messaging and creative characteristics
Note: Ongoing analysis and perspectives will be shared throughout the Bain & Company and Hive LinkedIn pages. Please follow for notification of additional releases:
Note: Published Bain Media Lab research relies solely on third-party data sources and is independent of any data or input from clients of Bain & Company
The scope of disruption from COVID-19 has included brands and agencies. Here’s how different brands and industries have adapted their TV advertising during the crisis.
Hive
At a Glance:
Through the weekend, 62 brands and counting had released national TV ad campaigns related to COVID-19, led by restaurants and automakers
The number of brands airing coronavirus-related campaigns almost tripled last week compared to the 22 brands who had launched campaigns in the prior week
52 percent of campaigns and 64 percent of airings were from brands messaging product and offering changes. These included “contactless” pickup and delivery at restaurants and deferred payment programs on autos
General messages of empathy and support were next most common, reflecting 26 percent of campaigns and 20 percent of airings
While some brands have stopped or scaled down TV ads, others are changing mix. In aggregate, restaurants and retailers dramatically shifted their mix of airings (1.9X) – across new and preexisting creatives – to amplify promotion of delivery and takeout options
to enable competitive intelligence and monitoring of trends in creative messaging during the period of disruption
62 brands release coronavirus-related TV ad campaigns over a two-week period
While the first U.S. coronavirus case was reported on January 21, the impact on most Americans wasn’t material until mid-March when restrictions on travel and public gatherings and an increasing number of stay-at-home orders set in. Despite many working from home since, brands and agencies have been quick to adapt their messaging to acknowledge the coronavirus outbreak.
National public service announcements from the Center for Disease Control began on March 13 and have since aired almost 1,500 times across more than 40 networks.
Verizon was the first brand to acknowledge the environment in its TV commercials, launching a campaign during the Democratic Debate on March 15 focusing on network stability so that “during times like this, Americans can stay connected to work, school and, most importantly, to each other.” Versions of the creative have since aired more than 2,500 times across 54 networks, in addition to airings from Verizon’s other coronavirus-related campaigns since launched.
During the week of March 16, 22 brands across industries aired national TV ad spots explicitly or implicitly addressing the crisis. During the following week, that number increased to 62 brands.
There has been significant variability across categories in terms of how many brands have released messages, and how quickly those campaigns were released (see Figure 1). Both weeks, restaurants and automakers had the highest count of brands with active coronavirus-related TV ad campaigns. Across categories, there were at least twice as many brands active during the week of March 23 compared to the week of March 16.
Brand messages focus on product and offering changes as well as general support
Initial coronavirus-related creatives fell into four broad buckets of messaging: 1) product and offering changes, 2) general support, 3) thematic marketing, and 4) virus-related information and calls-to-action.
Through March 29, 52 percent of campaigns and 64 percent of airings addressed product and offering changes. 15 restaurant brands composed the plurality of this group. Several quick service restaurants introduced “contactless” drive-thru, pickup, and delivery experiences; casual dining brands such as Chili’s and Denny’s announced waived delivery fees. Automotive brands were the next largest cohort in messaging product or offering changes, with nine brands releasing campaigns. This list included General Motors’ brands, which announced free OnStar Crisis Assist services and in-vehicle Wi-Fi data for existing Chevrolet, Buick, Cadillac, and GMC owners as well as zero percent financing with deferred payments and at-home delivery options for new buyers.
26 percent of campaigns and 20 percent of airings conveyed a diverse set of messages broadly aiming to show empathy and convey support. Quilted Northern and Angel Soft affirmed their commitment to restocking shelves with toilet paper. Anheuser-Busch announced that Budweiser would redirect its sports investments toward hosting American Red Cross blood drives at stadiums across the country. Walmart thanked its employees, many still working in-store to serve customers’ needs through the crisis.
Eight brands launched campaigns featuring existing products and services in the context of the crisis. Food delivery service DoorDash was an example, messaging that its network of restaurants was open for delivery through the crisis.
Six brands launched campaigns with informative messages, in addition to a series of public services announcements from parties including the CDC and American Red Cross. Among the brands, Clorox shared a brand-relevant informational message providing instruction on how best to kill germs in the home.
While consumer surveys to date have generally found positive receptivity to brands acknowledging COVID-19 in their marketing messages, advertisers will face a challenge to be differentiated over time. Even among the initial set of brands airing coronavirus-related creatives, the concentration of message themes has been relatively consistent within categories. 98% of restaurant airings have highlighted product or offering changes, as have 89% of automotive ad airings (see Figure 2).
“Even if stores are closed or products are sold out, TV will remain a valuable brand-building channel for marketers. However, as the pandemic continues, brands will need to continue to evolve their messages,” said Laura Beaudin, a partner at Bain & Company, who leads the firm’s Marketing Excellence practice. “Consumers won’t want to see a full commercial break with each advertisement telling them how to wash their hands.”
Restaurants shift mix to delivery- and pickup-focused creatives
Restaurants have been among the hardest hit industries during the COVID-19 outbreak, with many closing dining rooms at the request of local officials. While this has resulted in a growing number of independent restaurants closing their doors during the disruption, it has pushed quick service restaurants and casual dining chains to change their messaging.
While several restaurants have released new campaigns specific to the outbreak, including those promoting “contactless” transactions, the broader category has shifted its mix of national TV ads towards promoting off-premise dining using both new and preexisting creatives. During the four weeks ending March 15, 24 percent of restaurant airings highlighted pickup or delivery options, either as the focal point of the message or with an end card (including those promoting partnerships with delivery aggregators such as DoorDash and GrubHub). That mix of restaurant airings promoting delivery and pickup options increased to 28 percent during the week of March 16 and surged to 52 percent during the week of March 23.
Free Mensio access for any national TV brand, media agency, or TV ad sales team during COVID-19 crisis
Bain & Company and Hive also announced today that a version of Mensio will be made available upon request to any national TV brand, media agency, or TV ad sales team, providing users platform access through at least April 2020 including:
Access to Mensio’s commercial library to monitor and view new creatives from brands across industries
Access to competitive intelligence to measure changes in airings, estimated spend, flighting, and mix across brands
The ability to filter all data by creative groups, enabling more granular analysis of trends in messaging and creative characteristics
“Brands and agencies face uncertainty over if and how to maintain TV advertising investments during the COVID-19 crisis, what to message, and how competitive brands are responding,” said Dan Calpin, president of Hive Media and a senior advisor to Bain & Company. “The playbook on how to do this right is still being written, but it’s safe to say that no brand wants to be remembered for saying the wrong thing or nothing at all.”
Calpin added, “While the need for real-time competitive intelligence exists now more than ever, we know many companies face contract freezes preventing access to new tools to help understand how the landscape is changing. We view this offer as an opportunity to invest in the industry through the disruption.”
Note: Ongoing analysis and perspectives will be shared throughout the Bain & Company and Hive LinkedIn pages. Please follow for notification of additional releases:
Access to Mensio’s commercial library to monitor and view new creatives from brands across industries
Access to competitive intelligence to measure changes in airings, estimated spend, flighting, and mix across brands
The ability to filter all data by creative groups, enabling more granular analysis of trends in messaging and creative characteristics
Note: Published Bain Media Lab research relies solely on third-party data sources and is independent of any data or input from clients of Bain & Company
Social platforms face significant PR and revenue risks during the coronavirus crisis, challenged to maintain safe environments in the face of constrained human content moderation and insufficient in-house AI; Hive is using AI and its distributed workforce of 2 million contributors to help
Hive
SAN FRANCISCO, CA (March 23, 2020) – The extraordinary measures taken worldwide to limit the spread of the coronavirus disease have disrupted the global economy, as businesses across industries scramble to adapt to a reality few were prepared for. In many cases, companies have stalled operations – with notable examples including airlines, movie theaters, theme parks, and restaurants among others.
The disruption facing consumer technology companies like Google, Facebook, Twitter, and others is different. Engagement on social media platforms is unaffected, if not boosted, by the outbreak. However, underneath user trends are significant public relations and revenue risks if content moderation cannot keep up with the volume of user-generated content uploads.
Hive, a San Francisco-based AI company, has emerged as a leader in helping platforms navigate the disruption through a combination of data labeling services at scale and production-ready automated content moderation models.
Hive operates the world’s largest distributed workforce of humans labeling data, now more than 2 million contributors from more than 100 countries, and has been able to step in to support emergent content moderation data labeling needs as contract workforces of business process outsourcers (BPOs) have been forced to go on hiatus given their inability to work from home. Further, Hive’s suite of automated content moderation models have consistently and significantly outperformed capable models from top public clouds, and are being used by more than 15 leading platforms to reduce the volume of content required for human review.
Context for the Disruption
It is no secret that major social platforms employ tens of thousands of human content moderators to police uploaded content. These massive investments are made to maintain a brand safe environment and protect billions of dollars of ad revenue from marketers who are fast to act when things go wrong.
Most of this moderation is done by contract workers, often secured through outsourced labor from firms like Cognizant and Accenture. Work from home mandates spurred by COVID-19 have disrupted this model, as most of the moderators are not allowed to work from home. Platforms have suggested that they will use automated tools to help fill the gap during the disruption, but they have also acknowledged that this is likely to reduce effectiveness and to result in slower response times than normal.
How Hive is Helping
Hive has emerged in a unique position to meet emergent needs from social media platforms.
As BPOs have been forced to stand down onsite content moderation services, significant demand for data labeling has arisen. Hive has been able to meet these needs on short notice, mobilizing the world’s largest distributed workforce of humans labeling data, now more than 2 million contributors sourced from more than 100 countries. Hive’s workforce is paid to complete data labeling tasks through a consensus-driven workflow that yields high quality ground truth data.
“As more people worldwide stay close to home during the crisis and face unemployment or furloughs, our global workforce has seen significant daily growth and unprecedented capacity,” says Kevin Guo, Co-Founder and CEO of Hive.
Among data labeling service providers, Hive brings differentiated expertise to content moderation use cases. To date, Hive’s workforce has labeled more than 80 million human annotations for “not safe for work” (NSFW) content and more than 40 million human annotations for violent content (e.g. guns, knives, blood). Those preexisting job designs and workforce familiarity has enabled negligible job setup for new clients signed already this week.
Platforms are also relying on Hive to reduce the volume of content required for human review through use of Hive’s automated content moderation product suite. Hive’s models – which span visual, audio, and text solutions – have consistently and significantly outperformed comparable models from top public clouds, and are currently helping to power content moderation solutions for more than fifteen of the top social platforms.
Guo adds, “We have ample capacity for labeling and model deployment and are prepared to support the industry in helping to keep digital environments safe for consumers and brands as we all navigate the disruption caused by COVID-19.”
For press inquiries, contact Kevin Guo, Co-Founder and CEO, at kevin.guo@thehive.ai.
