For so long, Facebook has been the classroom bully in social media, with Snapchat taking it on the chin when Facebook copied Snapchat’s Stories format on FB, Instagram and WhatsApp. But now, the little tyke is exacting revenge as Facebook deals with blow after blow in the public arena: ongoing Russian meddling on the platform, incendiary posts inspiring real-life violence in Myanmar and Sri Lanka, and a stock market plunge that encapsulates its challenges fighting misinformation. Meanwhile, Snap has been quietly rolling out new deals with publishers and making itself out to be a much friendlier space to do business.
While it’s hard to compete with Facebook’s 1.47 billion daily active users, the story of Snapchat as the underdog fighting back is one to watch — especially as publishers tire of Facebook’s litany of problems.
‘Brand Safety and Control’
While Facebook consistently dominates tech news coverage, Snapchat also turned heads recently when it launched a private marketplace for advertisers akin to its own premium programmatic advertising marketplace. Now, advertisers can book space on specific shows and channels from a variety of publishing partners, including BuzzFeed, ESPN, and NBC Universal. Previously, brands could buy Snapchat ad inventory, but not target their advertising to specific publishers.
The beauty of this? Publishers can set their own ad rates, target only certain segments of a show’s audience, and advertisers can find more brand safety on Snapchat than they currently do with Facebook and Google’s YouTube. This is of course a boon for Snapchat too, as AdAge’s Garrett Sloane put it:
“Advertisers have been concerned about the type of content that appears on both YouTube and Facebook. Snapchat is trying to take advantage of the industry’s unease by offering a higher level of brand safety and control: Discover already operates as a gated community for professional publishers only, and the private marketplace now lets advertisers expressly select the shows they want while still using ad tech.”
On top of this, Snapchat is planning to sell six-second, unskippable ads in the private marketplace — meaning the chances of sustaining audience attention is even higher.
Broadening Discover’s Horizon
Snap also recently announced a new Discover partnership with an LGBT publisher — its first one — the U.K.-based website PinkNews. According to PinkNews CEO and editor-in-chief Benjamin Cohen, part of the incentive is that Discover is still a curated platform, meaning that accessing the humans behind the automation is still possible. Snapchat was also enticing in part because Facebook traffic for PinkNews— as is the case with many publishers — has gone down, Cohen said, and so he was looking to broaden audience traffic elsewhere.
The idea of working with a social platform like Snapchat that is actually willing to pay publishers became even more attractive for PinkNews. The partnership is also, undeniably, a win for Snapchat. It gains an outlet that will help the platform attract a young audience willing to push the boundaries of sexuality.
Indeed, it’s obvious that Snapchat is on the hunt to broaden its 191 million daily active users. In addition to working with traditional publishers, Snapchat has made a bigger effort this year to partner with digital publishers and social media stars that appeal to younger audiences. That includes Daquan Gesese, a hip-hop and pop culture personality with a huge presence on Instagram, and Fanbytes, an 18-month-old digital media company that runs four popular accounts on Snapchat, and operates a network of mostly 15- and 16-year-old creators who run their own accounts and publishing brands on Snapchat.
In May, Daquan launched his own Discover channel, and Fanbytes and Snapchat are currently trying to figure out whether “official” versions of its channels could be tailor-made for Discover.
More Flexiblity
But here’s what’s ironic about the Snapchat comeback: It wasn’t that long ago that Snapchat was ridiculed for a redesign that paired friends and family in one stream, and publishers and advertisers in another. Audiences complained, publishers worried.
“Content producers from eight publishers I spoke to said that the redesign had made their metrics go haywire,” Vanity Fair’s Maya Kosoff wrote. So it seems pretty natural that some publishers don’t necessarily see Snapchat as a particularly good long-term strategy if they can monetize better elsewhere, as one publisher anonymously confessed to Digiday last month.
However, it’s also understandable — decent, really — that Snapchat is letting publishers introduce non-exclusive shows to Snapchat Discover. Syndication is not particularly sexy, but even if shows have already aired on YouTube or Facebook Watch, this is a chance for Snapchat to build a Discover audience — and it’s a chance for publishers to ignite new revenue streams for its most popular intellectual property without having to create something original for each platform.
While publishers aren’t going to give up on a massive platform like Facebook anytime soon, Snapchat is getting back in the game on two counts. First, it’s actually the steady performer as Facebook struggles. And second, it is finally serving publishers in more ways while opening itself up to newer creatives. As with all platforms, there’s only so much trust publishers can give third parties who change their practices and rules on a whim, but it’s a good thing that Snap is trending up at just the right time – finally getting off the mat to give Facebook a few good licks.
Every day we’re reminded about the limited resources facing our industry, from the time people have to produce stories to the lack of insights we have about decisions made at the big platforms. There’s an irony then that it feels like there’s more data available to us than ever before. Yet many people still aren’t sure how to make the most of it.
Trying to improve business models, audiences, or content simply by adding more data doesn’t guarantee any success. Now, more than ever, the answer is finding the most relevant data—and making sure we’re uncovering all the available opportunities the data we have can provide.
Historically, some of this data has been hard to get to. The major technology platforms see it as theirs to wield. So, without major undertaking, it can be hard to piece the different types of data that audiences coming from Facebook, Google, your own editorial efforts, and untrackable sources actually show.
The Parse.ly data team, using Currents, looked at a recent major news story, immigration, as an example, to uncover opportunities for media companies that might have been missed in other data sources.
Finding the under-covered angle of the story
When Trump’s “zero tolerance” immigration policy separated children from parents, #KeepFamiliesTogether picked up steam on social media. But how did that translate to attention for the articles publishers wrote, and what did people want to know more about?
Over the course of one week, June 18 – June 25, there were 590 articles about immigration getting attention in our network. And that attention was vast: 16 million views.
So many articles means the topic was well covered, right? Not necessarily. Take the topic of “asylum seekers” for example.
Only 20% of these stories were related to asylum seekers. However, they received over 30% of the attention. High traffic per story suggests this angle was potentially under-covered and under-promoted.
Understand the differences between referral types
So where exactly were people finding stories about immigration? The biggest source of traffic was social media, which drove one-third of traffic to immigration stories. Given how much the media industry talks about Facebook, this may not seem surprising. But this is actually about double the typical traffic the network sends to any given story. It also bucks the trend of Google as the dominant source of traffic.
Other important ways readers learned about this issue? Directly from news sites, no platforms needed. About one-quarter of the overall traffic to immigration articles was from editorial promotion: site homepages, section pages, and links within articles.
For the specific topic of asylum seekers, we looked at where else people talked about this topic:
Twitter sent almost as much traffic as Google to stories about this topic. And Instagram shows as a significant referral – one of the more surprising results of this data to me. With data about what’s relevant to readers right now, and where, teams can be more pointed in how they spend precious resources, including their time.
Narrow in on what topics matter to different localities
Where people are paying attention to stories doesn’t just apply to places on the internet—search, social, etc. Readers’ physical locations impact attention, too.
For stories about immigration, attention wasn’t at the same level across the entire country. Certain areas, including parts of Texas, New Mexico, and Arizona, over-indexed, represented by darker colors on the maps below.
Geographic data can also inform where a story gets distributed. If you’re pushing your immigration story out on Facebook and Instagram, geo-target cities or states where attention, and therefore interest, is already high. Or if your newsroom is part of a network that spans multiple regions, this information can help guide syndication strategy.
Don’t get more data. Get relevant data
It would be amazing if organizations had more of everything: more staff, more resources, more time, more universally accessible sources of data and information. But the reality is you have to pick and choose your data wisely. You need to use sources that can find opportunities for your site, instead of accessing the same list or information that everyone else uses can make the most of that data.
In the absence of time and resources, focus on making sure you have the right data at your fingertips. Pay attention to the data that’s relevant: what audiences care about right now, where they’re finding that information, what stories are related, and where the gaps are.
After last week’s uproar over Mark Zuckerberg’s comments on censorship, Axios asked experts what they would do to decrease the fake news on Facebook. Clearly, this is not a simple problem to address but we must. In fact, because Facebook hasn’t taken proper action over the past two years, governments all over the world have stepped in to take steps to address the problem of misinformation.
As the trade organization representing media brands that seek long-term consumer trust through the creation of high quality news, information, and entertainment, we take the problem very seriously. In 2016, we wrote an unanswered letter to the CEOs of Facebook and Google – Mark Zuckerberg and Sundar Pichai – to provide our perspective on the dangerous proliferation of “fake news” throughout the digital ecosystem.
In the letter we asked Facebook to aggressively harness their brilliant minds and massive resources to clean up the garbage that was flowing, with little friction, through their platform. We also cautioned against acting as a censor. Given the escalation of concerns and the fact that the 2018 midterm elections are less than 100 days away, it’s critical that Facebook take more significant and concrete actions to help ensure their platform isn’t used against our democracy again.
In the spirit of transparency, here are a few things we mentioned to Axios that Facebook could do today.
Eliminate the viral and monetization benefits for known fake news peddlers. Take Infowars as an obvious example. (1) At this point, Infowars should only reach users who explicitly follow its account. We’re not asking for the account to be banned entirely, although the arguments to do so are reasonable at this point. (2) Infowars shouldn’t be able to buy advertising with creative containing links to Infowars content and (3) user activity (likes/clicks) on Infowars content should not enhance its presence in the feeds of users who don’t follow it. Essentially, their content shouldn’t be exposed to users unless they explicitly ask for it. It’s why on Tuesday I asked what percentage of the views of a grotesque Infowars clip were viewed by Infowars followers. The answer could be very revealing.
Publish a clear escalation policy (as YouTube does) which would suspend and permanently ban accounts which repeatedly violate their hate speech and harassment rules. Although YouTube’s escalation seems to have loopholes and oddities, as proven yesterday, it’s at least transparent and up for scrutiny by the public.
Elevate the brand presence around content. The brand is a proxy for trust and Facebook (and Google) have long minimized the brand in their experiences. This is important for those who have built up trust through their reputation but it’s also important to newer publishers who want to build their brands. If you’re reading an Axios story on Facebook in your feed, you should know the source. Likewise, if you’re reading a Russia Today story, you should know the source.
Develop a transparent ranking system by domain/brand. This is not a novel approach: Google does it. Email services do it. If Infowars wants to keep publishing garbage, then let’s see their domain score fall off a cliff. The score has to mean something. The fact is that most respectable news publishers, regardless of subject matter or leanings, would score well and not be impacted. However, the trash would get taken out.
Hire more human moderators. Algorithms are amazing but personal responsibility should involve people. The company needs to take ownership over its “news feed” or stop calling it a “news feed.” We also need transparency on where these moderators are being hired. As platforms have challenged the economics of local news, we’ve also lost local accountability to the public. Moderators need the proper context for the areas, countries and cultures they’re serving.
Engage with member associations and non-profits to get advice on codes of conduct that responsible news organizations follow. Facebook had a significant misstep here when they rolled out their political advertising labels and archive. They dangerously conflated boosted news coverage about political issues with advertising about political issues. Facebook chose to ignore counsel from publishers and shut off communication with member associations despite more than 20,000 news publishers expressing concern to its CEO and COO.
A couple of executives at what is arguably the most impactful news distributor on the planet are making business decisions that have a massive impact on the political dialogue in our democracy. They should thoughtfully listen to concerns, advice, and legal inquiry in order to become a responsible member of the digital ecosystem from which they reap great profit. The problem of misinformation is not small, it is not easy, but it’s a problem that we all have a stake in solving.
Google and Facebook’s dominance of the digital advertising market is well documented. Pivotal Research’s Brian Wieser estimated at the end of 2017 that these two companies “accounted for 73% of all digital advertising.” In the same report, he also estimated that the duopoly accounted for 83% of all growth, which means their grip is only getting tighter.
Scale is the main reason these companies dominate. Facebook has a huge user base, particularly when you factor in its ownership of Instagram and WhatsApp. And let’s not forget its “like” buttons on more than 8.4 million websites, a number Facebook recently disclosed in its answers to lawmakers’ questions during the Cambridge Analytica hearings. Despite lingering legal questions, those “like” buttons continue to collect data about the sites visited by Facebook users regardless of whether those consumers are logged in to the platform. Even more concerning, the buttons also collect data about non-Facebook users. The result is a massive and rich database of consumers’ personal information and activity, which Facebook offers to advertisers for targeting ads to very specific audiences on and off Facebook’s properties.
Google also offers hugely popular consumer services including its search, Gmail, Chrome, and maps applications. Of course, it mines them for very sensitive information about consumers (e.g. personal messages, friend networks, interests, location). Oh, and let’s not forget that Google has a hand in every part of the digital advertising supply chain. Like Facebook, Google is ubiquitous and nearly impossible for consumers to avoid.
No competition
Some might be tempted to argue that these companies serve as competitors to one another. Except that they don’t compete on price. The fact that these services are offered free of charge has enabled their lawyers to shield them (so far) from any antitrust scrutiny in the U.S. What they really compete over is which company can collect more data about consumers. This unbridled competition for data is even more corrosive as it lacks transparency and they offer no effective choice mechanisms for consumers.
Consumer groups assert that this dynamic is bad for privacy. And, they might have a point: Consumer trust is at all time low while adoption of ad blockers continues to rise. Yet, Google and Facebook haven’t felt the impact of this lack of consumer trust. That’s because these companies don’t care where ads are served and they have virtually unlimited places to serve ads (meaning ads can appear near any content, which can create a negative impact by association). Instead, other tech companies, marketers, and publishers bear the brunt of consumer ire.
A dangerous game
But, there is more going on here. Facebook and Google have created a feeding frenzy in the vast, and expanding, data pool. Other companies recognize that have to jump in or risk their ability to compete for digital advertising dollars. Verizon bought AOL and Yahoo! solely to have more ad technologies and inventory. Combined with the significant information about the activities of their user base, this might give them an opportunity to compete for the duopoly-dominated digital advertising dollars. Not to be outdone, AT&T bought AppNexus, the largest independent ad technology company. It’s hard to fault these companies for joining forces given the world they’re competing in.
From my perspective, the duopoly is creating a giant game of musical chairs. If this dynamic is allowed to continue, it’s not hard to imagine that publishers will be forced to pair up with a telecom provider or to form giant conglomerates in order to ensure that they have a chair when the music stops.
Unfortunately, this will have profound effects on well-known premium publisher brands and an even more devastating impact on the ability for new voices to emerge. Ironically, the internet was supposed to increase the number and diversity of voices. Instead, the duopoly is quietly reshaping the web into a dystopian data collection machine.
Ensuring the high-quality of inventory across the PubMatic platform, as it flows from sellers to buyers, requires strong policy, which standardizes compliance enforcement and operational coordination across account teams so that we spot issues early and often. It also requires a strategic focus on identifying what lies ahead for quality.
I’d like to share my thoughts on a few growing trends I expect to see regarding inventory quality. These views come from an amalgamation of inputs: my 10 years of experience in managing inventory quality, the signals and other clues arising from my daily quality operational work, and deep-dive investigations. Buyers have shifted their emphasis to quality and are focused on working with other quality-centric professionals across the industry.
Here are three major inventory quality trends:
Over-Reliance on Fraud Detection Technology
The industry has clearly spoken – third-party fraud detection is now considered “table stakes” for any large player, buyer or seller, in the digital advertising ecosystem. Though fraud detection vendors play an important role in helping to identify and avoid invalid traffic (IVT), I would advise treating this service as one tool among others to help improve quality.
Why?
No vendor measures quality the same way, yet many of them share the same MRC certification for Sophisticated IVT (SIVT). PubMatic uses a combination of IAS and White Ops to monitor invalid traffic rates and identify problematic pockets of inventory. However, many buyers use different fraud detection vendors and they may report very different results for the same inventory. These variances can be explained by unique proprietary methodology and differences in sampling where one vendor may look at a completely different subset of the same inventory vs. another vendor.
For example, if “Buyer A” is reporting their inventory is 100% IVT, while PubMatic’s White Ops reporting is showing 1%, the promise of fraud detection technology as a standalone method to identify non-human traffic breaks down. Yet, when stepping back and viewing fraud detection as a starting point, conflicts between buyers and sellers are more likely to come to an agreement. I believe this because both parties can recognize that even with big differences in fraud reporting, a deep-dive investigation will uncover other signals that likely support one report or the other.
In this specific example, I may find other evidence supporting the buyer’s claim and could come to a mutually agreeable conclusion (e.g. refund, blacklisting, termination of supplier, etc.). However, as often as not, my investigation might raise no other red flags to indicate poor inventory, and thus I would propose limiting access to that inventory for this buyer.
Growing Importance of Content and Audience
GDPR has impacted the ability of marketers to fully utilize the targeting potential of cookies and audience profiles in EMEA due to the regulatory changes in consent and privacy. One could argue GDPR is a direct consequence of the rise of ad tech and the lack of self-regulation concerning how the data of consumers are used in the targeting of advertising. Therefore, it is not unlikely that similar consumer data privacy and consent laws will spread around the globe. This will further reduce the efficacy of cookies and precipitating the return of contextual targeting for online advertising.
What does this mean? An increased focus on the quality of content—addressing fake news and brand safety concerns—as well as the quality of the audiences who consume this content as important quality trends in the marketplace.
Recognizing the importance of content and audience to buyers, PubMatic evaluates domains and apps not only on the level of IVT but also on the value of the audience and originality of the content. For instance, an organic, loyal audience is preferred to consumers acquired from other sources. We also avoid content farms and look-a-like sites that exist only as a necessary backdrop to sell ad impressions.
The Importance of Whitelisting and Ads.txt
Since ads.txt was introduced in 2017, adoption has been accelerating. Pixalate reports that as of March 2018, more than 50% of the top 5,000 programmatic sites have adopted ads.txt.
While ads.txt is a valuable tool to combat domain spoofing, it provides no inherent protection against IVT (bots and fraud). Further, it does not guarantee the quality of a domain’s content and audience. For example, a domain created solely for the purpose of driving bot and/or acquired traffic through pages filled with content stripped from other sources can have an ads.txt file, but still be a bad source of inventory.
Thus, working with a whitelist of trusted domains is the single best practice for both buyers and resellers of inventory. Being familiar with the domains on which ads are running, and avoiding all other domains, is the best prevention.
I strongly suspect that most of the behavior leading to poor quality inventory comes from the point where money changes hands—the domains and apps where advertising is consumed. By wisely choosing which domains to work with and working with only whitelisted domains, many quality issues will be avoided entirely. Alternatively, when a small group of domains isn’t enough to meet inventory requirements, working with trusted partners can also provide improved inventory quality and improved brand safety.
Marketing professionals, sales teams, and business owners are constantly chasing new audiences to target. This is only natural, as the more your grow your business and the more customers you reach, the greater your success. It is the core element of all business: the need to achieve stronger and greater consumer support.
But we all know that it’s not a “piece of cake” targeting new audiences, especially when they are beyond who you normally encounter or engage with. There are a lot of unknowns in increasing your audience targeting size. And marketers and publishers need to evolve with the technology around them.
While Lookalike modeling isn’t a term that is new to the marketing technology industry, it is still widely misunderstood. It is a tool that has been used by companies to expand their digital audiences while maintaining clear and relevant targeting practices. This piece will take a look into what Lookalike modeling is, how it works, and why it is so important for advertising campaigns.
What is Lookalike Modeling?
If you are looking to increase your targeting efforts with high performing audiences, the answers don’t lie in a mass chain of random messaging to consumers who have zero interest in your product. Instead, your focus should lie on your high performing audiences. What is it about your highest performing audiences that set them apart from the rest? Do they have common interests? Are they from the same geographic area? The best way to acquire new, high performing visitors is to focus on users who resemble your existing visitors, the users who have already shown an interest in your product or service.
Lookalike modeling is a process that utilizes machine learning to statistically analyze a given seed audience (already high-performing audience), identifying the demographics, characteristics, and different combinations of those and other data points. This creates new audiences composed of users that match these learned insights, which are continually updated.
For example, let’s say you’re are hoping to target people who are more likely to click on your ad or watch your video. Lookalike modeling uses machine learning to find more users who will take that specific action. This means your campaigns can scale to reach more people, with a high engagement rate.
How does Lookalike Modeling work?
Let’s say you are a clothing brand looking to boost online purchases for an upcoming sale. The first step would be to place a pixel – a small segment of tracking code – on your purchase confirmation page. This will allow you to track the behaviors of purchasers – during the current sale – as they move throughout the web.
The demographic and behavioral data points of anyone who completes a sale and makes it to the confirmation page can be ingested into a DMP platform and analyzed to identify which behaviors and patterns are most common among the audiences. Once those customer characteristics and data points are identified, you can use them create your new seed audience and ultimately engage with an even greater target audience.
It’s a truly incredible process that uncovers the hidden attributes that can optimize your performance for future campaigns. Icing on the cake? It’s all done in a centralized platform.
Why Use Lookalike Modeling?
Well, I guess the question would be, “Why not”? As an advertiser, when consumers within a specific audience converts, it’s a fulfilling feeling. And while you want to hold on to that high performing target audience, you still want to ensure you are growing your brand following.
By using a lookalike modeling tool, it helps you to identify a larger pool of possible customers. You can use the tool to seek audiences with behaviors that match up to your target audience, and so you have a greater chance to convert them. It’s essentially the same as building a robust profile of existing customers, only you are doing it for the audiences you have yet to reach out to and engage with.
In summary, Lookalike Modeling offers marketers and publishers a valuable approach to reaching new or current consumers in a cost-effective way, ultimately helping companies to grow the scope and reach of their businesses. Why not take advantage of your already high performing audiences and increase your brand awareness? As the industry continues to look for new and innovative ways to reach new consumers, lookalike modeling will help marketers stay true to their core and use what they already know to improve campaign success.
It’s a message we’ve been hearing percolate through the industry now for years: programmatic is the future of advertising. Brands, in search of more control over their media buying activity, have embraced technology-based approaches that promise efficiency, precision, flexibility, and superior ROI. Warts and all — and there are plenty, ranging from flat-out false value propositions to rampant fraud and monopolistic marketplace control by actor behaving badly — programmatic is here to stay.
Media planners and buyers have arrived at this conclusion, however begrudgingly. But other participants in the advertising ecosystem — designers, copywriters, developers, and publishers — are wading into programmatic territory in earnest now as well. Here’s what they need to know about programmatic.
Audiences Increasingly Rely on Programmatic-Driven Experiences
Digital users — across desktops, laptops, tablets and smartphones — increasingly expect tailored experiences, from both independent and sponsored content. And the most the efficient way to deliver custom experiences is via programmatic platforms.
For progressive advertising professionals, this is a welcomed opportunity (more on that later). Technology companies and developers benefit from this market evolution via an increased need for their solutions and services. Publishers, however, don’t have much of a choice in this regard. In order to encourage engagement, and minimize the deployment of inhibitive tools such as ad blockers, user experience must be a paramount consideration. Content providers that deliver optimal UX — which includes unobtrusive but effective advertising, such as native tactics — will win in the long run.
Dynamic Ad Creative Is a Genuine Game-Changer
One of the underlying historical maxims of the ad business has been its aim to distribute messages “to the right person, at the right time, at the right cost.” Though this has typically been more aspirational than realistic (and a regular source of frustration for creative professionals in particular) technology-enabled advertising does genuinely provide the opportunity for more specific customization.
To be sure, as a broader umbrella category, “digital marketing” was a step in the right direction on the road to customization (and what will eventually be widespread “personalization”). But due to a combination of hypergrowth conditions and the lack of internal structures to accommodate customization, the industry as a whole has lagged in this regard. As a recent BCG analysis explains, “Within both agencies and publishers, organizational silos with little cross-functional interaction lead to excessive work and rework, including costly handovers, long wait times, and fragmented decision making.”
Programmatic seems poised to serve as the bridge to genuine, industry-wide progress on the customization front. In a few short years, most campaigns will adjust art and messaging to accommodate fluid factors such as time of day, geography, demographics, user interests and behaviors, and the like. This will almost certainly improve campaign performance. It will also impact the underlying cost structure of campaign delivery. This will require more creative labor, for example, so the net ROI effect remains to be seen.
The Programmatic Train Has Left The Station
Like “digital” before it, programmatic will likely lose its specific designation over the next decade, and morph into a marketing channel line item or equivalent. But until it does, it will continue to be popular fodder for industry publications and conferences. And not without good reason. Most estimates peg the U.S. programmatic marketplace in the tens of billions of dollars annually, and growing in the double-digit range. eMarketer sizes the market at $46 billion in 2018, and comprising more than 80% of the entire digital display category, and a major factor in mobile advertising.
That said, in spite of its formidable size and growth forecast, all is not well in the programmatic category, and brands, publishers, and vendors alike are scrambling to address problems related to the big three challenges: fraud, transparency, and viewability. To wit, also according to eMarketer analysis: programmatic growth through 2020 will be driven by “private setups, such as private marketplaces (PMPs) and programmatic direct transactions, as buyers continue to be wary of the open markets’ transparency and quality issues”. [Disclosure: DCN is involved in one such marketplace, TrustX.]
It’s both an exciting and terrifying time to be part of the advertising business. Brand, publishers, and agencies alike are scrambling to navigate the constantly shifting terrain that’s characterized by tens of thousands of vendors competing for share and voice. Programmatic is one of the driving forces of disruption and upheaval in our industry today, and will play a big role in shaping the industry for years to come.
About the author
Raquel Rosenthal is the Chief Executive Officer of Digilant US, a programmatic marketing company headquartered in Boston. A digital industry veteran, she’s held various senior positions at Digilant, DataXu, AudienceScience, and DoubleClick. Raquel splits time between Dallas and New York City, and holds a B.S. from Ithaca College.
Media channels, more than ever before, need to develop consumer relationships throughout the funnel. To do this, they must focus on providing trustworthy content relevant to users as well as context relevant to digital advertisers. The fact is that not all content is equally trustworthy. Marketers who use reach and viewability as their key criteria need to factor trust into their media planning equation.
The new edition of Adtrust’s research, The Company You Keep, offers the latest findings about consumers’ trust in media and the impact of context on digital advertising. The study, based on 4,000 Australian adults, measures consumer trust in content and in advertising being carried by the medium. The study measures the influence of the environment on the advertising on it. The greater the trust in content, the greater the trust in ads, the greater the drive for purchase intent. Yes, environment matters.
The study measures the trust net score (TNS). This measures people’s distrust as well as their trust. The score subtracts the number of consumers who do not trust content (or ads) from the proportion that do trust. For example, if 45% of consumers trust radio content and 20% do not, the net trust score for radio content is 25%.
Among all media (online and off), newspapers earn the highest trust net score (TNS) for both content (48%) and ads (38%). Among digital media sites, news sites earn the highest TNS in both trust in content (34%) and trust in ads (23%). Social media sites earn the lowest TNS in both trust in content (-20%) and in trust in ads (-28%). Importantly, consumers’ trust in news media’s content and advertising has continued to increase over previous studies.
The study asks additional trust-oriented questions about Facebook. The social platform is distrusted more now than it was six months ago. In fact, more than half of all Australians (58%) report that they now trust Facebook less than last year. Further, only one in 10 Australian adults (14%) agree that “I trust the information provided in advertising on Facebook.”
The Adtrust research one again finds that trust of the advertising environment, the place where the ads appear, impacts advertising effectiveness and purchase intent. It reiterates the importance of marketers advertising in a clean environment with trusted publishers.