Turn every tap into potential

Press release: Advertising leader Verve’s latest acquisition, valued $185 million (approx. €170 million), also bolsters digital audio solutions, engaging ad formats, and AI optimization.

Thought leadership: Sameer Sondhi talks to Mediashotz at DMEXCO 2024 about anonymous targeting on mobile and the power of blimps.

New initiative unites full-funnel support under Verve brand, while enabling the unique benefits of distinct branding- and performance-focused formats and tools.

Thought leadership: AdvertisingWeek interviews Stafaniya Radzinovik about the future of CTV advertising.

Chrome has dominated the third-party cookie story since Google declared its deprecation intentions. Following an official halt to default blocking, advertising attention is now fixed on the new choice-centric browser experience and how web-based Privacy Sandbox adoption will pan out. However, changes set to be just as impactful for mobile are forging ahead unchanged and largely unnoticed. A Privacy Sandbox initiative for Android has been in the works since 2022. While there is no defined timeline, tools moving into beta last year suggest development is advancing, but many industry players are yet to explore these technologies and their potential wide-ranging impact.  Given Android’s 70% share of the global mobile market, failing to understand and proactively prepare for these proposals is a major oversight that could create sizable challenges for app publishers and advertisers.  Not all sandboxes are the same Firstly, it’s vital to recognize that the web and Android Privacy Sandbox initiatives are separate entities. Both share the mission to protect user privacy and allow businesses to maintain a thriving digital media ecosystem. While these branches share a unified vision and core components, they don’t work in the same way. This is largely due to the focus on usually cloud-centric activity for Chrome Sandbox solutions, while Android tools are designed for app software that users download and engage with via their devices.  Looking closer at the details, there are several key variations across the five main Android APIs — Topics, Protected Audience, Protected App Signals, Attribution Reporting, and SDK Runtime. Cohorts in, IDs out The familiar Topics API concept involves collecting on-device data to determine which topics users are interested in and putting them in cohorts that can be applied for targeting, such as ‘fitness lovers’ and ‘sci-fi fans’.  High on the list of pros for this tool is its capacity to seamlessly slot in with current trading. Topics categories can be added as another signal sent to demand-side platforms (DSPs) along existing programmatic pipes, allowing buyers to place real-time bids on app inventory that will reach relevant audiences, even if they don’t know who exactly will see their ads. Zero reliance on identifiers is also a big plus given their diminishing scope. Google maintains an emphasis on providing options that can work without IDs, because doing so has become increasingly crucial. In the immediate aftermath of Apple’s decision to make its iOS ad ID opt-in only, many users seized the opportunity to improve their mobile privacy, with consent rates teetering at 25% at that time. Opening the box of APIs  The Privacy-Preserving APIs provide another suite of solutions that is distinct from Topics but also intended to support ID-less operations. Within this collection are multiple building blocks designed to support use cases throughout the ad lifecycle, the main elements being Protected Audience, Protected App Signals and Attribution Reporting.  Protected Auction has two strains: Custom Audience for user segmentation in a re-marketing use case and Protected App Signals for app install (aka user acquisition) use cases without the reliance on cross-app identifiers. Crafting custom audiences is about creating groups based on interests or intentions, such as users who have abandoned an e-commerce app purchase over the last month. Local data storage that can’t be transferred between apps helps to maintain user privacy here. Ad Selection in a protected auction follows a structure for managing bidding activity that upends standard programmatic procedure. Normally, app publishers send audience data with bid requests, allowing demand-side vendors to produce profiles that are used for refined bidding according to key advertiser targeting preferences. Protected auctions turn the tables and means that buyers have to bring their requirements and data. This is then used in an auction inside a trusted execution environment and the only information that leaves the auction room is who has won.  Safe in the knowledge that data won’t leave the auction and users cannot be identified in the absence of cross-app identifiers, participants could work with more device-level data to boost ad relevance and impact, as long as there are robust enough provisions to prevent data leakage. In effect, auction spaces could follow the principles of data clean rooms.  Finally, Attribution Reporting functions like Apple’s SKAdNetwork (now App AdAttributionKit). Ad tech vendors register attribution sources (such as clicks and ad views) and triggers (in-app conversions), and the API links the two together through event-level and aggregated summary reports. Measurement is subject to several limitations to ensure advertisers can see a clear line from campaigns to conversion actions, but not individual users.  The great unbundling  SDKs aren’t just a bridge from platforms to apps. Deep integration practices have historically weaved them so tightly into the fabric of apps that it’s difficult to tell where the dividing lines lie. This close connection has facilitated smooth interaction with external tools and services, such as monetization SDKs that enable publishers to fuel crucial revenue with ads and mobile measurement partners (MMP). Yet the same free flow also allows SDKs to inherit privileges and data permissions, which raises concerns about privacy and the risk of unpermitted data collection.  Google hopes to tackle this with its enclosed SDK Runtime environment. By providing an isolation process that can run strains of code independently, the solution will unbundle third-party SDKs from apps. Additionally, there are further plans to cap the data SDKs can access, with initial designs suggesting a default list of four elements: internet connectivity, network information, phone state (such as network type), Google’s Privacy-Preserving APIs, and an ad ID — but only if users have granted the host app consent. These proposals have sparked anxiety about the challenges of complying with differing data requirements, especially for omni-channel campaigns. The reality is that SDK Runtime will likely mean less convolution. Just as Google can issue operating system updates to devices without disrupting apps, third-party vendors will be able to build new SDK iterations and fixes that publishers can implement without having to invest considerable time and resources in re-distributing their apps.  Why should the industry care?  It’s hard to predict precisely how Android tools will evolve or impact the industry. However, we can be sure of the need to...

New report highlights increased openness to balancing free content access with data-driven advertising, alongside a continued need for greater privacy protection and transparency

There’s never a dull moment in the streaming services. For example, earlier this year, reports surfaced that Disney+ might add cable-style streaming channels focused on Star Wars and Marvel content to its service. While viewers would need Disney+ subscriptions to watch, the channels would also likely be ad-supported — representing the latest in what seems to be the ongoing blurring of lines between streaming services and traditional TV.  This latest news, combined with other recent changes to bring more ads into popular streaming services, presents advertisers with an opportunity to connect with a vast and highly engaged audience. The AVOD market is poised for explosive growth, with projected global revenue exceeding $48.32 billion by 2024 and a staggering 3.4 billion users anticipated by 2027. AVOD’s growth is further amplified by the rising average revenue per user (ARPU), expected to reach $16.29 in 2024. Advertisers can seize opportunities to enhance their return on investment and effectively engage with a global audience. While all types of CTV grant access to sizable audiences on connected TVs, their characteristics vary considerably. For advertisers considering AVOD (including FAST channels), understanding where their ads are shown, what happens after they’re displayed, and what actions viewers take is paramount.  Tracking and understanding campaign success means monitoring the right metrics — the ones that truly matter to a campaign on an AVOD service. But which metrics should those be? AVOD metrics that matter  In general, advertisers’ KPIs within CTV advertising tend to be focused on reach, targeting, and campaign optimization for better engagement. Within the AVOD space, here are the metrics that should be prioritized.   Engagement metrics Video completion rate (VCR): This metric measures the percentage of all video ads that play through from start to finish. A good benchmark is above 95% for CTV campaigns. If VCRs don’t reach this benchmark, then the creatives may not be effectively engaging viewers within the first three seconds of an ad.  Viewable impressions: This metric represents the number of times your ad was actually seen by a viewer. While impressions measure the number of times your ad was displayed, viewable impressions track whether those impressions were actively watched. One of the best things about CTV is essentially all the impressions are viewable as they are taking up the entire screen. Visibility metrics Viewability: Viewability is a percentage that measures how easily your ads are seen. This metric is calculated by dividing viewable impressions by the total number of impressions.  Average watch time (AWT): Average watch time is the average amount of time a viewer typically uses an AVOD service. Adults in the U.S. spent close to two hours a day viewing their CTVs in 2023. On average, how much of that time is spent viewing the AVOD platform on which your campaign is running? Performance metrics Win rate: This measures the proportion of successful bids an advertiser wins out of the total number of bids submitted in an ad auction, campaign, or marketplace. Segment performance: This involves analyzing how different demographic segments respond to advertisements. Dimensions like age, gender, location-based performance, and device usage can provide insights into how effectively a brand’s targeting criteria are being met. Advertisers should collaborate with their ad tech partners to gain transparency into this granular data. Conversion rate: In the context of AVOD, the conversion rate measures the number of times viewers eventually take a desired action. This could be anything from visiting your landing page to making a purchase. While some ad formats are currently more measurable than others for conversions (e.g., scanning a QR code to install an app), platforms are continuing to add more measurement capabilities for performance. High conversion rates mean your ads are working. If a metric is not measured, it cannot be improved. Tracking the right AVOD metrics is crucial to making insightful decisions as an advertiser. Monitoring the metrics above will tell you if you are partnering with the right AVOD service, as well as how effective your campaigns will be in reaching your target audience.   Editor’s note: This article was originally published by Streaming Media.

Thought leadership: Gaylord Zach, Head of Mobile Product at Verve, looks at why app publishers and advertisers should be proactively preparing for Privacy Sandbox for Android.

App publishers are facing a data dilemma. Privacy regulations are restricting the use of mobile identifiers, and users are opting out of personalized advertising. This signal loss is leaving many publishers empty-handed. So, how can publishers continue to show advertisers that their inventory and their audiences are attractive? Enter on-device cohorts.  Cohorts are groups of users who share observable characteristics over a certain period of time. These characteristics could be just about any variable: location, demographic, or, in the realm of mobile apps, specific events tied to user engagement within the apps.  Cohorts aggregate users based on commonalities then pinpoint a specific user tied to a known ID (like Mobile ID).  Therefore, cohort-based targeting is perfect for advertisers looking to reach particular audiences without needing unique identifiers — and by adopting a monetization solution that utilizes (on-device) cohorts to signal user value, publishers can attract these advertisers. Our on-device targeting solution, Anonymized Targeting On Mobile (ATOM 3.0), is an innovative tool that uses cutting-edge on-device AI to classify users into cohorts for accurate and granular targeting.  Not convinced yet? Let’s take a look at some more reasons why publishers need to start advocating for on-device cohorts. Privacy compliance As the name suggests, an important advantage of targeting via on-device cohorts is that the data stays on the device. This means that first-party data is gathered and processed within each user’s device, helping publishers ensure data privacy and security.  Keeping data secure is top priority as the alphabet soup of data privacy regulations (GDPR, CCPA, CPRA…) begins to boil over. Utilizing on-device cohorts helps publishers comply with today’s strictest data privacy regulations by ensuring that no personally identifiable information (PII) is used or transferred to third parties. User experience But privacy compliance isn’t just about keeping the policy-makers happy — it’s about the users themselves. Users are becoming increasingly aware of their digital privacy rights. Given the choice, the majority of users opt out of personalized advertising. On our marketplace, 70% of iOS traffic comes from users that do not permit the use of mobile IDs. And in a recent survey by Twilio, 62% of consumers said that protecting their data is the top way for brands to build their trust.  Users are making it clear what they want, and everyone in the advertising supply chain needs to listen. It has become vital that publishers demonstrate a real commitment to data protection — and one effective way to do that is to advocate for on-device cohorts. Investments made now in privacy-focused monetization tools will build trust with their users, and in turn, this trust can lead to better engagement and app loyalty. Data quality Users are taking action against intrusive advertising that exploits their identifying information. At the same time, however, contextually-relevant advertising is vital for driving impressions and engagement. So, the key to user-friendly targeting is about striking a balance: ads need to be contextually relevant without feeling intrusive. An IAS survey found that 63% of consumers prefer to see ads that are contextually relevant. And when it comes to unrelated ads, 35% of consumers find them annoying, 28% find them disruptive, and 22% said they are confusing. So, where is the middle ground where consumers see contextually-relevant ads that do not rely on their personal information? Using cohort data that is gathered on-device provides a new level of accuracy for targeting specific audiences. Advertisers no longer need to rely on potentially inaccurate third-party data for their campaigns. Instead, using on-device triggers to target users by cohort is an ideal way to deliver highly-relevant advertising that users are more likely to find interesting and useful. For example, ATOM 3.0 analyzes a wide array of device signals and real-world contexts, such as app usage pattern, session duration, session depth, gestures, and screen brightness. An innovative machine learning model uses these signals to group users into cohorts such as “Active Gamers,” “Frequent Shoppers,” and “Tech Enthusiasts.” Competitive advantage Early adoption of compliant targeting solutions is the key to future-proofing a monetization strategy. Rather than waiting around for another GDPR-level shakeup, publishers and advertisers alike are turning to cohort-based solutions, fully embracing the “privacy by default” mindset. Currently, less than half of publishers offer cohort-based targeting solutions; yet, 82% of advertisers currently use or plan to implement cohort-based targeting by 2025. This represents a huge opportunity for publishers. Brands are in need of advertising solutions that align with their own commitments to data privacy. Of those not already using cohort-based targeting, 70% will likely adopt it by the end of next year. Publishers can attract these brands by going beyond the current privacy standards and integrating on-device cohorts. Improved bid rates and eCPMs At the end of the day, the effort required for publishers to integrate a privacy-focused cohort-based targeting solution will pay off. In the absence of identifiers, on-device cohorts allow advertisers to continue to reach their intended audience — and this is something that brands are willing to pay for. Compared to the IDFA-less eCPMs we see today, publishers integrating ATOM 3.0 achieve improved bid rates and higher eCPMs. Emerging privacy-enhanced technology ATOM 3.0 is Verve’s on-device cohort targeting technology, providing publishers with a privacy-centric framework for monetizing their mobile inventory. ATOM 3.0 uses machine learning to process on-device and contextual signals to predict user traits and segment them into cohorts. By circumventing the need for unique identifiers, ATOM 3.0 is a secure and future-proof tool for mobile publishers. Publishers ready to get on board with on-device cohorts can get in touch with Verve to begin integrating ATOM 3.0 via HyBid SDK 3.0.

Thought leadership: Publishers and advertisers have myriad options when it comes to sustainable addressability solutions, but which are they prioritizing?