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Privacy Sandbox: Remerge & Verve Group pioneer on-device bidding

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Privacy Sandbox: Remerge & Verve Group pioneer on-device bidding

The mobile industry is moving ever-closer toward a privacy-centric future, so the mechanics of programmatic in-app advertising are rapidly changing with it. Google’s solution for Android is their Privacy Sandbox initiative – a set of APIs designed to facilitate the on-device selling, buying and targeting of in-app ad placements, without sharing user data among third parties.

This means that the Supply Side Platforms (SSPs) who sell ad inventory for publisher apps, and the Demand Side Platforms (DSPs) who buy the inventory for advertisers, must now rework their tech stacks to ensure that all parties experience a smooth transition to the privacy-first era. Leading the charge on Android is Remerge and Verve Group – one of the first mobile DSP-SSP partnerships to work with Google on building and testing the Privacy Sandbox.

To learn more about their progress with on-device bidding, and get industry perspectives from both the sell side and buy side, we spoke to Verve Group’s Head of Mobile Product, Gaylord Zach and Remerge’s Staff Product Manager, Luckey Harpley, who is responsible for their Android privacy solutions.

As the first mobile DSP/SSP partnership to test the Privacy Sandbox, how has the process and testing been so far for Remerge and Verve Group?

Gaylord: The objective was to explore the integration of the Privacy Sandbox technologies into real-world use cases, specifically utilizing Remerge's demand-side platform (DSP) capabilities and Verve Group's on-device SDK. Traditionally, integrating ads involved straightforward processes – but in the advent of privacy-focused technologies, our new aim is to ensure that ads are served in a privacy-preserving manner. Verve Group developed the necessary components on the supply side, while Remerge handled the buy side.

Luckey: Together, we set up a test in the form of an on-device, single seller, single buyer auction using the Sandbox’s Protected Audience API (PaAPI). With an emulated device and Verve Group’s test app and SDK, we joined the device to a Remerge custom audience via custom audience delegation. Verve Group initiated an auction which Remerge won, allowing us to successfully render a banner ad via Verve Group’s SDK.

How did the test work from a technical standpoint and what were the objectives?

Gaylord: The test was conducted using emulated devices within a development environment. These emulators simulate the behavior of Android devices, allowing for testing and development without the need for physical hardware. In the development environment, there's a window that resembles an Android phone, where the emulated device operates. This setup allowed for initial testing and validation of the integration between Remerge's DSP capabilities and Verve Group's on-device SDK. The next step would involve transitioning from emulator testing to real device testing.

We also initiated efforts to address ‘frequency capping’ within PaAPI. The absence of advertising IDs presents a challenge for implementing frequency capping on the buy side, as actual user information is unavailable – so frequency capping will be transitioned to the device level to ensure effective control and management of ad exposure.

What changes within the industry have led us to invest into these initiatives?

Gaylord: Previously, user data was shipped to buyers for analysis. However, with these new privacy technologies, data becomes more localized, requiring ad tech players to rethink their model architectures and decide what processes they should run on-device and/or within another Trusted Execution Environment (TEE). As auctions move from servers to devices and other TEEs, the landscape of mobile advertising is undergoing significant change.

Over the past 15 years, numerous business models have evolved around mobile advertising, leveraging platform capabilities and user data – but particularly advertising IDs for targeted decision-making. However, with Google phasing out IDs and promoting on-device data processing, traditional models will become outdated. Investing in initiatives that embrace these changes is imperative for businesses to adapt and thrive in a world where data privacy and user-centric approaches are the priority.

Luckey: Being early adopters of the Privacy Sandbox sets us up for success in the long term – given that privacy-first advertising is going to be the future of retargeting and user acquisition on Android. Investing into these initiatives sooner rather than later is essential because it allows us to play an active role in driving the development of the Privacy Sandbox without interrupting the service we provide for our clients. Working with Google also means we can advocate for the needs of the industry and see these requests materialize into features.

As testing is being carried out, what do advertisers need to know?

Luckey: Live-traffic testing on end-user devices will take place later in 2024 – so at this point, advertisers should stay informed with the latest privacy developments, do their research, and team up with advertising partners like Remerge who are working closely alongside key industry players such as Verve Group and MMPs like AppsFlyer to test and adopt Google’s Privacy Sandbox on Android. After the Privacy Sandbox rollout, in-app advertising should work as it always has, as long as advertisers keep their SDKs updated. For any questions, they can simply reach out to our team at Remerge. We’re always happy to chat.

What is changing from the perspective of an SSP and how does this impact publisher apps?

Gaylord: The previous workflow revolved around sending ad requests to Verve Group's ad server, which then distributed them to multiple buyers, conducted auctions, and returned results to the SDK. However, with the adoption of new technologies, (particularly on-device auctions or auctions within other TEEs), the entire process is undergoing a significant shift. In the new setup, while Verve Group still initiates the auction, the actual auction process now takes place on the user's device.

Consequently, Verve Group is undertaking the heavy lifting in updating its SDK and backend processes – and splitting them into multiple steps to accommodate the change. However, it's important to note that these changes do not affect publishers directly. They simply need to update their SDKs and any SDKs associated with their Mobile Measurement Partners (MMPs). From there, they can continue requesting ads as before.

What does Remerge’s and Verve Group’s ‘bidding proof of concept’ test mean for the development and rollout of the Android Privacy Sandbox?

Luckey: As a DSP-SSP partnership, it’s an exciting first step because it serves as evidence that two independent entities are able to make on-device bidding work successfully. This is great validation for all parties involved. Not only does it prove that our products work, but it shows that the Privacy Sandbox’s APIs are working too – which is evidence that in-app retargeting will continue to thrive in the privacy-first era.

Gaylord: For us, the test symbolizes a collaborative effort towards innovation, privacy, and industry progress. The successful execution of these tests demonstrates the feasibility of integrating Privacy Sandbox technologies into real-world applications. Looking to the future, as the technology evolves, we’ll remain committed to pioneering solutions that prioritize user privacy and experience.

What parallels are there today to bidding on OpenRTB? (Real Time Bidding)

Gaylord: We still kick off the auction process with a contextual bid request via OpenRTB, only without an advertising ID. These requests now signal support for Protected Audiences. The bid response serves as an opportunity for buyers to remotely contribute their data and bidding logic for the protected auction. While OpenRTB remains a vital component of our process, its functionality is evolving to incorporate additional logic, ensuring a comprehensive approach to ad serving and auction dynamics.

How has it been so far working with the Android Privacy Sandbox APIs and how are they shaping up?

Gaylord: Working with the Android Privacy Sandbox APIs has been quite an adventure. While still in the early stages and not yet widely adopted, there's a certain thrill in exploring uncharted territory. There may not be established best practices or extensive debugging experience yet, but we're confident that by the time this technology reaches users' devices, it will have matured.

Luckey: It's been an interesting challenge from a software engineering point-of-view. It's a well-defined space with somewhat of an even playing field to innovate. The product itself has some way to go and a lot of the smaller details are yet to be defined, but Google is working hard to understand the industry and take on our feedback. We’re excited to see this come together and to be part of such an important project.

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Retargeting lexicon
Programmatic Advertising

The automated process of buying and selling advertising space through digital platforms.

View-Through Attribution
view-through-attribution

Refer to: Attribution Methodology

Uplift Test
uplift-test

A randomized control trial test conducted by Remerge to measure the incremental impact of one or more campaigns.

See also: Randomized Controlled Trial

Uplift Report
uplift-report

A report by Remerge showing the results of an uplift test. It presents the incremental revenue generated, on top of organic and other marketing-driven conversions. Also contains observed values such as ad spend, group sizes, amount of conversions, converters, and revenues per group, plus other metrics.

SKAdNetwork
skadnetwork

Stands for Store Kit Advertising Network. Apple’s measurement framework for tracking mobile attribution. Introduced in 2018 and widely implemented in 2020 with the iOS 14.5 update.

Segment
segment

A group of users with common attributes such as location, demographics, activity level, value or amount of purchases, and how recently they last opened a specific app.

Retention Rate
retention-rate

The share of users active in the app within certain time frames after install, reengagement, or other events.

Retargeting
retargeting

A type of marketing channel used by an app owner to engage with their existing users through other channels within the same device. Usually, the aim is to encourage users to complete a particular task e.g. completing a purchase, buying in-game currency, placing a first order. The conventional way of retargeting relies on user IDs, such as AAID and IDFA.

Reshuffle
reshuffle

Reshuffle indicates the randomization and marking of users when they were once part of a test or control group.

In incrementality measurement, reshuffling the group assignment for a specific application fights aggregated bias over time where one group doesn't see any ads while the other group is constantly exposed to them.

Reshuffling is relevant in cases where a test has been running for a long time and/or in campaigns the experience more extensive changes to the campaign setups, segmentation, or creative strategy.

Real-Time Bidding (RTB)
real-time-bidding-rtb

The process by which individual ad placements are bought and sold via programmatic auctions that happen instantaneously. With real-time bidding, ad buyers bid on an ad space, which, if the auction is won, instantly displays the buyer's ad. This lets demand-side players such as advertisers or DSPs optimize the purchase of ad placements from multiple sources.

Randomised Controlled Trial (RCT)
randomised-controlled-trial-rct

A method that randomly separates a specific population into two groups that are as similar to each other as possible, namely the test group and control group.

further reading
Queries Per Second (QPS)
queries-per-second-qps

The number of ad placements a DSP is able to process in order to determine on how to bid on them.

Publisher
publisher

Within the sphere of app marketing, a publisher is an App Developer that gets paid for placing ads within their app. For example, an advertiser wants to reach their users via App Y, so they pay App Y to display their ads.

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Public Service Announcement Ad (PSA Ads)
public-service-announcement-ad-psa-ads

An incrementality testing methodology where devices in the control group are shown PSA ads, like donation drives or road safety reminders. By serving real ads, information on the devices within the control group that would have been exposed can be obtained. Unexposed devices are excluded from the measurement to reduce noise.

Probabilistic Attribution
probabilistic-attribution

Refer to: Attribution Methodology

Organic Behavior
organic-behavior

A user’s behavior not directly attributable to specific marketing efforts.

Multi-Touch Attribution
multi-touch-attribution

Refer to: Attribution Methodology

Mobile Measurement Partner (MMP)
mobile-measurement-partner-mmp

Within the sphere of app marketing, MMPs are a service provider that specializes in measuring activities that are happening within and leading to the app. An app publisher may incorporate an MMP into their app to track activity and events e.g. time spent on a certain screen, sources of incoming traffic, app opening frequencies etc.

Lifetime Value (LTV)
lifetime-value-ltv

The amount of revenue generated by the user for the App Developer during the entire duration of the relationship with the user, beginning with the app install.

Last-Click Attribution
last-click-attribution

Refer to: Attribution Methodology

Key Performance Indicator (KPI)
key-performance-indicator-kpi

The key metrics used to assess the effectiveness of an effort in achieving its objective. In programmatic advertising, the common types of performance indicators depend on the goals and nature of each campaign. These can include ROAS, cost per action, and retention rate.

Intent-to-Treat (ITT)
intent-to-treat-itt

An incrementality testing methodology where no ads from the campaign are shown to devices within the control group. Also known as a ‘holdout test’. Cost-free and easy to implement, but with a relatively high level of noise.

This method compares the behavior of all users in both groups. In the test group, this includes both exposed and unexposed users

Incrementality
incrementality

A method of measuring the impact of a specific activity, on top of organic and other activity.

Incremental Revenue (iRevenue)
incremental-revenue-irevenue

The estimated revenue caused directly by the campaign.

Formula:Revenue from test group – revenue from control group = iRevenue

Incremental Return On Ad Spend (iROAS)
incremental-return-on-ad-spend-iroas

A KPI used in calculating how cost-efficient a campaign is. This is used to evaluate the relationship between incremental revenue and the amount of money spent on the campaign. The figure is typically represented in percentage.

Formula:
Percentage: [IRevenue ÷ ad spend] × 100 = IROAS%
Ratio: IRevenue ÷ ad spend = IROAS

Incremental Cost Per Action (iCPA)
incremental-cost-per-action-icpa

A KPI used to evaluate the cost of incremental conversions.

Formula:Ad spend ÷ [test group actions – control group actions] = iCPA

Incremental Conversions
incremental-conversions

The estimated amount of conversions caused directly by the campaign.

Formula:
Test group conversions – control group conversions (scaled) = Incremental conversions

In-app Event
in-app-event

Actions made by a user within the app, such as log-in, registration, completion of onboarding, or purchases. These events can be tracked with the help of an MMP.

Impression
impression

The deployment of the ad to the ad placement. An impression might not necessarily mean that the ad has been viewed.

Identifier for advertisers (IDFA)
identifier-for-advertisers-idfa

A unique random device identifier Apple generates and assigns to every iOS device. Advertisers can use this to track user activity across apps, show them personalized ads, and attribute ad interactions.

Ghost Ads
ghost-ads

A testing methodology that shows devices in the control group an ad ran by another advertiser on the platform, therefore removing any additional cost for clicks and impressions. The control group behavior is then marked with a ‘ghost impression’, which gives the information on which control group users would have been exposed.

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General Data Protection Regulation (GDPR)
general-data-protection-regulation-gdpr

A regulation under the EU (European Union) law on data protection and privacy within the EU and the EEA (European Economic Area), that grants users control over how their data is stored and used by organizations. To comply with GDPR, programmatic sellers must clearly communicate to users how their data will be stored and used. When a user gives consent to an organization to process their data, it enables targeted advertising.

Exposure Rate
exposure-rate

The percentage of devices within a test group that received at least one ad impression, versus the total number of devices within the test group targeted within a campaign during an uplift test. For example, if 900 out of 1,000 users are shown an ad, the exposure rate is 90%.

See also: Uplift Test

Deterministic Attribution
deterministic-attribution

Refer to: Attribution Methodology

Deep link
deep-link

A link that sends users directly to a specific in-app location, instead of the app marketplace. Deep links bypass the steps needed to go through to reach a conversion point, bringing the user directly to where they can perform the intended action e.g. completing a purchase, buying coins, placing an order.

Test Group
test-group

Within the sphere of app marketing, this refers to the group of devices that may be shown ads from a specific campaign in the test. The actions on these devices are then compared to the actions on the devices in the control group.

Compare with: Control Group

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Control Group
control-group

Within the sphere of app marketing, this refers to the group of devices within the target audience that are not shown ads from a specific campaign in the test. The actions on these devices are then compared to the actions on the devices in the test group.

Compare with: Test Group

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Contextual targeting
contextual-targeting

A type of targeting that works with contextual signals only, such as location data (country, city, postal code), language setting, mobile operating system, device model, as well as publisher information.

California Consumer Privacy Act (CCPA)
california-consumer-privacy-act-ccpa

A bill that enhances privacy rights and consumer protection for residents of California, United States. The CCPA took effect on January 1, 2020.

The CCPA provides these rights to consumers:

- Know what personal data is being collected about them.
- Know whether their personal data is sold or disclosed, and to whom.
- Say no to the sale of personal data.
- Access their personal data.
- Request a business to delete any personal information that was collected from that consumer.
- Equal service and price, even if they exercise their privacy rights.

Attribution Window
attribution-window

A specific time frame that is taken into consideration when determining the source of a user’s action.

Attribution Provider (AP)
attribution-provider-ap

A role played by an MMP to credit the in-app activity of users to the correct media sources.

Attribution Methodology
attribution-methodology

Refers to the process of identifying which conversions belong to which preceding click or impression. Common attribution methodologies include:

  • Click-Through Attribution - Determines the source of a conversion based on the user’s click activity.

  • View-Through Attribution - Determines the source of a conversion based on the ad impression delivered to the user.

  • Deterministic Attribution - A model that establishes the origin of a user’s conversion from a specific click or impression, based on unique device IDs.

  • Probabilistic Attribution - A model that establishes the likelihood of a user’s conversion originating from a specific click or impression, based on the data logged on both occasions, such as device language, timezone, IP address, and OS version.

  • Last-Touch Attribution - A model that establishes a match between the action taken by a user (e.g. app open, purchase) and its corresponding ad click or impression. When a user converts from an ad, the DSP that delivered the respective ad is given full credit for that conversion event.

  • Multi-Touch Attribution - Also known as multi-channel attribution. A model determines the value of every touchpoint on the way to a conversion. Rather than giving full credit to one ad, multi-touch attribution divides the credit among all advertising channels that the user has interacted with, leading to the conversion.
Attribution
attribution

A method of identifying the touchpoints a user has encountered within a specified period before making a conversion.

App Tracking Transparency (ATT)
app-tracking-transparency-att

The privacy framework from Apple that, among other things, manages the process of obtaining user consent before accessing their Identifier for Advertiser (IDFA).

App Monetization
app-monetization

The strategy a publisher employs to earn money from their app. This can be done through in-app advertisements, paid membership, and charging for premium features or an ad-free experience, among others. For example, some gaming apps are free to download and play, but users may need to pay in order to progress to the next level quickly.

Android Advertising identifier (AAID)
android-advertising-identifier-aaid

Also known as Google Advertising Identifier. A unique device identifier that Android generates and assigns to every device. Advertisers can use this to track user activity across apps, show them personalized ads, and attribute ad interactions.

Advertisers
advertisers

The advertiser is a person or legal entity focusing on generating sales and leads through serving ads that convey the right message to the right audience at the right time.

In mobile advertising, the advertiser is on the client-side and is the one interested in promoting an app.

Causal Impact Analysis
causal-impact-analysis

A measurement framework developed by Google that works without device IDs. It measures the incremental uplift of one or more conversion events, removing the influence of other campaigns and organic conversions. Used to assess the effect of ID-less campaigns.

Similar to measuring the effect TV ads have, the principle is based on running campaigns on identifiable sub-markets (test group), while leaving other sub-markets unexposed (control group).

Ghost Bids
ghost-bids

An incrementality testing methodology based on Ghost Ads, adapted for retargeting campaigns. The difference is that it removes all devices that are not seen on ad exchanges, or that would not be bid on, from both test and control groups, to reduce noise. A bid is placed as usual for the test group, while the control group is tracked with ‘ghost bids’ (bids that could have been placed, but weren’t in the end).

Return on Advertising Spend (ROAS)
return-on-advertising-spend-roas

A KPI that measures the relationship between the revenue generated by specific advertising efforts and the money spent on them.

Formula

Percentage: [Revenue ÷ ad spend] × 100 = ROAS%

Ratio: Revenue ÷ ad spend = ROAS

See also: Incremental Return On Ad Spend

Supply-Side Platform (SSP)
supply-side-platform-ssp

A company that works with publishers to sell ad inventory across ad networks.

Demand-Side Platform (DSP)
demand-side-platform-dsp

A company that works with advertisers to purchase ad inventory across ad networks. Their platforms are built to identify a desired ad space and place bids on it.

Compare with: Supply-Side Platform

Open RTB
open-rtb

A digital marketplace where ad inventory from multiple publishers are available for advertisers to bid on in real time.

See also: Real-Time Bidding

Self-Attributing Network
self-attributing-network

An ad network like Meta, Snap, and Twitter, that attributes its traffic internally, without the involvement of third-party MMPs.

Variable Bidding
variable-bidding

The dynamic adjustment of bid prices based on a user's in-app behavioral patterns, contextual information, time of day, and ad placement performance.

Dynamic Product Ad (DPA)
dynamic-product-ad-dpa

Also known as a dynamic ad. It is dynamically assembled based on the user’s behavior and information sourced from a feed. This type of ad delivers a tailored experience for individual users.

Real-Time Audience Segmentation
real-time-audience-segmentation

The division of an audience into distinct segments based on real-time events, thus enabling targeted advertising and alignment with a user's behavioral patterns and preferences.

User Acquisition (UA)
user-acquisition-ua

A mobile marketing effort used to attract new users to an app. Paid UA may refer to ads shown in mobile ad networks or social media channels, while non-paid UA involves app store optimization and promotion on the advertiser’s own channels.

Programmatic Advertising
programmatic-advertising

The automated process of buying and selling advertising space through digital platforms.

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