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Is your DSP protecting your users' data? A Q&A with Remerge's Julie Kremp

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Is your DSP protecting your users' data? A Q&A with Remerge's Julie Kremp

Blog article: Is your DSP protecting your users' data? A Q&A with Remerge's Julie Kremp
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The stakes are high for app businesses when it comes to safeguarding their users’ data - especially when sharing it with DSPs or other advertising partners. How companies collect, process and protect this data can impact customer trust, commercial relationships and even the performance of your marketing campaigns.

At Remerge, privacy and data protection are central to how we work with advertisers. Our Principal Privacy & Data Protection Manager, Julie Kremp, was recently nominated for the PICCASO Awards under the category for Bridging the Privacy and Security Gap. This nomination recognizes individuals and organizations for their work on privacy, information security, AI and compliance.

We checked in with Julie about the legal responsibilities that fall with advertisers and DSPs alike, how Remerge protects advertiser data, and what app businesses should look for when evaluating their advertising partners.

Hi, Julie! Why is user data privacy so important for advertiser apps?

Regulators can order companies to stop processing certain data or delete it altogether under Article 58 of GDPR. For an advertiser app, that could mean losing access to an audience, having to stop using certain targeting signals, or even suspending activity in a particular market.

Under Article 83(5) of GDPR, fines can reach €20 million or 4% of a company's global annual turnover, whichever is higher. For growing businesses, that percentage is particularly important because the potential penalty increases as the company grows.

There are also the requirements set by Apple and Google. An app needs to comply with both privacy regulations and the app stores' own policies, because failure to do so could result in your app being removed.

Beyond regulatory consequences, mishandling user data can damage customer trust, which leads to lower tracking opt-in rates, poorer app store reviews and reduced customer retention, all of which can negatively impact advertising performance.

How does Remerge stay compliant when privacy regulations are constantly evolving?

We treat privacy as an ongoing process rather than a one-off project. Regulations change, platform requirements evolve, and our own technology continues to develop, so our approach needs to adapt alongside them. We continuously monitor regulatory, vendor and platform developments, then translate those changes into requirements for our products, processes and contracts.

Our information security management system is aligned with international standards such as ISO 27001. We also have designated internal and external Data Protection Officers to ensure clear accountability. Every vendor and internal tool goes through privacy and security due diligence, where we identify potential risks and apply a structured framework to address them.

We can't control how regulations will change in the future, but we can control how quickly we identify those changes and respond. This enables us to understand the implications for our clients' campaigns before they become an issue.

What measures does Remerge take to keep advertiser and user data secure?

One of the most important principles is data separation. Data belonging to different advertisers is kept in separate silos and is never mixed. One client's data is never used to inform another client's campaigns.

We also follow the principle of data minimization. We work with pseudonymous advertising identifiers and technical event data rather than names or email addresses. As data moves through our systems, references to individuals are reduced, and pseudonyms are removed entirely from aggregated reporting to anonymize the data.

We don't work with special-category data, such as health information, or data relating to children under 13. If such data is received inadvertently, it's deleted promptly.

From a technical perspective, we use encryption in transit and at rest. Our employees only get role-based access controls to client data, requiring single sign-on with two-factor authentication for added security. Development and production environments are separated, and we maintain encrypted backups, continuous monitoring, incident response procedures and regular staff training.

Data retention is also limited by design. We retain data only while the account is active or for as long as the service requires, whichever is shorter, and delete it when the relationship ends.

We make our security measures available to clients so they can assess them against their own requirements.

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Transparency has always been a priority for Remerge. How do we demonstrate this to clients?

We make important privacy and security documentation publicly available, including our data processing agreement, sub-processor list, and technical and organizational measures. These documents can be accessed through our website and Trust Center, even before a commercial relationship begins. This means prospective clients can complete much of their due diligence without having to contact us.

We're also clear about the responsibilities of each party. The advertiser acts as the data controller, while Remerge acts as the processor. We identify our sub-processors and their locations so clients can assess how their data is handled.

Beyond documentation, we answer security questionnaires, support client assessments and provide access to a designated Data Protection Officer.

For me, transparency means making this information accessible from the beginning, not only once a contract is being negotiated.

What privacy-related questions should advertisers be asking before partnering with a DSP?

  1. Is my data kept separate, or is it pooled with other advertisers' data to improve your models and their campaign results? Get the answer in writing.
  2. What types of personal data do you receive about our users from third parties, and why do you need it?
  3. How long do you retain our data, and what happens to it when our contract ends?
  4. Who are your sub-processors and where are they located?
  5. What are your commitments around notifying me of a data breach?

 These questions help advertisers understand not just what a vendor promises, but how its privacy practices actually work.

What else should advertisers understand about privacy in today's ad tech industry?

There are three points I'd emphasize.

First, privacy and performance don't have to be a trade-off. Holding less data for shorter periods reduces costs and risks. Campaigns that depend on excessive data collection are often relying on weaker signals in the first place.

Second, consent quality is also a performance consideration, not just a legal one. If consent hasn't been collected or recorded properly, the resulting advertising inventory may not be usable. That can directly affect an advertiser's ability to reach its audience.

And third, privacy commitments need to be backed up by evidence. If a vendor makes strong claims about protecting data, advertisers should ask to see the documentation and processes behind those claims.

Where can advertisers learn more about Remerge's privacy policies and practices?

Our Trust Center provides information about our security controls, policies and self-assessments.

We also publish our service privacy policy, data processing agreements for EU and non-EU clients, sub-processor list, and technical and organizational measures on the Remerge website.

If there's anything our published documentation doesn't cover, our team is available to answer questions directly.

To find out more about how Remerge can help your app run high-performing, privacy-compliant retargeting campaigns, get in touch with our team today:

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Everything you’d expect from a mobile DSP, but done better.

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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

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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.

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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.

further reading
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.

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Incremental Revenue (iRevenue)
incremental-revenue-irevenue

The estimated revenue caused directly by the campaign.

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

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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

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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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further reading
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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further reading
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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