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Retargeting lexicon

An ever-growing directory of common app marketing terms

It’s hard to master a culture if you don’t know the language. Same goes for understanding mobile marketing. Therefore, we have collected and defined the terminologies used in the industry in one location. Keep checking back as we will be adding new terms periodically.



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.

Android Advertising identifier (AAID)

The AAID is a unique device identifier that Android generates and assigns to every device. Advertisers can use this to track user’s activities across apps, show them personalized ads and attribute ad interactions.

App Monetization

The strategy an app developer/publisher employs to earn money from their app.

App Tracking Transparency (ATT)

ATT is a framework from Apple that manages the process of obtaining user consent before accessing their Identifier for Advertiser (IDFA).


Mobile attribution is the method of matching data points such as crediting ad impressions or clicks with corresponding app-install and post-install events or attributing ad spend to user engagement or installs based on certain variables.

Attribution tries to explain what happens when a user interacts with an ad but relies only upon a timely correlation of events per user, not taking into account other influencing factors that might have led to a conversion.

Common attribution models are click-through, view-through, last touch, and multi-touch attribution.

Attribution Methodology

A methodology used to identify which conversions belong to which preceding click or impression.


Behavioral-based bidding

Behavioral bidding is a dubious practice that is based on identifying groups of users that are known to drive high revenues for a certain app, then bidding aggressively on them to gain new users for other apps.

Behavioral bidding is also one of the main reasons behind Apple's privacy policy reform.


California Consumer Privacy Act (CCPA)

The California Consumer Privacy Act (CCPA) is 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 about a consumer collected from that consumer.
- Equal service and price, even if they exercise their privacy rights.

Causal Impact

Causal Impact Analysis is a framework developed by Google that is routed in econometrics. It scientifically measures incremental uplift across various conversion events, separating organic conversions, as well as uplift from any other marketing initiatives. It is also able to observe the re-engagement impact of your UA campaigns. It does not need user IDs to work.

Similar to how TV ads are being measured, the principle is based on running campaigns on identifiable sub-markets (Treatment), while leaving other sub-markets unexposed (Control). It requires building multiple control groups that are statistically equivalent in time components, and forecasting the baseline values for the time period after the event. The difference between observation and prediction yields the incremental impact.


A user clicking on the displayed ad.

Contextual targeting

A type of targeting that works with interest and demographic-based, device-level contextual signals, such as location data (country, city, zip code), language setting, mobile operating system, device model, as well as publisher information.

Continuous Uplift Tracking

Continous uplift tracking is a part of Remerge's product offering that aims to constantly determine the true value of campaigns. This round-the-clock monitoring system runs throughout the duration of a campaign to further determine the exact value of each optimization.

This type of uplift tracking is always running in the background for all live campaigns. In doing so, advertisers receive complete transparency over the exact value the campaigns deliver while optimizing campaigns for incrementality.

Control Group

Also known as the holdout group, the control group is a group of users that is part of the desired segment on a campaign, but that will not receive any ads. The control group is not shown any ads, so it becomes possible to evaluate the organic conversions that can arise without an ad's influence. The control group is generally smaller in size than the test group.


Demand-Side Platform (DSP)

A platform that allows advertisers to purchase ad inventory across programmatic ad networks. The platform is built to place bids on the advertisers' behalf to identify, win the desired ad inventory, and optimize on RTB spending.

The real-time bidding process, through ad exchanges, occurs in milliseconds, as a user's computer loads a page or app. This powerful technology enables advertisers to automate the purchase of display, video, mobile, and ads according to information about users' location and/or behavior.

Dynamic Content Ad (DCA)

A dynamic content ad is created real-time based on user behavior with the intent of delivering a tailored experience based on each user's behaviors, preferences, and intentions. DCAs can have different formats and consist of many custom assets.

A DCA is dynamically assembled in milliseconds, based on the user's previous behavior and information from a regularly updated product feed.


Exposure Rate

In the context of uplift testing, exposure rate is the calculation of the number of users in the test group who had impressions.
The exposure rate comprises all unique users (UU) that received a minimum of one impression in the test group. The goal is to increase the exposure rate.


General Data Protection Regulation (GDPR)

The General Data Protection Regulation (GDPR) 2016/679 is a regulation in EU law on data protection and privacy in the European Union and the European Economic Area. It also addresses the transfer of personal data outside the EU and EEA areas.

GDPR was devised to protect and define how data held by companies is handled across all industries, including programmatic advertising. GDPR grants the users control over how their data is stored and used by organizations. Organizations are required to be completely transparent over the ways they store and utilize said data.

In advertising, gaining and retaining consent from users is crucial in how the products and services sold in the ecosystem. Therefore, to comply with GDPR, programmatic sellers must effectively communicate to users how their data will be stored and used and make sure they understand how giving consent can benefit them. From the user perspective, giving consent enables advertising to be targeted and, therefore, more relevant.

Ghost Bids

Ghost bids is Remerge's bidding strategy used for incrementality campaigns that tracks revenue and conversions via users divided into a test group and control group.

This method has no additional cost and the lowest noise possible. On it, we track revenue and conversions for all users who fall into the target segment and are seen on RTB ad exchanges, regardless of placing a bid for that user or not. The desired users are divided into a test group (exposed to ads) and a control group (not exposed to Remerge-served ads).


Identifier for advertisers (IDFA)

Short for: Identifier for Advertisers. An IDFA is a unique random device identifier Apple generates and assigns to every device. Advertisers use IDFAs to track users' activities across apps, show them personalized ads and attribute ad interactions.


A view of the displayed ad by a user.

In-app Event

In-app actions taken by the user, such as login, registration, tutorial completed, or purchases.

In-app events can be tracked by the mobile measurement partners and allow advertisers to measure the effectiveness of their campaigns through the performance indicators (KPIs) defined in the earlier stage of their campaign setup.

Tracking events enables advertisers to spot usage patterns and identify user segments for effective retargeting.

Incremental Conversions

A performance indicator that reflects how many conversions of the users targeted by the campaign are incremental as compared to the control group.

In more transparent terms, incremental conversions are the conversions that occurred as a result of your campaign. They are incremental because they wouldn't have happened if your ad was not shown.

Incremental Conversions = Test Group Conversions − Control Group Conversions (scaled)

Incremental Cost Per Action (iCPA)

A metric (also referred to internally as Cost Per Incremental Conversion) that enables the advertiser to determine the incremental cost it takes for a user to make a conversion or purchase.

Looking at the cost per incremental conversion (iCPA) for goal-setting and performance evaluation makes sense for campaigns using a business model that is not reflected by tracked revenue or when revenue is not available from the in-app event stream.

iCPA = ad spend / incremental conversions

Incremental Return On Ad Spend (iROAS)

The difference between the test group revenue (exposed to ads) and control group revenue (not exposed to ads) divided by the funds invested in ads.

Incremental Return On Ad Spend is a KPI that reflects how cost-efficient a campaign is. It only accounts for users who are making a purchase disregarding organic conversions, which makes it an excellent metric for calculating the specific impact of a campaign.

An iROAS > 100% means the campaign is generating more incremental revenue than the cost of the campaign or, in other words, a positive ROI. For every $1 spent in ads, the company gets $5 back, making $4 in profit. Formula = incremental revenue / ad spend.


The method Remerge uses in measuring the impact of marketing campaigns by differentiating organic traffic from paid installs.

The challenge of distinguishing organic traffic from paid installs is a common issue in the mobile marketing industry. This often leads to miscalculations on the marketing spend and, in a worse-case scenario, end up leaving marketers paying for install that would have happened free of charge.

These issues can be solved by measuring incrementality, showing the impact of marketing campaigns and the extent of the organic traffic.
With this method, one can measure the true cost of each incremental conversion and scale that channel accordingly.

Intent-to-Treat (ITT)

This method of incrementality testing and measurement compares the behaviour of a test and control group by exposing a small portion of the test group to the ad. With ITT, the control group is not shown any ad. The behavior of the entire audience of the control group is then compared to the behaviour of the entire audience of the test group (including the unexposed users).
It is the most commonly used because of its ease of implementation, however creates noise in data.

In an effort to minimize noise, another version of Intent-to-treat measurement compares the behaviour of the entire audience of the control group with only the exposed users of the test group.


A potential in-app ad space that is meant to display the ad to a user visiting the app.

iRevenue (Incremental Revenue)

A metric that reflects how much of the attributed revenue of a campaign is incremental, compared to the behavior of the control group.

This metric captures how much additional revenue a campaign is driving on top of organic behavior and other marketing activities.

Formula = revenue with retargeting - revenue


Key Performance Indicator (KPI)

The key metrics or data points set by advertisers to track campaigns performance.

Setting performance indicators is the first step to any digital advertising campaign to determine the goals and the success metrics that need to be measured. The type of performance indicators depends on the goals and nature of each campaign. Commonly used KPIs include iROAS, iCPA, iRev, among many others.


Last-Touch Attribution (LTA)

One of prevalent methods used by Mobile Measurement Partners, Last-Touch Attribution establishes a match between the last action taken by a user and its corresponding ad click.

In the context of mobile advertising, this model attributes credit to the last Demand Side Platform that generated the click.

When a user converts from an ad that they have clicked on, the DSP that has generated the user's last click is given credit for that conversion event. In case a user clicked an ad multiple times (and each time through a different DSP), the only click that will count will be the last one. The last touch model does not consider previous touch points that a user went through in their conversion path.

Lifetime Value (LTV)

A metric used to calculate the worth of an average user. Lifetime value accounts for the revenue and profit margin a business expects to earn over the duration of their relationship with the user.

Knowing the Lifetime Value metric helps advertisers identify the most valuable user segments, and thus make informed decisions concerning their investments in campaigns.

Retargeting is a campaign strategy implemented to boost the Lifetime Value. By retargeting their users, advertisers have a better chance of keeping them engaged in-app, thus increasing their lifetime value potential.


Mobile Measurement Partner (MMP)

Attribution partners provide a platform that records attribution data of app user events such as ad impressions, clicks, installs, app open, registration, and other conversion events.

This data allows advertisers to determine which sources should be attributed to their paid campaigns and understand the effectiveness of those marketing efforts.


Open Exchange

An open exchange is a digital marketplace where ad inventory from multiple publishers are available for advertisers to bid on.


Programmatic advertising

Programmatic advertising is the automated process of buying and selling digital advertising space using real-time bidding auctions.

Public Service Announcement Ad (PSA Ads)

Also known as placebo ads, this method of incrementality testing exposes a portion of both test and control groups to two different ads. The conversion behaviour between the two groups are then compared directly to see whether the real ad causes a change in user behavior (whether it generates clicks).

The exposed users in the control group receive a PSA ad, also known as social awareness ads for health or charity announcements. The exposed users in the test group receive the actual ad being tested for an impact on revenue.

While this methodology brings the noise in data to zero, it creates a cost for the control group, making this method unsustainable for continuous uplift testing.


Publishers develop and publish apps in the App Stores. Their main goal is app monetization which they will often accomplish via their ad inventory. Traditional publishers such as free-to-play games, media companies, for example, make their revenue almost entirely from programmatic ads.

Publishers are an important part of the advertising ecosystem because they are the source of inventory.

Publishers can be categorized into owned, operated, and managed:

An owned and operated publisher owns its inventory and receives the entire profit for all impressions sold.
A managed publisher does not own its inventory but rather holds business agreements with those who do.

Publisher lookalikes

Apps that are similar to one another in that they operate in the same vertical (e.g. gaming) and serve similar interests (e.g. strategy games).


Queries Per Second (QPS)

A performance indicator for the frequency in which a DSP is called to make a bid on an ad placement to reach a user. In real-time bidding, the more QPS capacity, the higher the volume of the request/query of analyzing and acting on those bids.


Randomised control trial (RCT)

In incrementality, Randomized Control Trial (RCT) is the name if our random separation of users into test and control groups to avoid any kind of bias and to actually allow us to evaluate the effect of our influence via ads. The usual division is 80/20 test/control groups.


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.


Retargeting is a powerful way for app marketers to reach out to their users when they are on other apps. The aim is to reactivate existing users and engage them at all stages of their mobile app experience. By analyzing an app’s audience behavior, demand-side platforms like Remerge can show individuals personalized ads, which encourage them to reinstall an app, re-engage with it or make a purchase.

Return on Advertising Spend (ROAS)

A performance indicator that measures the revenue a company receives for every dollar spent on an advertising source.

Calculating Return on Advertising Spend allows advertisers to see whether the campaign budget is generating sufficient revenue. A positive Return on Advertising Spend indicates that a campaign is generating more revenue than expenses.

In the context of retargeting, incremental Return on Advertising Spend (iROAS) shows the real impact of ad campaigns on the revenue, and doesn't take credit for user acquisition or organic conversions. Incremental Return on Advertising Spend consists of the incremental revenue divided by the cost of the campaign. Tracking this metric allows advertisers to evaluate the success of their campaigns and optimize accordingly.

Formula: ROAS = revenue/cost



A segment is a group of users with shared behavioral
patterns such as activity level, value or amount of purchases, or how recently they last opened your app.

Self-Attributing Network

Self-attributed networks or self-reporting networks are big players like Google, Facebook, and Twitter. They self-attribute their campaigns and do not support intermediary tracking links with MMPs. Self-attributing networks are also known as walled gardens.

Unlike independent players who run campaigns and get their attribution results via a 3rd party measurement tool (Mobile Measurement Partner.), Self-Attributing Networks are closed ecosystems in which all the operations are determined and controlled by the network itself.


SKAdNetwork stands for “Store Kit Ad Network” and is Apple’s measurement framework for tracking mobile attribution on iOS.

Statistical Significance

The term used in incremental measurement that refers to the measurable differences shown by test and control groups in campaigns that were not the result of a random occurrence /incident. Some of the measuring methods include Chi-squared test, Bayesian statistics, and Fisher's exact test.

In an incrementality test, statistical significance is important because it signals if the results shown are worth accurate and thus worth considering/valuable.


Test Group

In incrementality measurement, the test group is the group of users who has at least one impression of an ad. Their actions will be taken into account to calculate if the ads had any relevance in the total amount of conversions when compared to the conversions of a group (the control group) that was not exposed to the same ads.


Uplift Report

A report generated by Remerge that allows Remerge's clients to evaluate the uplift results on incrementality campaigns by presenting the incremental revenue generated on top of organic and all other marketing-driven conversions.

Uplift reports commonly present results for observed values and calculated KPIs. The observed values include ad spend, group sizes, amount of conversions, converters, and revenues per group. All other KPIs are calculated using said values.

User Acquisition (UA)

The process of attracting new users to install and/or purchase your app.

User Acquisition is a significant part of any mobile marketing strategy, and it can be divided into two main types of activities: paid (via ads in mobile ad networks or social media channels), and non-paid (including app store optimization and promotion on owned channels to drive organic downloads).

Since the goal of User Acquisition for mobile is to get users to install the app, advertisers plan user acquisition campaigns from soft launch throughout the app's lifecycle as a way of continuously attracting valuable users.