What is ATOM ?

Anonymized Targeting On Mobile or ATOM, is an on-device cohort targeting and monetization technology for mobile marketers. It’s a privacy-centric approach to targeting and monetization, built for a world without IDs. It uses machine learning/computing models to process device signals and real-world context of users to predict user traits and classify them into cohorts. It uses no IDs/PIIs, and all data processing and storage happens securely within the user device.

ATOM is a small library that is integrated with an ad SDK of the app. ATOM monitors app usage patterns anonymously and enriches the ad requests with relevant cohorts at a time. The enriched ad requests can be targeted by an advertiser seamlessly, when a specific campaign includes the selected cohorts.

Why ATOM ?

ATOM enables DSPs and marketers to continue reaching the right audiences without compromising on privacy. ATOM supports your efforts to engage users and achieve your advertising goals effectively in a privacy-safe way.

  • For performance buyers, ATOM provides incremental signals over and above the contextual intelligence that you receive through the bidstream. While contextual signals (like app bundle id or other metadata information) point to a user’s ‘moment’ of intent in a particular point in time, it may not provide a sufficient picture of the user behavior. ATOM cohort is a combination of many such moments observed over a period of user activity that helps paint a better picture of a user’s behavior.
  • ATOM provides incremental cohort information (ie. groups of user profiles) that allows bidders to understand with better degree of confidence on what type of users they are seeing in the case of ID-less requests.
  • Match anonymous users to relevant cohorts. Further, learn which cohorts and ads drive your users. ATOM currently supports 30+ standard cohorts that are constantly updated frequently.


ATOM is designed to fully operate without any personal data and strictly adheres to GDPR requirements. By default, an integrated ATOM library does not require MAC-addresses, advertising IDs or any other identifier that can be used to identify the user. The data used for cohort calculations is purely executed on the device. The actual cohort data IDs that enrich bid requests are anonymous with no PII.
To update cohorts, ATOM sends anonymous app usage history to the Verve data center in EMEA. This data is aggregated across all ATOM users and does not include PII and it does not allow to fingerprint or trace back the user.

ATOM Cohorts and Taxonomy

By definition, a cohort is a group of people who have something in common. The ATOM SDK relies on the following anonymous signals to analyse and calculate on-device cohorts.

Device: Device OS, Manufacturer, Model, Timezone, Sensors.
App: Bundle ID / App ID, App starts, Session time, Dayparts.
Ad: Ad events, Clicks, Video started, Cohort affinity.

Behavior-based Cohorts

Tech Enthusiasts100002BehaviourA group of people that are excited about technology, new gadgets and software.
Active Gamer100003BehaviourA group of people that play the game of the app actively, more than 75% of the players.
Casual Gamer100004BehaviourA group of people that play the game of the app casually, similarly to most other players.
Impulsive100005BehaviourA group of people that use the app more often and shorter periods than an average app user.
Healthy lifestyle100006BehaviourA group of people that are into a healthy lifestyle and maintain a steady sleeping rhythm.
Employed100007BehaviourA group of people that are employed and uses the app mostly outside of work.
Loyalty100009BehaviourA group of people that frequently use the app.
Bored people100010BehaviourA group of people that have not much else to do than play the app.
Social interaction seekers100011BehaviourA group of people that interact with social media activities.
Information seekers100012BehaviourA group of people that actively look for news and other information throughout the day.
Sports fan100014BehaviourA group of people that follow sports every day.

Demographic-based Cohorts

Female100015DemographicWomen who engage with the app.
Male100014DemographicMen who engage with the app.
Age 18-24100012DemographicYoung adults whose app engagement is likely to mirror the vibrancy and evolving interests of this dynamic age group.
Age 24-45100011DemographicAdults whose app engagement is likely to mirror the vibrancy and evolving interests of this dynamic age group.
Age 45+100013DemographicMature adult adults whose app engagement is likely to mirror the vibrancy and evolving interests of this dynamic age group.

Location-based Cohorts

At Home100031LocationUsers who engage with the app from their homes.
At Work100032LocationUsers who engage with the app at work.
Not at Home100033LocationUsers who use the app in other settings, outside of their home environments.
Not at Work100034LocationUsers who use the app in other settings, outside of their work environments.

Attention-based Cohorts

High Attention100035AttentionThe ad consistently captures and holds the viewer’s attention.
Mid Attention100036AttentionThe ad attracts the viewer’s attention but may not maintain it fully.
Low Attention100037AttentionThe ad briefly draws the viewer’s attention, which fades quickly.
No Attention100038AttentionThe ad does not capture the viewer’s attention at any point.

Definition of BidRequest Object

userarray of objectsDetails via a User object about the human user of the device; the advertising audience.
eidsarray of objectsContains the Extended identifiers object
idstring; recommendedis the respective cohort ID as per Verve's ATOM taxonomy
sourcestringSource or technology provider responsible for the set of included IDs. Expressed as a top-level domain. For example, the source for ATOM is verve.com.
uidsarray of objectsPasses the User IDs matched from the given provider.


The signal from ATOM will come from the user.ext.eids object (as defined in Definition of the User Object)

Example of Bid Request