Company Overview

For over 7 years, 33Across has created advanced data models for Fortune 1000 brands.  With code on over 1 million publisher sites, our publisher network yields more than 30 billion intent and interest signals from social sharing behaviors such as copy & paste of images, text and links (both public and private), content consumption/browser behavior, and search keywords.

Data Collection Methodology

Data is collected via our javascript code that is directly implemented on 1MM+ publisher sites. The users are then cookied with a unique 33Across ID that is processed in our proprietary DMP. The users’ copy and paste activity, search keywords, and content consumption on those pages are analyzed and modeled accordingly in our platform in real time. We have several mechanisms in place to validate our users and our segment methodologies. For example, users must be seen more than once in a 24 hour period in order to be deemed a viable user. We are also updating and refreshing our data every 24 hours with new users. Our data is comprised of online signals only.

We are capturing the share that happens when User A copies specific content/image(s)/URL and pastes it in a direct message to User B. User A is not sharing with an entire network of users (i.e., all of their Facebook friends or Twitter followers); it’s a direct share that is more predictive of both User A’s engagement with that content and his/her connection with User B.

Types of Data Sets Available

Interest and Intent Audience Segment User Profiles where 33Across identifies a more direct social sharing connection.

We have the ability to create custom segments based on client provided search keywords.