Real-World
Data Enrichment
CREATE FREE ACCOUNT

Get your
first-party
data enriched
in real time
Universe
1.6 billion users across
44 countries
360° Understanding of Your Consumers
CARBON™ allows you to select data attributes from the Near universe that best suits your use case, such as brand affinity, home location, dwell time, distance traveled and multiple other real-world attributes.Get answers to critical business questions vis-à-vis your customers now.
- <script src="https://pixel.zprk.io/v4/1/2/abcdef.js?
- "></script>
- import AdSupport
- ...
- // Check if "Limit Ad Tracking" is Enabled
- if ASIdentifierManager.sharedManager().advertisingTrackingEnabled {
- // use the IDFA
- myIDFA = ASIdentifierManager.sharedManager().advertisingIdentifier.UUIDString
- }
- else {
- // use a random UUID
- myIDFA = NSUUID().UUIDString
- }
Setup in minutes
Copy and paste a simple piece of code
we call the CARBON™ Pixel on your website/app. You’re done!
Designed to work with your organization,
Choose how you want to access your enriched data
File Sync
Daily batch output in simple CSV posted to secure cloud storage.
In Platform
Get the enriched data exported to an external platform.
API
Use our secure API to consume the enriched data, as you like it.
PRIVACY-LED DATA ENRICHMENT™
Near takes privacy very seriously. From inception the Near Platform has followed a privacy-led design. As a result, the Platform never stores or deals with PII (Personally Identifiable Information) and all incoming data streams are consensual. The Near Platform has built-in processes to forget and purge user data on request as well. The Platform is GDPR compliant.
From the time you signup, a secure private setup is created safeguarding all your data in its own instance. Stored and enriched data are hashed and requires a private key to unhash.
See for yourself why this among other privacy safeguards make Near so enterprise friendly.
Privacy PolicyTechnologies powering CARBON™
Near’s proprietary technologies, built using advanced machine learning techniques and algorithms, bring context to our large scale datasets on people and places.