Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Scalarr offers a cutting-edge solution for mobile ad fraud detection through advanced Machine Learning technology. To combat the most significant threats in mobile advertising, Scalarr employs a dual-layered approach with next-generation algorithms that achieve an impressive accuracy rate of up to 97% in identifying various forms of in-app fraud. Users can experience the benefits of Scalarr by exploring its capabilities to overview, analyze, and thwart mobile app install ad fraud using its unsupervised machine learning features before any harm occurs. The platform utilizes both unsupervised and semi-supervised machine learning techniques to automatically spot and understand fraud patterns across vast datasets. By examining countless clicks, installs, and post-install event variables, Scalarr significantly minimizes both false positives and false negatives in its detection process. With a sophisticated model design prioritizing result accuracy and thoroughness, Scalarr stands out as a robust tool that provides actionable insights at the individual conversion level, ensuring advertisers can make informed decisions regarding their ad campaigns. This comprehensive approach ultimately enhances the overall integrity of mobile advertising strategies.
Description
In-app bot fraud is increasingly jeopardizing your business, with the mobile ecosystem grappling with rampant automated bots that inflict significant damage on applications. Various types of apps are vulnerable to having their entire user experience commandeered for deceptive objectives; for instance, gaming applications can see their in-game economies destabilized, while e-commerce platforms may face severe breaches of financial data. The evolution of bots has led to the emergence of highly sophisticated variants capable of mimicking genuine user behavior with remarkable precision, enabling them to bypass conventional detection techniques. Armed with these advanced bots, fraudsters can disrupt user experiences and negatively impact retention through automated gameplay, account hijacking, credit card fraud, spam, and other abusive practices. In response to this growing threat, Unbotify has developed the first patented machine learning solution designed to distinguish between authentic users and bots. Our state-of-the-art technology leverages an in-depth comprehension of human behavior patterns to effectively identify and eliminate sophisticated bot fraud that might otherwise evade notice, all while maintaining an impressively low false-positive rate. This innovative approach not only protects app integrity but also enhances user trust and engagement.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Adjust
Yes
AppsFlyer
Yes
Beaver Builder
No
Branch
Yes
Kochava
Yes
Singular
Yes
Tenjin
Yes
mParticle
Yes
Integrations
Adjust
No
AppsFlyer
No
Beaver Builder
Yes
Branch
No
Kochava
No
Singular
No
Tenjin
No
mParticle
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Scalarr
Founded
2016
Country
United States
Website
scalarr.io
Vendor Details
Company Name
Adjust
Founded
2012
Country
Germany
Website
www.adjust.com/product/unbotify/
Product Features
Click Fraud
Account Alerts
No
Activity Monitoring
No
IP Address Monitoring
No
IP Blocking
No
Keyword Tracking
No
Refund Management
No
Risk Assessment
No
Time on Site Tracking
No