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6 Results - IPQualityScore (IPQS) profile banner
IPQualityScore (IPQS)
Based in USA
IPQualityScore (IPQS)
IPQualityScore (IPQS) provides enterprise level fraud prevention, user validation, and data hygiene. Score user, lead, & payment data in any country with ...
100% Compliant
Fresh Data
Access New, Accurate Data
API Access
100% Uptime - Transparent Data profile banner
Transparent Data
Based in Poland
Transparent Data
From tech-driven company data solutions to API creation, legacy systems rescue & integrations - Transparent Data acquires and integrates data about companies... - Fraudlogix profile banner
Based in USA
Fraudlogix helps the world’s largest advertising exchanges and networks prevent digital ad fraud through longstanding partnerships and integrations. We speci...
1 Billion
Unique Users Monitored
300+ M
URLs and APPs Tracked
Internet Population Monthly - Interceptd profile banner
Based in USA
Interceptd is your ingenious defence against mobile ad fraud to let you identify the best channels to spend your money, shield and protect your marketing dat...

The Ultimate Guide to Ad Fraud Data 2021

Learn about ad fraud data analytics, sources, and collection.

What is Ad Fraud Data?

In the digital advertising ecosystem, not all ads reach the intended audience. This is brought about by ad fraud which is a deliberate activity that is initiated by fraudsters to prevent the proper delivery of ads to the intended audience. In most cases, ad frauds take the form of bots or domain spoofing, hence thriving via siphoning off funds from advertising transactions that are meant for a real audience. Thus, data on ad fraud is collected to keep track of the trends in digital ad frauds and inform users on how best to navigate around and avoid unfortunate activity that may lead to loss of money and reduced value in advertising initiatives for businesses.

How is Ad Fraud Data collected?

The collection of ad fraud data is largely an online-based activity that is initiated and accomplished by several online tools designed to detect and prevent ad fraud. These tools are advanced algorithms that are designed to detect, mitigate, and report on digital ad fraud before it makes its way to an advertiser’s budget. These tools work in such a way that they evaluate impressions, clicks, conversions, and events hence offering proactive approaches that assist advertisers to scale and optimize their marketing activities without having to worry about being swindled online. Some of the ad fraud data collection tools are also designed to allow marketers and brands to analyze traffic in real-time and do post-processing of traffic’s validity hence detecting any form of ad fraud.

What are the attributes of Ad Fraud Data?

Ad fraud data is made up of key components that identify the main aesthetic attributes of digital fraud. Some of the attributes of ad fraud that are identified in this data include:
• Bots – these are software that is deliberately designed to view ads, watch videos, click on online ads that are used as a tactic to siphon money from advertising transactions.
• Domain spoofing – refers to the process through which swindlers fool ad buyers into believing their ads are being directed to premium sites while in reality, they are being directed to low-quality domain sites.
• Pixel stuffing and stacking – this is data that highlights a method in which fraudulent ad display contents that are not visible to the naked eye. This method is mainly used to hide ad keywords.
• Traffic fraud – traffic fraud mainly aims to inflate the number of impressions that are generated from individual sites or placements, by manipulating the network traffic.

What is Ad Fraud Data used for?

Ad fraud data is crucial information that largely helps marketers to reduce the impact of digital ad fraud. Guided by the information provided in ad fraud datasets concerning the transformation and development of ad fraud, marketers and companies can make notable developments towards the detection of ad fraud, helping them to prevent losses by employing several techniques that may include:

• Acquiring enough ad verification tools
• Monitor and block suspicious IPs spoofing through their websites
• Acquire anti-fraud software solutions and tools
• Employ ad fraud prevention tools that have incorporated machine learning capabilities.

How can a user assess the quality of Ad Fraud Data?

The quality of ad fraud data is grounded on the fact that online swindlers are evolving and finding new ways to navigate around ad fraud detection and prevention tools. When assessing the quality of this data, a user ought to consider the aspect of time in terms of how and when was the data collected. Old data on ad fraud may prove to be obsolete in the sense that it may not capture the actual transformation and advancement of methods through which online ad swindlers are currently employing to advance their objectives of defrauding marketers and companies.

Who are the best Ad Fraud Data providers?

Finding the right Ad Fraud Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Ad Fraud Data providers that you might want to buy Ad Fraud Data from are IPQualityScore (IPQS), Transparent Data, Fraudlogix, and Interceptd.

Where can I buy Ad Fraud Data?

Data providers and vendors listed on Datarade sell Ad Fraud Data products and samples. Popular Ad Fraud Data products and datasets available on our platform are Ad Blocker User Blocklist Feed by Fraudlogix under-performing audience intelligence by Fraudlogix, Ad Fraud Prevention for USA based on Deterministic & Probabilistic Data - Interceptd by Interceptd, and IP Address Reputation & Intelligence by IPQualityScore (IPQS).

How can I get Ad Fraud Data?

You can get Ad Fraud Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Ad Fraud Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Ad Fraud Data APIs, feeds and streams to download the most up-to-date intelligence.

What are the most common use cases for Ad Fraud Data?

The top use cases for Ad Fraud Data are Risk Management, Fraud Prevention, and Digital Advertising.