This document discusses forensic auditing of digital media using FouAnalytics. It describes analyzing discrepancies between bids won, ads served, and ads displayed. Drop-offs between these metrics indicate issues. The document also discusses evaluating accuracy of ad delivery in terms of location targeting, ad sizes, and frequency caps. Additionally, it covers analyzing when and where ads are served, including dayparting and reach across sites. Finally, the document examines ad quality factors like context, exposure to humans vs bots, and viewability.
This document provides a summary of digital ad fraud trends in Q1 2022. It discusses how ad fraud goes beyond just bots (IVT) to include other forms of fraud by sites and apps that are underreported. While industry associations only report on IVT rates around 1-3%, the document argues overall fraud rates are much higher. It also discusses the negative impacts of ad fraud on publishers, consumers, and advertisers. For publishers, it leads to lower revenues and CPMs. It also discusses how ad fraud has harmed local news organizations. For advertisers, it discusses examples like P&G and Chase cutting digital ad spend with no impact on performance. The document provides recommendations for publishers to sell direct inventory,
Desktop ad blocking rates on business sites range from 9-16% of traffic share, which is 50-70% of total traffic. Mobile business site ad blocking is much lower at 1-2% of their 30-50% traffic share. For consumer sites, desktop ad blocking is 3-10% of their 15-30% traffic, while mobile consumer site ad blocking is even lower at 0.8-1% with mobile traffic being 70-85% of total consumer traffic.
how the money flows from the advertisers through the ad tech intermediaries to longtail, fraud, and fake sites, with the help of botnets and traffic sellers
In 2021 some marketers are still asking whether ad fraud is real and whether it is pervasive. This serves as a simple reminder of some of the evidence collected over the years.
bad guys started with fake websites, then moved to loading ads only to save time and bandwidth; now they are simply faking bid requests and flooding exchanges
This document discusses forensic auditing of digital media using FouAnalytics. It describes analyzing discrepancies between bids won, ads served, and ads displayed. Drop-offs between these metrics indicate issues. The document also discusses evaluating accuracy of ad delivery in terms of location targeting, ad sizes, and frequency caps. Additionally, it covers analyzing when and where ads are served, including dayparting and reach across sites. Finally, the document examines ad quality factors like context, exposure to humans vs bots, and viewability.
This document provides a summary of digital ad fraud trends in Q1 2022. It discusses how ad fraud goes beyond just bots (IVT) to include other forms of fraud by sites and apps that are underreported. While industry associations only report on IVT rates around 1-3%, the document argues overall fraud rates are much higher. It also discusses the negative impacts of ad fraud on publishers, consumers, and advertisers. For publishers, it leads to lower revenues and CPMs. It also discusses how ad fraud has harmed local news organizations. For advertisers, it discusses examples like P&G and Chase cutting digital ad spend with no impact on performance. The document provides recommendations for publishers to sell direct inventory,
Desktop ad blocking rates on business sites range from 9-16% of traffic share, which is 50-70% of total traffic. Mobile business site ad blocking is much lower at 1-2% of their 30-50% traffic share. For consumer sites, desktop ad blocking is 3-10% of their 15-30% traffic, while mobile consumer site ad blocking is even lower at 0.8-1% with mobile traffic being 70-85% of total consumer traffic.
how the money flows from the advertisers through the ad tech intermediaries to longtail, fraud, and fake sites, with the help of botnets and traffic sellers
In 2021 some marketers are still asking whether ad fraud is real and whether it is pervasive. This serves as a simple reminder of some of the evidence collected over the years.
bad guys started with fake websites, then moved to loading ads only to save time and bandwidth; now they are simply faking bid requests and flooding exchanges
Previous studies that addressed the impact of losing third party (“3P”) cookies on ad revenue did not clearly differentiate between the impact on ad tech intermediaries versus on publishers. Instead of “advertiser CPMs” (what advertisers pay) this study uses “media CPMs” (what the publishers get) to better isolate the impact of tracking vs no tracking on publishers.
“In addition to the ad fraud itself, bad guys make money by selling the “picks and shovels” too – e.g. bots, traffic, clicks, malware, fake apps, etc. They have an entire ecosystem to extract value. What follows are just a few examples, scratching the surface.”
The original idea of the digital media trust collaborative is was sharing threat intelligence to more quickly remove fraudulent domains and apps from media buys.
most buyers who buy in programmatic channels think they are getting enormous "reach" -- i.e. their ads are shown on many sites; but this data shows the exact opposite is true. Their ads are being shown on a small number of sites (less than 1,000); the buyers might as well have bought more direct from good publishers.
digital ad fraud is as rampant as ever; new ripples caused by privacy regulations are starting to affect the market. and more BS from trade associations pretending to be doing something
U.S. smartphone browser share mirrors the mobile operating system market share, with Android users predominantly using Chrome and iOS users using Safari exclusively. On desktop computers, which are mostly Windows-based, Windows users primarily browse with Chrome. The majority of iOS device users have iOS 13 and Safari 13 installed, with only 6% using browsers other than Safari.
Using Google Analytics to find abnormal traffic and fraud; this is a how-to, to get hourly charts instead of daily rolled-up or averaged data, which hides the fraud.
This document provides an overview of the history and global impact of digital ad fraud. It discusses how fraudsters are able to generate infinite fake ad impressions through virtual ads rather than real billboards. The document outlines how major brands like Chase and P&G cut digital ad spending significantly without negative effects after removing fraudulent sites. It also examines how ad fraud has contributed to the decline of local journalism and thousands of newspaper closures. Throughout, it encourages analyzing your own analytics and reports to identify abnormal patterns that may indicate fraud.
from the IAB FY 2019 advertising revenue report, we show that CPM and CPC ads represent 92% of all digital spend; these are the favorite targets of fraudters
FouAnalytics is an alternative to Google Analytics, but with fraud and bot detection baked in. Marketers can use FouAnalytics to look at their own campaigns, find the domains and apps that are eating up their budgets fraudulently, and turn them off, while the campaign is still running. How does that compare to your blackbox fraud detection that just gives you a percent IVT number?
FouAnalytics - site analytics and media analytics for practitioners to detect fraud and take action themselves - on-site tags and in-ad tags measure sites and ad impressions, respectively
Fraud filters were found to increase the rate of fraud when enabled across multiple browser types and ad exchanges, with costs 44-67% higher when using fraud filters. Simple blacklists of sites and apps were more effective at reducing fraud. Exchangewide win rates should typically be between 5-15%, and sites with win rates over 70% could be flagged for potential fraud.
When advertisers spend money on digital ads, only a small portion goes to the original creators of the content. The majority is kept by intermediaries like ad exchanges, traffic brokers, and media agencies. On average, only 15% of total spending on programmatic ads makes it to publishers, with the remaining 85% going to these middlemen in the form of fees and commissions.
The document compares marketing outcomes between a legacy whitelist of publisher sites and a new hand-picked whitelist. It found that the new whitelist achieved a 70% increase in marketing efficiency as measured by conversions per click. Additionally, the new whitelist resulted in both higher eCPM prices for publishers and better marketing results for advertisers in the form of lower cost per start.
The document discusses the issues caused by "badtech" in digital advertising, including how it has harmed local news publishers and stolen ad revenue. Fake local news sites committed ad fraud for years by tricking users and advertisers. Several case studies show large brands like P&G, Chase, and Uber cutting digital ad spending by 80-99% with no negative impact on performance, indicating much of their previous spending was wasted on fraudulent sites and bots. The document argues for advertisers to buy directly from good publishers who have real human audiences, rather than through ad exchanges, to avoid issues like ad fraud, privacy violations, and most of the marketing budget being extracted as fees rather than going to media. Good publishers are identified by
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
What is an RPA CoE? Session 2 – CoE RolesDianaGray10
In this session, we will review the players involved in the CoE and how each role impacts opportunities.
Topics covered:
• What roles are essential?
• What place in the automation journey does each role play?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
More Related Content
More from Dr. Augustine Fou - Independent Ad Fraud Researcher
Previous studies that addressed the impact of losing third party (“3P”) cookies on ad revenue did not clearly differentiate between the impact on ad tech intermediaries versus on publishers. Instead of “advertiser CPMs” (what advertisers pay) this study uses “media CPMs” (what the publishers get) to better isolate the impact of tracking vs no tracking on publishers.
“In addition to the ad fraud itself, bad guys make money by selling the “picks and shovels” too – e.g. bots, traffic, clicks, malware, fake apps, etc. They have an entire ecosystem to extract value. What follows are just a few examples, scratching the surface.”
The original idea of the digital media trust collaborative is was sharing threat intelligence to more quickly remove fraudulent domains and apps from media buys.
most buyers who buy in programmatic channels think they are getting enormous "reach" -- i.e. their ads are shown on many sites; but this data shows the exact opposite is true. Their ads are being shown on a small number of sites (less than 1,000); the buyers might as well have bought more direct from good publishers.
digital ad fraud is as rampant as ever; new ripples caused by privacy regulations are starting to affect the market. and more BS from trade associations pretending to be doing something
U.S. smartphone browser share mirrors the mobile operating system market share, with Android users predominantly using Chrome and iOS users using Safari exclusively. On desktop computers, which are mostly Windows-based, Windows users primarily browse with Chrome. The majority of iOS device users have iOS 13 and Safari 13 installed, with only 6% using browsers other than Safari.
Using Google Analytics to find abnormal traffic and fraud; this is a how-to, to get hourly charts instead of daily rolled-up or averaged data, which hides the fraud.
This document provides an overview of the history and global impact of digital ad fraud. It discusses how fraudsters are able to generate infinite fake ad impressions through virtual ads rather than real billboards. The document outlines how major brands like Chase and P&G cut digital ad spending significantly without negative effects after removing fraudulent sites. It also examines how ad fraud has contributed to the decline of local journalism and thousands of newspaper closures. Throughout, it encourages analyzing your own analytics and reports to identify abnormal patterns that may indicate fraud.
from the IAB FY 2019 advertising revenue report, we show that CPM and CPC ads represent 92% of all digital spend; these are the favorite targets of fraudters
FouAnalytics is an alternative to Google Analytics, but with fraud and bot detection baked in. Marketers can use FouAnalytics to look at their own campaigns, find the domains and apps that are eating up their budgets fraudulently, and turn them off, while the campaign is still running. How does that compare to your blackbox fraud detection that just gives you a percent IVT number?
FouAnalytics - site analytics and media analytics for practitioners to detect fraud and take action themselves - on-site tags and in-ad tags measure sites and ad impressions, respectively
Fraud filters were found to increase the rate of fraud when enabled across multiple browser types and ad exchanges, with costs 44-67% higher when using fraud filters. Simple blacklists of sites and apps were more effective at reducing fraud. Exchangewide win rates should typically be between 5-15%, and sites with win rates over 70% could be flagged for potential fraud.
When advertisers spend money on digital ads, only a small portion goes to the original creators of the content. The majority is kept by intermediaries like ad exchanges, traffic brokers, and media agencies. On average, only 15% of total spending on programmatic ads makes it to publishers, with the remaining 85% going to these middlemen in the form of fees and commissions.
The document compares marketing outcomes between a legacy whitelist of publisher sites and a new hand-picked whitelist. It found that the new whitelist achieved a 70% increase in marketing efficiency as measured by conversions per click. Additionally, the new whitelist resulted in both higher eCPM prices for publishers and better marketing results for advertisers in the form of lower cost per start.
The document discusses the issues caused by "badtech" in digital advertising, including how it has harmed local news publishers and stolen ad revenue. Fake local news sites committed ad fraud for years by tricking users and advertisers. Several case studies show large brands like P&G, Chase, and Uber cutting digital ad spending by 80-99% with no negative impact on performance, indicating much of their previous spending was wasted on fraudulent sites and bots. The document argues for advertisers to buy directly from good publishers who have real human audiences, rather than through ad exchanges, to avoid issues like ad fraud, privacy violations, and most of the marketing budget being extracted as fees rather than going to media. Good publishers are identified by
More from Dr. Augustine Fou - Independent Ad Fraud Researcher (20)
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These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
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Topics covered:
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Getting the Most Out of ScyllaDB Monitoring: ShareChat's TipsScyllaDB
ScyllaDB monitoring provides a lot of useful information. But sometimes it’s not easy to find the root of the problem if something is wrong or even estimate the remaining capacity by the load on the cluster. This talk shares our team's practical tips on: 1) How to find the root of the problem by metrics if ScyllaDB is slow 2) How to interpret the load and plan capacity for the future 3) Compaction strategies and how to choose the right one 4) Important metrics which aren’t available in the default monitoring setup.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
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What is an RPA CoE? Session 1 – CoE VisionDianaGray10
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Introducing BoxLang : A new JVM language for productivity and modularity!Ortus Solutions, Corp
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Dynamic. Modular. Productive.
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Interoperability at its Core
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Multi-Runtime
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👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
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The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
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LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...DanBrown980551
This LF Energy webinar took place June 20, 2024. It featured:
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-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
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-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
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2. In Layman’s Terms
“I’ve been asked by many clients about the Google algorithm
changes that have happened over the last few years. This is a
deliberately oversimplified explanation of what the major
changes consisted of. For a more detailed and technical
explanation, I will point you to my colleague, Glenn Gabe’s
blog and articles (see links below).”
-- Augustine Fou
http://www.hmtweb.com/marketing-blog/
http://searchenginewatch.com/author/2623/glenn-gabe
-2-
Augustine Fou
3. Panda - 2011
“A major algorithm update hit sites hard,
affecting up to 12% of search results (a
number that came directly from Google).
Panda seemed to crack down on thin
content, content farms, sites with high
ad-to-content ratios, and a number of
other quality issues. Panda rolled out
over at least a couple of months, hitting
Europe in April 2011.”
Source: http://moz.com/google-algorithm-change
-3-
Augustine Fou
4. Penguin - 2012
“After weeks of speculation about an
"Over-optimization penalty", Google
finally rolled out the "Webspam
Update", which was soon after dubbed
"Penguin." Penguin adjusted a number
of spam factors, including keyword
stuffing, and impacted an estimated
3.1% of English queries.”
Source: http://moz.com/google-algorithm-change
-4-
Augustine Fou
5. Hummingbird - 2013
“Announced on September 26th, Google
suggested that the "Hummingbird" update
rolled out about a month earlier.
Hummingbird has been compared to
Caffeine, and seems to be a core algorithm
update that may power changes to
semantic search, [natural language
queries], and the Knowledge Graph for
months to come.”
Source: http://moz.com/google-algorithm-change
-5-
Augustine Fou
6. Related Articles
Impact of Google Encrypted Search
By: Augustine Fou, October 2013
Google PLA vs Text Search
By: Augustine Fou, September 2013
Display Ad vs Search Benchmarks
By: Augustine Fou, August 2013
Benchmarking Organic Search vs Paid Search
By: Augustine Fou, August 2013
Mobile Search vs Display Benchmarks
By: Augustine Fou, July 2013
-6-
Augustine Fou
7. Dr. Augustine Fou – Digital Consigliere
“I advise clients on optimizing advertising
across all channels. One main area of focus
is reducing ad waste due to fraud – fake
impressions, clicks, leads, and sales. Another
area is improving effectiveness. This is rooted
in an understanding of how search works.”
FORMER CHIEF DIGITAL OFFICER, HCG (OMNICOM)
MCKINSEY CONSULTANT
CLIENT SIDE / AGENCY SIDE EXPERIENCE
PROFESSOR AND COLUMNIST
ENTREPRENEUR / SMALL BUSINESS OWNER
PHD MATERIALS SCIENCE (MIT '95) AT AGE 23
ClickZ Articles: http://bit.ly/augustine-fou-clickz
Slideshares: http://bit.ly/augustine-fou-slideshares
LinkedIn: http://linkd.in/augustinefou
-7-
@acfou
Augustine Fou