This document provides guidance on using YouTube, blogging, and LinkedIn for marketing purposes. It discusses creating how-to, behind-the-scenes, and professional videos for a YouTube channel. It also recommends customizing the channel, adding playlists and engaging with other users. For blogging, it suggests topics related to HVAC and employees and maintaining consistency. Finally, it outlines building a complete LinkedIn profile by filling out sections, adding connections, and getting recommendations.
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 provides guidance on using YouTube, blogging, and LinkedIn for marketing purposes. It discusses creating how-to, behind-the-scenes, and professional videos for a YouTube channel. It also recommends customizing the channel, adding playlists and engaging with other users. For blogging, it suggests topics related to HVAC and employees and maintaining consistency. Finally, it outlines building a complete LinkedIn profile by filling out sections, adding connections, and getting recommendations.
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.
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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.
More from Dr. Augustine Fou - Independent Ad Fraud Researcher (20)