The latest LUMA Display Ad Tech Landscape is a living document. While it is impossible to categorize companies across an industry into discrete categories, this is at least an attempt to organize the landscape. If you have constructive suggestions, please email them to me at tkawaja@lumapartners.com.
You all knew this, right? The adage "you get what you pay for" never held more than it does in digital media. Buying low CPM impressions doesn't save you money if you spend the same budget. Buying better media so your ads are shown to humans leads to better outcomes. And notice the conversions are done by humans.
The latest LUMA Display Ad Tech Landscape is a living document. While it is impossible to categorize companies across an industry into discrete categories, this is at least an attempt to organize the landscape. If you have constructive suggestions, please email them to me at tkawaja@lumapartners.com.
You all knew this, right? The adage "you get what you pay for" never held more than it does in digital media. Buying low CPM impressions doesn't save you money if you spend the same budget. Buying better media so your ads are shown to humans leads to better outcomes. And notice the conversions are done by humans.
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
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.
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
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
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More from Dr. Augustine Fou - Independent Ad Fraud Researcher
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
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.
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
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...2023240532
Quantitative data Analysis
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Reliability Analysis (Cronbach Alpha)
Common Method Bias (Harman Single Factor Test)
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06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).