Programmatic geotargeting is accurate to the DMA level. But because the geolocations are approximated from the IP addresses (rather than taken from real GPS data), they are less accurate and appear as a "freckles" pattern on the map. This is fine for certain types of marketing (targeting the DMA level) but may have enough precision for other forms of marketing.
Remember the Milk: Location-based Apps and the MarketplaceAmber Case
Slides from a speech to the Software Association of Oregon on November 10, 2010 at the Multnomah Athletic Club.
---
There’s a message from your future and it’s telling you to remember to pick up milk.
What will you learn:
1. Why developers of apps should look at what users want to do now, as well as what users want to do in their future.
2. Why social apps should try to mirror real–world relationships
3. Why sharing should be about who you share with as well as how long you want the information to be available.
4. Why developers should think about making apps "ambient” and require less user interaction
Amber Case and her partner Aaron Parecki are the founders of GeoLoqi. GeoLoqi is a private, real-time mobile and web platform for secure location data, with features such as Geonotes, proximal notification, and sharing real-time GPS maps with friends. Geoloqi has been covered in the Willamette Week and Oregon Business. It has been presented at eComm, Open Source Bridge, Show and Tell PDX and Research Club under the alias Non-Visual Augmented Reality with SMS and GPS.
This study was to test whether there were more bots at higher CPM prices. There were, but not significantly more. But there were much more bots at the very low price points of < 50 cent CPMs
Planning Liveable Cities With Big Social DataMatt Low
Big social data – data collected from online social networks such as Twitter, Facebook, Foursquare and Yelp – can provide new insights into the dynamics of cities. Billions of data points can be harvested to understand how people move around the city and how they experience the urban environment. Deeper, real-time urban insights provide the evidence base for planning more liveable cities – building more responsive transport systems, developing unique neighbourhood identities, and designing more attractive places.
These new data sets are especially useful for addressing gaps within the urban planner’s
toolbox. Firstly, while the pace of change in cities accelerates, conventional data sets (such as Census data or surveys) are updated infrequently. Secondly, there is limited data about the invisible dimensions of cities – sentiment, movement, and social networks.
Andra Keay
Silicon Valley Robotics
Overview
Forget worrying about killer robots and robots stealing our jobs! What will a world of robot smog, spam and stereotypes look like? How network effects and algorithms can turn useful robots into social problems. And what we can do about that right now!
Objective
Explore the possible error modes of ubiquitous robotics.
Programmatic geotargeting is accurate to the DMA level. But because the geolocations are approximated from the IP addresses (rather than taken from real GPS data), they are less accurate and appear as a "freckles" pattern on the map. This is fine for certain types of marketing (targeting the DMA level) but may have enough precision for other forms of marketing.
Remember the Milk: Location-based Apps and the MarketplaceAmber Case
Slides from a speech to the Software Association of Oregon on November 10, 2010 at the Multnomah Athletic Club.
---
There’s a message from your future and it’s telling you to remember to pick up milk.
What will you learn:
1. Why developers of apps should look at what users want to do now, as well as what users want to do in their future.
2. Why social apps should try to mirror real–world relationships
3. Why sharing should be about who you share with as well as how long you want the information to be available.
4. Why developers should think about making apps "ambient” and require less user interaction
Amber Case and her partner Aaron Parecki are the founders of GeoLoqi. GeoLoqi is a private, real-time mobile and web platform for secure location data, with features such as Geonotes, proximal notification, and sharing real-time GPS maps with friends. Geoloqi has been covered in the Willamette Week and Oregon Business. It has been presented at eComm, Open Source Bridge, Show and Tell PDX and Research Club under the alias Non-Visual Augmented Reality with SMS and GPS.
This study was to test whether there were more bots at higher CPM prices. There were, but not significantly more. But there were much more bots at the very low price points of < 50 cent CPMs
Planning Liveable Cities With Big Social DataMatt Low
Big social data – data collected from online social networks such as Twitter, Facebook, Foursquare and Yelp – can provide new insights into the dynamics of cities. Billions of data points can be harvested to understand how people move around the city and how they experience the urban environment. Deeper, real-time urban insights provide the evidence base for planning more liveable cities – building more responsive transport systems, developing unique neighbourhood identities, and designing more attractive places.
These new data sets are especially useful for addressing gaps within the urban planner’s
toolbox. Firstly, while the pace of change in cities accelerates, conventional data sets (such as Census data or surveys) are updated infrequently. Secondly, there is limited data about the invisible dimensions of cities – sentiment, movement, and social networks.
Andra Keay
Silicon Valley Robotics
Overview
Forget worrying about killer robots and robots stealing our jobs! What will a world of robot smog, spam and stereotypes look like? How network effects and algorithms can turn useful robots into social problems. And what we can do about that right now!
Objective
Explore the possible error modes of ubiquitous robotics.
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
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
More from Dr. Augustine Fou - Independent Ad Fraud Researcher (20)
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
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
The affect of service quality and online reviews on customer loyalty in the E...
Bots vs Humans on a Map
1. September 2017 / Page 0marketing.scienceconsulting group, inc.
linkedin.com/in/augustinefou
Bots vs Humans On A Map
Marketing Science and advanced analytics expert Peter Zajonc studied the geographic
distribution of human and bot segments. Overall, the geographical distribution of bot
segments mirrored the geolocations of human segments well. But, when advanced bots
are distinguished from less advanced bots, it is clear that the more sophisticated bots
also 1) disguised or randomized their geolocations, or 2) are made from malware on
actual humans’ PCs, which corroborates previous findings from other fraud researchers.
Humans (blue) vs Bots (red) – not much visual difference in geographic distribution
Less sophisticated bots – these bots
did not disguise their geolocations to
appear to be from residential IPs. So
this map shows locations that are
more sparse and concentrated in
cities that are known to have large
data centers or colocation facilities.
Humans (blue) vs Bots (red) – closeups show humans are mainly in metropolitan areas,
while some bots are observed in unpopulated areas outside of cities.