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}AdWords, AdSense, AdMob
&
DoubleClick
INTERNET MONETIZATION}Ali Kamran Maken
August, 2014
Contents
1 AdWords 3
2 AdSense 12
3 AdMob 20
4 DoubleClick 29
1 AdWords
Figure 1: Google AdWords Logo.
1.1 Description
The general structure of an account is described using the following picture:
Figure 2: Google Adwords account structure.
The structure consists of an adwords account. For each website the advertiser owns, it is
recommended to create a separate account. Although it is possible to maintain multiple websites
in the same account, but there is no grouping on campaigns per website, so the advertiser has
to keep track of which campaigns belong to which site.
1.1.1 Account
The account is the highest level on Google Adwords interface. At this level the advertiser can
configure options that will be applicable to all the sub levels of this account. The configuration
options available to the advertiser are as follows:
1. Access
The account can be shared among multiple users. And the access level can be set to read-
only or full access etc. The “Account Access” section of the AdWords interface will allow
the advertiser to invite new users. Once an invitation has been accepted, the advertiser
have to grant access to the user by visiting again the “Account Access” section.
2. Billing Information
The overall due payments and transactions to and fro the account can be seen in this
section.
3. Notifications
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General notifications, messages and suggestions from Google AdWords team can be found
in this section.
4. General Preferences
This section contains the general preference settings that will be applied to the entire
account.
1.1.2 Campaigns
In an AdWords account the advertiser can create up to 10,000 campaigns. A campaign is
targeted at a specific scenario and situation of advertisement. For example to target the on going
sale in your store, you can create a specific campaign to cater this need.
A campaign contains many parameters that can be set per the need of the advertiser. Fol-
lowing are the di↵erent properties that can be set in a campaign:
• Networks
This section allows to chose the specific ad networks you want to this campaign to run on.
• Budgets
The advertiser can set daily budgets. So the ads will be served until the budget is available
and once the budget is over the ads will cease to display, to avoid over charging.
• Languages
This defines the targeted language for the ads. If you are selling something in Italy, the
language would be Italian in the case. An ad in English will not be able to capture large
population in this case.
• Locations
Many times the ads are displaying the on site o↵ers and store names. This information is
most useful in the vicinity of the physical location of the site and store. So the advertiser
can limit the ads to be displayed only if the user is coming from that area or location.
• Schedules
If the ad is showing some information which is only valid for a time period or a season.
Then the schedule can be setup so that the ad is only served in that schedule and after the
schedule gets over the ads cease to display.
1.1.3 Ad Groups
Each campaign can contain up to 20,000 ads in the form of ad groups. Ad groups are groups
of ads with similar properties, targets and features. The ads can be created of one of the following
types:
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• Textual
Ads made up of standard text. Consisting of up to 4 lines. These are suitable and the only
allowed option for ads displayed along search engine results.
• Graphical
The ads other than text ads can be divided in to following subcategories as follows:
– Image Ads
Ads made up of static images.
– Video Ads
Animating ads made up of videos or GIFs.
– Rich Media Ads
Ads with which the user can interact, by hovering the mouse and clicking on the ad
to get more information without leaving the current page, he is viewing. These ads
can extend out of the standard boundary of the ad units.
1.1.4 Keywords
In each Ad Group the advertiser can ad millions of keywords. These keywords will be matched
according to the preferences set by the advertiser and will decide whether a specific ad is targeted
to the current web page being displayed to the user.
1.1.5 Display Targets
Other than targeting unknown and new users, the advertisers can target users who fall in to
specific categories based on their actions in the past. For example if a user have registered on
the website and downloaded a brochure of a product but haven’t bought it. That user can be
specifically targeted for new promotions about that product.
1.1.6 Opportunities
A section dedicated to optimization guidelines and tips generated by AdWords team based
on the current setup of campaigns and ad groups. It is a good place to visit often to keep the
things optimized for maximum return of investment (ROI).
1.1.7 Conversions
Suppose a user clicks on an ad placed on the a web page and the click leads him to the website
of the advertiser. If the user performs an action which leads to achieve a goal of the advertiser,
then that is known as a conversion. For most websites the conversions could be:
• Online purchase
• Lead generation
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• Newsletter subscription
• Contact form or call
Other type of uncommon but useful conversions could be:
• Social follow ups
• File downloads
• Promotional video views
• Coupon downloads
• Getting driving directions
These conversions need to be tracked by the advertiser by managing success pages and actions
so that it would be automated to calculate the monetary impact of the marketing campaign.
1.2 Auctioning Functions
Google want to make sure that the ads that are displayed to the user must have a high ad
quality. This benefits the user and also ensure that the advertisers maintain a certain level of
quality in their ads and landing pages. So that is why the auction doesn’t solely depends on the
biding price, but a combination of the bid price with the ad quality.
1.2.1 Quality Score
The ad quality is measured as quality score. There are three components of quality score:
1. CTR
Google checks that which ads are best for the current query by the user.
2. Relevance
Google makes it sure that the user is only displayed with the relevant ad to the keywords
as well as the user query.
3. Landing Page
An ad is only useful if landing page allows them to find the information the user is looking
for. The page must be quick to load. Minimum pop-ups should be placed on this page.
This page must also clearly state the nature of the information collected from the user and
its use by the company in case.
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Figure 3: Ad Quality Score
1.2.2 Ad Rank
Ad Rank is the bid of the advertiser multiplied by the quality score that the ad gets.
max bid ⇥ quality score = ad rank
Below is an example of a bid for top 3 slots. The placement is calculated by arranging the
ad rank in descending order.
Advertiser Max Bid Quality Score Ad Rank Position
1 $ 4.00 1 4 -
2 $ 3.00 3 9 2
3 $ 2.00 6 12 1
4 $ 1.00 8 8 3
Table 1: Sample Ad Rank calculation
1.2.3 Determining Click Cost
Finally in order to calculate the amount payable by the advertiser if the user clicks on his ad
is determined by the following formula:
Let P1 be the amount payable by advertiser who won the auction.
Let Q1 be the quality score of the advertiser who won the auction.
Let B2 be the bid amount of advertiser who was second best.
Let Q2 be the quality score of advertiser who was second best.
P1 ·Q1 =B2 ·Q2 (1)
P1 =B2 ·Q2
Q1(2)
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Using the second best bid price as the amount payable, makes the advertiser happy as well
as gives the incentive of getting high quality score that will provide users with quality advertise-
ments.
In this scenario and according to the equation described before. If an advertiser improves his
quality score, then he will have to pay even less than what he was paying before. This gives a
great incentive to advertiser to improve there quality score.
1.3 Parameters
1.3.1 Keyword match types
1. Broad
Default based on relevance to the user queries Increases reach, similar words, plural worlds,
synonyms Increase the ad tra�c so must be done carefully
Broad match modifier : Using a “+” sign with a part of the keyword. example: “+Ath-
letic Shoes”. specifies a part of query to be present in the query or must be very close to
the one that the user has typed in. The order of the words in the keyword phrase doesn’t
matter.
2. Phrase
Restricts tra�c even further as compared to the broad match. Order of the keyword phrase
must match the order by which the user query is done. The phrase match can be done by
part of the user query. So a phrase could be in the start, middle or at the end of the user
query. Exact phrase must exist somewhere in the user search terms. The keyword must be
specified by using (“ ”) sign at both ends. For example “athletic shoes”.
3. Exact
To be more specific. Our allowed ad will show only if the user query matches exactly with
the keyword we have specified. This can be specified by using ([]) square brackets around
the keywords. For example [athletic shoes]. Exact order must match and no other words
must be in the user’s query.
4. Negative
This match modifier helps to reduce the unwanted extra tra�c in case the user was search-
ing for something else and some words of his query matches one of our keywords. For
example “paris hilton” query doesn’t meant to get to the business which is Hilton hotels
in Paris. By defining a negative match modifier you can avoid extra useless tra�c to the
account. This helps in increasing the relevance of the tra�c of our ads. The keyword must
be specified by a “-” sign with the keyword.
Negative keywords can be maintained on all levels including account level, campaign level
and eventually on ad groups level. This is because most often the negative keywords are
required to be reused in many campaigns.
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1.3.2 Evaluating Keywords
1. Frequency
How often the people are typing in to Google when searching. This is important because
we want to bid on the keywords that people actually search for. Similarly if you bid on the
keyword that is searched too often, then the tra�c will be too generic and may get extra
and irrelevant ad tra�c. This often happens when you use a single word keyword. The
keyword become too generic and it is hard to get any real relevant ad tra�c.
2. Relevance
(a) Advertising Goals
(b) Ads
(c) Landing pages of ads
(d) Products or services that you o↵er The keywords should try to describe the exact
service you provide. Instead of using “roses” as a keyword, it is better to use “buy
roses online”.
3. Competition
You are competing in an auction for your keywords so the popular terms will have a higher
price as compared to the terms that nobody uses. So you have to create a balance between
bidding for popular terms and the unpopular terms.
1.3.3 Longtail keywords
Specify keywords that are extremely likely to end up on your site. This includes specifying
long phrases as keywords which exactly describes the products and services you provide. This
keyword may not be matched quite often but when matched will surely lead to your website. So
the point is to create many of such variants of keywords.
1.4 Analytics
1.4.1 Dashboard
After setting up and the account and filling up a few campaigns, ad groups and keywords, the
homepage of AdWords interface will start showing a lot of overview details about the account
and its performance. The interface is built in such a way that it can be customized in any way
desired. Elements can be added and removed from the interface quite easily. This gives a quick
overview of the entire account, once the advertiser logs in.
1.4.2 Overview plots
The homepage dashboard contains many overview plots to visualize the data in a nice and
quickly understandable way. Few of the overview elements that are displayed on the home page
dashboard are as follows
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• Clicks
• Impressions
• CTR
• Avg. CPC
• Avg. CPM
• Cost
• Avg. Pos.
1.4.3 Detailed performance metrics
Once the data starts pooling up, the advertiser can see the detailed performance metrics in
the Campaigns section of the interface. This data can be drilled down to ad groups as well as
keywords level. So the advertiser can know what combinations of targeted user and keywords
are giving the most ROAS.
1.4.4 Google Analytics
Google has made it possible to share the performance data among its multiple platforms. So
the advertiser can see the detailed data and perform further analysis by connecting his Google
Analytics account with Google AdWords account.
1.5 Tools provided
1.5.1 Data Exporting
The data can be exported in many formats to support further and o✏ine analysis. The
formats that are available are as follows:
• CSV
• XML
• PDF etc.
1.5.2 Filters
The metrics displayed in the interface are intuitively formated and visualized to give the
advertiser a complete picture of whats going on under the hood. Many filters are provided to
customize the data as per the requirements and needs of the advertiser. Following are few of the
filters that can be applied while analyzing the data:
• User Segment
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• Date Wise
• Network Wise
• Click type
• User Device
1.5.3 Conversion Tracker
This section allows the advertiser to generate a Java-script code snippet for every type of
conversion that is successfully happened on the website and the code will automatically update
the AdWords information base about the specific campaign, ad group or even a keyword that
lead to the successful conversion. This will help in measuring the Return of Ad Spending (ROAS)
and can be displayed in reports to analyze later on. This will also let the advertiser know which
keywords, ad groups and campaigns are more profitable as compared to others.
1.5.4 Keyword Planner
• Search for new keywords and ad group ideas: This place gives you ideas of keywords that
you may want to target. Suggestions for more tightly themed ad groups. You can also
specify the landing URL and Google will get suggestions from the page itself.
• Get search volume (frequency of search over time) for a list of keywords or group them into
ad groups: In case you already know the keywords and just want to group them together
in to a ad group.
• Get tra�c estimates for a list of keywords: Let’s you play with hypothetical bids and to
see what predicted impacts you will get.
• Multiply keyword lists to get new keyword ideas: Let’s you quickly combine existing key-
words to get new keywords.
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2 AdSense
Figure 4: Google AdSense Logo.
2.1 Description
AdSense is a wonderful tool if we want to monetize from the display advertising on our
websites.
“Display Advertising: Certain areas of a website or blog are reserved and sold to advertisers
to promote a particular product or service.”
Determining value is an important aspect in display advertising. Web add spots can be sold
in the following schemes:
1. Flat rate (monthly, quarterly, annually)
Depends on the preference of the website’s owner.
2. Cost per action (CPA)
Action an add receives from the user. e.g. Clicking on the add and then submitting email
address. This technique generally helps the advertiser more than the website’s owner.
3. Cost per click (CPC)
The advertiser pays the publisher a certain amount of money every time a user clicks on
their add on the publisher’s website.
4. Cost per thousand impressions (CPM)
An impression is simply when a user navigates to a website and sees an advertisement. If
a webpage has 3 add spot on one page. When a user navigates to this page it actually
creates 3 impressions for the website owner.
Figure 5: Impressions vs. Page views.
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This method of selling display adds tends to benefit the website’s owner then any other
display add selling techniques.
2.2 Auctioning Functions
Google AdSense automatically choses the highest paying advertisements to be displayed on
a particular website to maximize the revenue that a website owner can make.
The advertisements are placed by the Internet Ad Networks on the add spots that the website
owner creates.
“Internet Ad Network: Network of publishers earning revenue from ads displayed on their
website and advertisers paying for the displayed ads.”
2.2.1 Bidding Process
Advertisers will chose the ”keywords”, ”categories” and ”topics” of websites on which their
adds are to be displayed on and on the same time they also specify the maximum bid price they
are willing to pay for their add.
Google AdSense will compare the bids for a specific ad spot on the web page. Among all the
advertisers that are bidding on the ad position. The one that has the highest bid price will win
the bidding contest and their adds will be displayed in that specific ad spot.
Google AdSense will make sure that the publisher earns the maximum amount of money
possible, by intelligently selecting the highest bidding ads. This process is done for every ad spot
on the webpage.
Figure 6: Bidding Process.
2.2.2 Ad Network’s share
Every ad network takes a cut out of the earnings of the publisher. But generally speaking
the amount that it takes is less than the expenses the publisher would incur if he goes out and
get ads manually.
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2.3 Parameters
2.3.1 Ad Units
There are many parameters that can be fine tuned in order to generate maximum revenue.
Described below are few of the items:
Google’s recommended Ad Units (Ad block sizes)
1. Large Rectangle (336 x 280)
2. Medium Rectangle (300 x 250)
3. Leader board (728 x 90) Works great on the top or the bottom of a page. Users are more
likely to see the ads which are at the top as compared to the ads which are on the bottom.
4. Wide Skyscraper (160 x 600) Wider then the standard skyscraper. Although taller ad units
are discouraged in favor of wider ad units. But this one is more wider and may be useful
on the free space on the margins of the webpage.
These recommendations are also known by the advertisers. So they might as well bid higher
on these ad units as compared to any other unusual sized ad spots on the page.
2.3.2 Custom Channels
Publishers can create custom channels comprising multiple ad units from their webpages.
This allows them to track the combined performance of group of ad units. Individual ad units
can also be tracked, but sometimes it is more useful to track a group of ads altogether to see any
impact on the overall revenue of sub domains or specific topics of your website.
A custom channel can be created by going to the “My ads ) Custom Channels” section of
the Google AdSense interface and clicking ”New ad unit” button.
2.3.3 URL Channels
Similar to custom channels which deals with ad units and their groups. The URL channels
allows the publisher to track group of up to 500 URLs of their websites.This helps in finding out
what content is attracting most users and generating more revenue as compared to the other
content of the same website. This will also give us an idea what kind of content and topics gives
the user more interest and can attract more ads that are relevant to the users, or which can
attract ads with higher bid rates.
The URL channels can be created by going to the “My ads ! URL Channels” section of the
Google AdSense interface and clicking ”New URL channel” button.
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2.3.4 Experiments
This sections allows the publisher to create alternate color schemes of text based ads. Later
on the publisher can set to distribute the tra�c among the schemes and analyze which color
schemes attract more users. This is why it is called experiments.
Color schemes can be used from the default ones or can be created and customized and saved
to be used later on.
The Experiments can be created by going to the “My ads ! Experiments” section of the
Google AdSense interface and filling out appropriate details.
Figure 7: Default and High contrast color schemes.
2.3.5 Custom Search Engine
Google allows the publishers to create a custom search engine. This allows the publisher to
have more ads similar to the ones that can be seen in Google’s search results. The search engine
page can be customized to a great detail.
The analysis of the search page can be done separately and thus it can be tracked that how
much revenue is being generated from the custom search engine. This is done by creating a
custom channel from the same page of custom search engine creation.
2.3.6 Allowing & Blocking Ads
Although there is no pinpoint control available to set a specific add to be displayed or not
to be displayed. But publishers can control this at a certain level. This can be achieved by
navigating to “Allow & block ads” section of the Google AdSense home page. Following are the
few possibilities on controlling ads:
1. Ads can be blocked based on the advertiser’s URL
2. General categories can be turned o↵. By default all categories are allowed.
3. Sensitive categories can be turned o↵. This includes categories like Politics and Religion.
By default all categories are allowed.
4. Certain Ad Networks can be turned o↵. By default all ad networks are allowed. By default
the new ad networks that will join Google’s AdSense platform are also allowed. There are
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more than 1300 ad networks in this section. It is recommended to keep them turned on
unless there is a specific reason to do so. This ensures generating the maximum revenue.
5. Ads can be blocked based on their types. This includes text based ads, animated ads etc.
6. Ads can be blocked by selecting individual ads from the “Ad Review Center” section. This
applies only to the ads that are being displayed at the given moment. The default behavior,
i.e. allow all ads without approval, can be changed to approval within 24 hours. This way
the publisher can disallow any add in advance. But if no action is taken before timeout,
the ad will automatically be allowed.
2.4 Analytics
2.4.1 Terms used in Reports
• Pageviews in Google AdSense are when an advertisement in an ad unit is viewed by a
user on a website.
• Clicks are when an advertisement in a Google AdSense ad unit is clicked on by a user on
a website.
• Clickthrough rate (CTR) is the ratio of clicks a particular ad on a website receives in
comparison to the number of total page views it has received.
• Cost per click (CPC) is the amount of money paid by an advertiser for each click an
ad in a Google AdSense ad unit receives.
• Revenue per thousand impressions (RPM) is the average amount of revenue earned
by a publisher for 1,000 impressions on a particular ad unit or website.
• Ad requests refer to the total number of times an ad unit on a particular website requests
Google AdSense to serve a relevant advertisement.
• Coverage is the percentage of ad requests in which a relevant advertisement is found and
displayed within the ad unit.
2.4.2 Reports
1. Dashboard
After the publisher starts earning, the homepage of the AdSense becomes a dashboard
which gives an overview of the entire account and its performance.
Earnings for current day. Earnings of yesterday. Earnings of last month. Comparison
between this month and last month.
Scorecard section which allows the publisher to see how well the site is optimized. There are
three subsections. First one tells how well the site is optimized for mobile devices (tablets,
smart-phones). Second one tells about revenue optimization, like how well we have done
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for optimizing our website for AdSense display ads. Last section is site health which tells
how fast our website is loading. Faster loading pages can attract and handle more users.
At the end of the homepage we can find detailed information about todays performance.
This information includes:
• Pageviews
• RPM
• Top channels
• Top countries from where the visiting users belong
• Top sites in case of multiple sites configured with same AdSense account
• Top platforms from where the site is accessed (mobile, web etc)
2. Performance Reports
The reporting interface allows the publisher to filter down the data based on a large variety
filter. Some of the prominent and more useful filter are:
• Custom Channels
• URL Channels
• Ad Units
• Ad Networks
• Ad Types
3. Data Visualization
Many di↵erent type of visualization options are available for the AdSense users. The main
components can be described as follows:
• Date filters for selecting flexible range of data
• Bar Graphs for comparison among categorized items
• Line Graphs for time continuous data of:
– Earnings
– Pageviews
– Clicks
– CTR
– CPC and
– RPM
4. Custom Reports
The AdSense’s reporting interface allows the publisher to create custom reports. The
process is simple and intuitive. All that is needed to be done is filter down the required
data and select ”Save Report” and the filters and settings will be saved.
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This saved report can be accessed any time later and also an option can be selected to
generate and send the report by email to the publisher by the chosen frequency. For
example a report can be set to be generated daily, weekly or monthly.
Multiple recipients can be added by just entering their email addresses and they will start
receiving the report whenever that report is generated.
5. Exporting Reports
There is also an option to export a report generated in Google AdSense reporting interface
to multiple formats and destinations. Following are the formats to which a report can be
exported to:
• Excel CSV
• Google Drive spreadsheet
• Google APIs Explorer
• BigQuery code
2.5 Tools provided
2.5.1 Optimization Notifications
Over the time of the Google AdSense account usage, the Google AdSense team may send
you tips and messages on how to optimize your settings in order to generate maximum revenue.
These messages come up as a notification icon at the top right corner of the interface ( ). It
is represented by a bell shape and an indicator of the number of messages waiting for you.
2.5.2 Transaction history
Complete detailed history of transactions between Google AdSense account to the account
you have provide while registering for Google AdSense. The details can be filtered according to
the date range you specify.
2.5.3 Holding payments
The default behavior is to payout at the end of every month if your balance is more than
100$. But this can be customized according to one’s own choice. For example the settings can
be changed in order to receive payments in a big chunk every 3 months instead of every month.
2.5.4 Policy Violation Status
This interface will display any violations of the policy contract, if been done, on your account.
The details of the violations and their consequences are displayed as a list. The information
displayed for each violation is:
• Violation detail
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• Occurrence date of violation
• Status of site after violation
• Consequence of that violation
• Site on which the violation is done
2.5.5 Google AdSense Help
Customized help and Search for optimization articles and definition of terms used is available
on demand. This can be accessed by using the search tool available in the top right corner of
the interface.
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3 AdMob
Figure 8: AdMob Logo.
3.1 Description
AdMob is a mobile advertising service and it is designed to help mobile app developers monetize
and promote their apps. Since 2012 it is a subsidiary of Google. Google acquired AdMob to
widen its ad market to iOS and Windows Phone devices.
Publishers across the world are connected using Google’s ad networks. They get paid when
a user clicks on their add. Google will make sure that the ad is relevant to the user to make it
more likely that the user clicks on it.
3.1.1 House Ads
This feature let’s the developer of an application, create a normal campaign but the ads will
be specified before hand. This will allow the developer to display ads about other applications
developed by him. This allows him to let the users notice other applications developed by the
same developer.
3.1.2 Terminology
• Cost per click (CPC)
The advertiser pays the publisher a certain amount of money every time a user clicks on
their add on the publisher’s website.
• Clickthrough rate (CTR)
CTR is the ratio of clicks a particular ad on a website receives in comparison to the number
of total page views it has received.
• Impressions
An impression is simply when a user sees an ad on a mobile platform.
• Fill Rate
It is the rate by which the ads are served vs. the total ads requested. Usually it is targeted
to 100% to maximize the user’s revenue. FillRate depends on the ad network selected. You
can also select to allow Google to maximize fillrate.
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• Revenue per thousand impressions (RPM)
RPM is the average amount of revenue earned by a publisher for 1,000 impressions on a
particular ad unit or website.
3.1.3 Ad Formats
• Click to call
A convenient option to allow the user to directly call a helpline to get more information
about an advertisement.
Figure 9: AdMob click-to-call Ad format.
• Website link
This is the default behavior of any mobile ad. Usually the person is taken to a home page.
• Expandable map
The user can click on the ad which then expands to show a map so that the location of the
advertiser’s store or restaurant can be identified.
Figure 10: AdMob map-directions Ad format.
• Product ad
To promote a specific product, this type of ad can display a small picture of the actual
product to capture attention of the user.
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Figure 11: AdMob product Ad format.
• App promotion
To promote an application the user is presented with an ad which takes him to the appro-
priate application store from where the application can be downloaded. This format is also
used in case of house ads.
Figure 12: AdMob app-promotion Ad format.
• Adjustable width banner
This format automatically adjusts its width according to the size of the device’s screen. It
looks better then the ads that appear in the center with the borders all left out.
Figure 13: AdMob adjustable-width Ad format.
3.1.4 Tablet specific ad formats
• Leader Board: 728x90
Figure 14: AdMob Tablet leader-board Ad format.
• Rectangle: 300 x 250
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Figure 15: AdMob Tablet rectangle Ad format.
• Banner: 468x60
Figure 16: AdMob Tablet banner Ad format.
3.2 Auctioning Functions
Starting from February 2012, AdMob has been shifted to the same auctioning mechanism as of
Google’s AdSense. This is done to streamline both platforms and to make it possible for the
future to merge the two platforms together at some point in time.
After 31st August, users of AdMob will no longer be able to access legacy AdMob but will
have to transfer their data and settings to new AdMob version which is entirely based on Google’s
AdSense and AdWords platforms.
3.3 Parameters
3.3.1 Campaign
A new campaign must be created by entering the following details:
1. Campaign Name
A descriptive name of the current campaign being created.
2. Start Date and Time
A starting point in time for the current campaign.
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3. End Date and Time
This is optional. Useful for the campaigns having temporal nature.
4. Daily Budget
Amount in $ to be used as a daily limit. The minimum is at least 10$.
3.3.2 Ad Group
A campaign contains many ad groups. Ad group must be uniquely named in a campaign. An
ad group can target a specific platform. The available platforms are:
• iPhone OS Universal (iPhone + iPad)
• iPhone
• iPad
• Android
3.3.3 Targeting
The ads in a specific ad group can be targeted with respect to the following categories:
1. Platform/Device
This filter allows to chose specific version of the mobile operating system (e.g. Android OS
2.0) and/or specific targeted devices (e.g. Samsung Galaxy S5).
2. Geography/Operators
An ad group can specifically target people from a region/continent/country. Also people
using a specific mobile carrier can be targeted.
3. Demographics
People can be targeted based on their age and gender. An age range can be specified.
3.3.4 Ad Filtering
The ads can be filtered in many ways. They are described as follows:
• Advertiser URL
You can prevent ads from specific advertiser URLs from showing up on your app. The
limit is 500 URLs per account.
• Category
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– General Category
Although the list contains hundreds of categories, but you can only block up to 50
categories. Beware that ads can belong to more than one categories at the same time.
(e.g. Business, Finance, Travel etc)
– Sensitive Category
This list includes categories more sensitive as compared to the general category list.
(e.g. Politics, Religion etc)
• Language
Regardless of the language of the application, ads from other languages can be blocked.
• Search
You can search using the ad review center for a specific ad in the entire network to block
it.
3.3.5 Ad style
1. Look & feel
• Banner
Banners can be used to display text and image ads.
• Interstitial
This type allows to receive text, image and video ads. You can choose one or all of
the types. But it is recommended to check all types to get maximum revenue.
• Interstitial timeout
As interstitial ads are heavy and may require some time to download on slow net-
works. So there is a time out setting to let the download attempt cancel if nothing is
downloaded in the time specified. You can select from 3 to 10 seconds and it must be
a whole number.
• Text Ad
Select a text ad style that complements your app. You can use the standard style or
customize your own style.
2. Refresh rate
Determine how often a new ad impression is generated. You can choose not to refresh or
to refresh ads every 30 to 120 seconds. We recommend setting a refresh rate between 45
and 60 seconds.
3. Layout & Placement
• Header
This ad will show up at the top of the application content space.
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• Footer
This ad will show up at the bottom of the application content space.
• Fullscreen
This ad will cover the entire screen of the user’s device. The user have to click on the
close icon (X) to return to the previous screen. This mode is suitable for video ads.
3.4 Analytics
3.4.1 Built-in analysis
1. Homepage dashboard
A dashboard layout is available on home page which shows most relevant metrics directly
once logged in. The dashboard shows the following analytics:
(a) Estimated earnings (Today, yesterday, this month, last month)
(b) Estimated conversions (In case you are using AdMob for app promotion)
(c) An overview graph of earnings given by:
• Estimated earnings
• Impressions
• Request RPM
• FillRate
(d) Tabular details of each app, which makes you able to identify the application(s) which
is making more revenue than the others.
2. Monetize section
An overview graph of earnings given by all the previous metrics on homepage and including
new metrics like:
• Requests
• Clicks
• Impression CTR
• Impressions RPM
Filtering is available to better understand the contribution of di↵erent aspects. The filters
can be applied based on:
• Date
• Apps
• Ad Units
Geo-Map report can also be viewed for quick visualization of the source of add tra�c
requests on a map
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3. Promote section
An overview graph of showing the progress of events over a time period is displayed. The
graph can be seen for the following categories:
• Impressions
• Clicks
• Conversions
• Costs
On the same page you can also find tabular details of the same metrics broken down with
respect to all the applications you have added to the account. This can give quite a good
idea on the applications which are making more business than the others.
3.4.2 Google Analytics Integration
After Google’s acquiring of AdMob in 2012, they have provided the option of integration of
Google Analytics with AdMob account. After the integrations is enabled users can find new
reporting options in their AdMob account. Some of the additions are discussed below.
1. Updated Home Page
• Sessions
The total number of sessions for all of your linked apps. A session is the period of
time a user interacts with an app. All usage data (Screen Views, Events, E-commerce,
etc.) is associated with a session. Avg. session duration: The average duration of
sessions for all of your linked apps.
• Users
The sum of all active users of each of your linked apps during the requested time
period.
2. Analyze Tab
• Real-Time
See user tra�c as it happens on your app. Monitor users, top active screens, top
locations, and more. You can use Real-Time as an end to end debugging tool for your
Google Analytics SDK implementation.
• Audience
Get to know the people using your appwhere they are, how often and long they use
an app, and what devices are popular with your visitors.
• Acquisition
Find out how often your app is downloaded and installed, and how successful certain
marketing campaigns are in attracting visitors.
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• Behavior
Track in detail the ways users interact with your app. Find out which screens are
viewed in a typical visit, or set up Event Tracking to analyze custom actions, like
button clicks and video plays. Technical exceptions and crashes are also included in
this set of reports.
• Conversions
Know the real value of your app. Set up Goals and E-commerce to track targeted
objectives, like completed sign-ups and product sales.
3.5 Tools provided
1. Conversion Tracking
This type of tracking will let you know how much of clicks on your ads showing up in your
applications is being converted in to actual purchases of the application.
For Android application, there is no need of anything else, but for iOS Applications, you
need to add a small code snippet in the application source code. For each application
you can set a conversion value, which is usually slightly lower then the actual cost of the
application. This cost is also known as Cost per Acquisition (CPA).
2. Conversion Optimizer
This option will let you chose to have more priority to the adds which belong to the
applications which are giving you more conversion over the previous tracked time period.
For this option to work and predict correctly you must enable the conversion tracking first
and let it run for at least 30 days or 15 conversions (whichever comes first).
3. Ad Filters
Similar to Google’s other advertisement platforms, users have an option of blocking ads
based on the following categories:
• Advertiser URLs
You can block ads from specific advertiser URLs. For example, you might not want
to show your competitions’ ads on your apps.
• General categories
You can block ads from general categories such as Apparel, Internet, Real Estate, and
Vehicles.
• Sensitive ad categories
You can block ads from categories related to sensitive topics such as Religion, Politics,
and References to Sex and Sexuality. Sensitive category blocking is available for ads
in a limited set of languages, regardless of the language of the app.
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4 DoubleClick
Figure 17: Google DoubleClick Logo.
4.1 Introduction
Google acquired DoubleClick in 2008 to extend its operations in to Ad Exchanges. Dou-
bleClick can act as an Ad exchange connecting di↵erent ad networks together as well as an Ad
Server providing publishers with ads from other Google services such as Google’s AdSense. It
can also provide ads from privately owned ad servers. It is also capable of handling pass-back
requests from ad servers when the ad servers are not able to provide any suitable ads at the
moment, to display ads from its own sources.
Figure 18: How DoubleClick works for Advertisers (A) and Publishers (P).
4.2 Auctioning Functions
DoubleClick Ad Exchange uses a Second Price (SP) Auction model. Where possible and
if the ad network supports DoubleClick also uses Optional Second Price (OSP) Auction. SP
Auction is described below:
1. In the open auction, Ad Exchange matches buyers’ targeting with sellers’ inventory and
seeks the highest bid.
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2. The buyer with the highest net bid wins.
3. If two or more buyers bid the same amount for an impression, the winner is selected
randomly.
4. The Ad Exchange auction closing price is determined as the second-highest bid price in
the Ad Exchange auction or the ad unit’s minimum CPM, whichever is greater. Sellers are
paid the Ad Exchange closing price, net of Google’s Ad Exchange revenue share.
5. If Preferred Deals or Private Auctions are in play for an ad unit, they are taken into
consideration before the impression goes to the open auction. The Preferred Deals and
Private Auctions are described below:
• Preferred Deals
This feature provides the ability for publishers to o↵er inventory to one or more
buyers on a fixed price basis. Deals are pre-auction, meaning that fixed price deals
will transact if the buyer accepts the inventory, even if the price is below that of the
auction. Publishers can o↵er a Preferred Deal to more than one buyer.
• Private Auctions
Private Auctions provide Ad Exchange publishers more control over how they sell
their inventory, while providing preferred buyers an advantage in auction buys.
Google has subdivided the service in to two distinct modes. These modes are discussed in
the following sections.
4.3 DoubleClick for Advertisers (dfa)
4.3.1 Description
DFA is an ad-serving solution that helps media agencies and advertisers manage the entire
scope of their digital advertising program. DFA streamlines campaign work-flow and enables
agencies to tra�c, target, and serve creatives. DFA users can also pull reports to view and
optimize campaign performance. Google is continuously improving the platform and is in state
of entire transition from DFA to DoubleClick Campaign Manager (dcm) which is a component
of DoubleClick Digital Marketing (ddm) umbrella of platforms.
When a publisher webpage is visited by a user. The page will call the DFA for an ad request.
This is done by placing a specific code in place of the ad. The DFA will then select an ad among
the list of all ads based on user location and other parameters, and will serve the ad to the
publisher web page. This process usually takes a fraction of a second to complete.
4.3.2 Parameters
1. Advertisers
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As the DFA platform is designed to be used for both individual advertisers as well as for
marketing companies who are running campaigns on behalf of other advertisers, so you can
add advertisers in the account. These advertisers could be your own branch of business as
well. This will help in better management of campaigns.
2. Campaigns
For each campaign, an advertiser is required. In case of a marketing company, the adver-
tisers would be the clients of the company. In case of individual advertiser, the advertiser
would represent the business itself or one of the branches of the business.
A name and duration of the campaign is required. The duration could be timed which is
suitable for campaigns targeted at limited time o↵ers and seasonal sales. In other case the
ending dates are omitted to set the campaign to run for unlimited time period.
Each campaign must be assigned one or more landing pages. These will be used as a default
landing page for all the creatives and ads.
3. Placement
A placement is a location specified by publishers on their website for advertisements. You
can search for a website by its name. The results will display the website URL, the type
of creatives it supports, such as pop-ups or in-stream video etc. The final cost for that the
advertiser wishes to pay for this placement is also defined.
4. Creatives
Creatives are the actual graphical resources, which represent an advertisement. For exam-
ple a banner or a flash animation. Each creative must be associated with a dimesion so
that it could be referred where a suitable placement is available.
5. Types of creatives
Figure 19: Ad Types for DFA.
• Image
Upload an image in *.JPEG or *.GIF file formats.
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• Flash in-page
A flash file in *.SWF format and a backup image file in *.JPEG or *.GIF format for
users who can’t view flash in their browsers.
• Rich Media
Rich media ads are interactive ads including videos and expandable ads.
• In-Stream Video
Video ads that are displayed before playing videos.
• Batch Upload
Batch upload helps in speeding up the process of individual file uploads by allowing
the user to upload all the *.SWF, *.JPEG and *.GIF resources as a single zip file.
• Advertiser-level
If you want to reuse a creative from a previously created campaign, you can select
one from the list of all creatives.
6. Ads
Ad is a logical binding between a creative and its placement on a pageone or more creatives
can be associate with one ad. It is required to select the appropriate dimensions. Smaller
creatives can be displayed in larger ad dimensions, but not vice versa.
A duration is required to describe the e↵ective active period of the ad. You have to provide
appropriate landing pages for each ad. By default they will be set to the campaign’s default
landing page.
If you choose more than one creative for an ad, then you can chose an ad rotation method
to specify how the ads will be changed among each other and over time. The rotation
methods are:
• Sequential
• Random (Unlike the name, the tra�c will be evenly distributed among all the cre-
atives)
• Weighted (Weights have to be provided for each ad in this case)
• Best performing (Based on the CTR of creatives)
• Optimized
For each ad, you have to chose a placement as well. You can practically assign ads to all
the available placements for maximum coverage.
7. Tags for Publishers
In order to advertise manually on websites not managed by DFP, tags can be created for
placements and can be sent to publishers so that they can place the tags in their webpages
and on clicking the DFA account can serve ads on those websites.
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4.3.3 Analytics
• Report Builder
Report Builder is a tool completely built on Google Analytics technology and specialized
for reporting for DFA. The graphs and tables can be totally customizable. Comparisons
can be made between di↵erent metrics. Fields and columns can be added where and when
required.
Reports can be downloaded in standard MS Excel and CSV formats for local o✏ine analysis
purposes. Reports can be scheduled to be generated automatically and sent to the recipients
based on their email addresses. The schedule can be set for daily, weekly (day or days of
week) or monthly (day or days of month) reports.
Figure 20: DFA Report Builder Interface.
• DFA Reporting API
To make the reporting process streamlined and available on multiple platforms as native
applications, Google has provided the developers with the DFA Reporting API. This is a
Rest based API using standard HTTP and JSON, but also pre-built client libraries are
available in many languages including the most common languages such as .Net, Java and
Objective-C. This allows developers to use the reporting API in their native applications
for Windows Phone, iOS and Android application with ease.
4.3.4 Tools provided
• DoubleClick Studio
A free end-to-end work-flow management system that allows creative teams to easily build
and preview Rich Media creatives.
• Google Web Designer
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With this tool you can create engaging, interactive HTML5-based designs and motion
graphics that can run on any device. This tool can create resources for the web as well
as have specialized user interface to create interactive ads. There is also built-in support
for publishing directly to DoubleClick Studio which will help streamlining the advertiser’s
work-flow.
4.4 DoubleClick for Publishers (dfp)
4.4.1 Description
DFP is an ad-serving solution that helps publishers manage the entire scope of their digital
advertising program. DFP streamlines the campaign work-flow for publishers and allows them
to tra�c, target, and serve creatives. DFP users can also pull reports and optimize ads serving
on their ad inventory.
4.4.2 Parameters
1. Ad Units
Ad Unit is the basic unit referring to a section or space on your website which will be used
to display advertisements. The unit is defined by means of a name and its size in pixels
referring to width and height. An ad unit can be fixed size or can be considered as “Smart
Banner”. As per the name suggests the fixed size ads do not change the size which the
smart banners can change their size based on the user’s interaction (e.g. mouse over).
It can also be specified whether the target of the ad will be the same window or a new
window when the user will click on the add. This can be specified by selecting one of the
options from “ top” which means the same page or “ blank” which means a new page.
2. Ad Placement
As the Ad Unit is considered to be a reusable entity, so to use the same ad unit at more
then one locations on a website, the placements can be defined per ad unit.
3. Ad Inventory
It is the collection of ad units defined in the account. The ad units them self are not
attached to any ad requests directly. For ad request establishment, specific orders have to
be created on selected ad units.
4. Orders
Order defines the source of advertisement. It is a container that can hold one or more
Order Line Items (defined below).
5. Line Items
A line item takes an ad unit or ad placement and attaches it to one of the orders. This
setting will enable an ad to be displayed in an ad unit. Next step would be to generate
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specific code for an ad unit and place it in the source code of your website to start displaying
ads.
6. Goal oriented line item
A line item can be goal oriented. Which means that a specific goal will be associated to a
line item, and the focus would be to complete the goal. The goals could be one of these:
• Percentage goal in terms of portion of tra�c
• Absolute goal for number of impressions or clicks
• Unlimited which would be stochastic in nature
7. Line item priority
When creating a line item for an order, a priority level can be set for each line item. The
priority level ranges from 1 (lowest) to 16 (highest). This priority will later help in deciding
the decision of dynamic allocation of ads to slots.
4.4.3 Ad Selection Mechanism
Figure 21: DFP Ad Selection Mechanism.
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1. A user’s browser reads a web page that contains DFP ad tags and sends an ad request to
a DFP ad server.
2. The DFP ad server receives the ad request and gathers information to help select the best
ad.
3. The ad server creates a list of all line items matching the targeting criteria. The criteria
could be for an example, geographic location or operating system of the user.
4. The ad server filters out line items not eligible to serve. These will leave out the line items
which have reached their daily frequency caps. The frequency caps are maintained on client
side using ”DoubleClick cookies”.
5. The ad server scans the list of eligible matching line items, starting with highest priority
and working down until a line item is chosen to serve. The matching for each priority then
looks at the goals in this specified order:
• Line items with percentage goals
• Line items with absolute goals
• Line items that are unlimited
6. Once the best line item is selected, the DFP ad server chooses the best ad in the following
way:
(a) Only consider ads that match the size of the ad request, with an allowance for slightly
smaller ads.
(b) Only consider creatives of a valid creative type for that slot based on format (image,
Flash, and so on).
(c) If there is only one matching creative in the line item, serve it.
(d) If there is more than one matching creative in the line item, follow a creative rotation
rule:
• Random (Choose a creative at random.)
• Weighted (Choose a creative at random, but according to the relative weights
specified for each, such as 70/30.)
• Optimized (Choose the creative with the highest historical average click-through
rate.)
7. The creative from the selected line item is served to the user.
4.4.4 Analytics
• Multiple reporting options
As in all other Google products, reporting feature is quite detailed and robust. So in a
single interface, a user can create reports based on delivered order, inventory performance
and overall sales.
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• Customizable reports
The interface is highly flexible by letting the user ad filters and columns as and when
required. This helps drilling down to the exact information you are looking for.
• Reports Scheduler
Reports can be saved and also can be scheduled to be automatically generated and sent to
appropriate recipients.
4.4.5 Tools provided
• Inventory Forecasting
– Granular forecasts
Forecast how many ad impressions are available for specific dates, inventory, and
targeting criteria.
– Availability reports
View how your delivering campaigns impact your other ads with availability reports.
Ensure your most valuable ads have priority and are going to deliver on schedule.
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1INTRODUCTION
Almost 3 billion people have an internet access making the web the biggest communication channel in the world. No surprise that today there is a prosper market for displaying commercials and ads on the web: to choose this channel indeed would potentially mean to reach 40% of the population world wide, possibility more than appealing for any commercial activity. The amount of different specialized entities that throughout the years tried to create a connection between adverti-sers and publishers proves what stated above.
The interaction between the different parties are of different nature and could be complex so to have a bet-ter insight of the mechanism governing the market let’s understand what are the fundamental roles:
• Users: people who navigate to various webpages• Publishers: who control the webpages and their content, therefore they owe the “free space” ( called Ad-
slot or Display Ad ) to host an Ad or a commercial.• Advertisers: who is willing to post commercials on the ad-slot of a webpage so to get the attention of
the users.
These are the main roles and we can understand that due to the size of the channel (the Internet) direct negotiation between advertisers and publishers could work only for big companies, that’s why in the overall mechanism there are also intermediaries.
Intermediaries can be of different kind but in general their role is to aggregate several parties: Ad Networks for instance pool many Advertisers to bridge their negotiations to big publishers, the Publishers Networks instead are the AdNetwork counterpart on the Publishers side. An advertiser could also choose to delegate the design and the marketing of an ad campaign to an Ad Agency. Even if at a first glance the situation could look clear enough, in practice the interactions among the parties are much more complicated: often the roles overlap or Publishers/Advertisers try to bypass some steps making the ad-path complex and difficult to analyze.
A recent way of selling and buying ads on the Internet is via an exchange that brings sellers (publishers) and buyers (advertisers) together to a common marketplace. This model exists since a long time ago in the context of financial securities, currency, physical goods, virtual credits, and much more and it serves many purposes from improving the efficiency, to eliciting prices and aggregating information and parties. Some AdExchange examples currently leading the online ad market are RightMedia, AdECN and Doubleclick. In this work the main features of such a configuration will be analyzed together with some equilibrium properties and some insight on the overall mechanism governing an AdExchange Market.
Figure 1:AdPath in an exchange marketplace
2
To better understand how the presence of an Exchange and in general many intermediaries influences the on-line Ad marketplace Figure 1 pictures the AdPath in such a configuration.
This general settings comprises one center that sells a unique, indivisible good and n intermediaries that bid in an auction run by the center, it’s important to notice that nor the center nor the intermediaries have a value for the good itself. Each intermediary i has a set of buyers and each buyer j has it’s own value vj for the good. Any further assumption on the actual value vj or its probability distribution varies from model to model. As in many other known settings to decide to whom sell the good the intermediaries run an auction; in this particular situation the timing is as follows: first each intermediaries runs in parallel a contingent auction that will determine a contingent price and buyer for that specific intermediary. Please notice that the contingent buyer will get the good only if its intermediary will get the good and this can happen only if such an intermediary turns out to be the winner of another auction ran by the center. The center runs an auction in turn and the intermediaries bid based on the their contingent price; once a winning intermediary is selected it transfers the good as determined by its own auction.
This situation recalls the standard economic concern of double marginalization. An upstream monopoly manufacturer (the center here) sells to customers via a monopolist downstream retailer (a single interme-diary). In contrast to the case where the manufacturer sells directly to the customer, the consumer will be charged a higher price and therefore demand a lower quantity, since both the manufacturer and the retailer must extract margins from this transaction.
To not include such a natural market effect in the online setting would be myopic and would lead to wrong equilibrium considerations. Do not forget that the trade is made online and the good (AdSlot) is sold on a single impression rather than a “per click” basis; this means not only that the volume of transaction is huge but also that the Ad-Slot is auctioned in real time. The average 10-100 ms loading time of a webpage calls out loud for real time algorithm and fast networks.
Let’s now analyze each part of the system to understand the equilibrium and the mechanism of such a setting.
THE PUBLISHER
Even if the exchange model repre-sents a common marketplace the pu-blisher often decide to commit also
for guaranteed contracts, especially because that is the traditional way of selling advertisement on the internet. The publisher then has both to fulfill the legal requirements imposed by the guaranteed con-tract ( i.e. to guarantee to the advertiser a certain number of impressions of a certain quality ) and to sell impressions in the exchange market. It is easy to understand that a spot marketplace ( the Exchange ) is still appealing to the publisher because it represen-ts an immediate, short term source of revenue, the value of the impression to sell thought is determined
by the result of an auction (the price could be low), therefore it could be better for the publisher to sell that specific AdSlot to the guaranteed customer in-stead (contributing to fulfill it’s legal duties). A good move for the publisher would be to assign a own value to the impression, probe the spot market pla-ce to understand the perceived value of the Ad Slot and decide the trade channel accordingly. Clearly if the buyers’ evaluation of the impression is higher than the publisher one the latter will sell the Ad-Slot through the exchange marketplace otherwise it will sell it to the guaranteed customer.
The question is: how can a publisher understand the buyers’ evaluation? This is not trivial at all, a good hint is the price resulting from the auction in the spot market. Indeed on the long run and with
3
a high enough number of buyers (AdNetworks) the highest bid (the price) converge to the real evalua-tion of the Advertiser.
A smart idea for the publisher is to virtually par-ticipate in the Exchange auction as a buyer bidding its own evaluation of the Ad-Slot, in this way either the publisher results to be the winner of the auction or some other Ad-Network wins the right to buy the Ad-Slot. In the former scenario the bids of the other Ad-Networks are below the Publisher’s evaluation of
the impression therefore it will be sold to the gua-ranteed customer; in the latter scenario there exists an higher evaluation and the impression will be sold through the exchange.
This solution has been analyzed in the paper “Bid-ding for Representative Allocations for Display Ad-vertising” [1] and I refer the reader there for more analytical details about the optimal allocation and bidding strategy.
THE CENTER
The center is the first step of the Ad-Path from the publisher to the advertiser, it’s the center (or Exchange) that decides how to fil-
ter the information given by the publisher therefore it represents the first marginalization stage. To clari-fy this point let’s call the information shared by the publisher with the exchange (P(w), ρ, P(u)) which are the information on the Web Page hosting the AdSlot, the AdSlot minimum price and some User profiling information respectively; the center can decide to share with the AdNetwork a different ver-sion of P(w), ρ and P(u) so to take advantage of his winning position. Namely such filtered information are E(w), E(ρ), E(u) and they are the AdNetwork’s knowledge about the publisher side. Being able to set E(ρ) price means to set a reserve price on which the Exchange could monetize: as already stated, in-deed, nor the AdNetwoks nor the Advertisers have the knowledge of the real ρ price set by the publisher. Please also notice that the Exchange does not have to pay any price to none of the other parties so it is its interest to maximize the expected revenues (not the profit as it will be for the intermediaries).
This introductory reasoning it’s useful to under-stand what kind of mechanism the exchange should implement so to guarantee a good equilibrium and a good marginalization. From the vantage of the cen-ter, it is simply running an auction for a single indi-visible item with bidders with known values, indeed at the time of the auction the intermediaries have already run their contingent auctions therefore their value it’s known. This situation is well known and the revenue-optimal auction is a second price au-ction with reserve; actually this would be true in the case of symmetric participants which in this setting means that all the intermediaries have the identical number of buyers and those buyers have the identi-cal bid distribution. Unfortunately such hypothesis do not hold for the Exchange marketplace setting where there are AdNetwork bigger than others and not symmetric bid distribution among the adverti-sers. In practice though, second price auction repre-sents the predominant mechanism for on line bid-ding and are a good way for the center to be fair enough among many different intermediaries. That’s why real exchange marketplaces such as DoubleCli-ck implements a second price auction at the center side.
4
INTERMEDIARIES
The main question to answer in this context is: given that the center runs a second price auction with reserve pri-
ce, which is the optimal strategy for an intermediary with captive buyers? The two main assumptions the-refore are the kind of auction ran by the center and the captivity of the buyers: regarding this it is a rea-sonable situation since, in practice, it is likely that a buyer will bid in a single network per auction. Even though this is true in practice, it would be a of great interest for the advertisers themselves to study a set-ting in which bidding for different ad networks at the same time is allowed (Game theory of advertisers).
An answer to the main question can be found in the paper “Auctions with Intermediaries” (2) under the stringent assumption of having just one buyer per intermediary; it is easy to understand that such an hypothesis just does not fit the real on-line situation, nonetheless it is of great theoretical interest. The main result in this this context is:
“With a single buyer, a take-it-or-leave-it price is the only dominant-strategy incentive-compatible mecha-nism available to the intermediary.” (2)
The theorem means that the intermediary offers a price p to its buyer, if the buyer’s value is such that v≥p he will agree to the price otherwise he will reject to bid. If the buyer accepts the price then the inter-mediary will bid that price into the center auction. Formally what just stated could be expressed in this way:
• p(v)=p is the intermediary price (and potential bid into the center’s auction)
• a(v)=1 if v>=t or a(v)=0 if v<t is the probability to win the contingent auction.
Another important result in this first setting is that: “ There exists an equilibrium in which intermediaries
offers a random price in an interval [Vl ,Vh] with some PDF π ”
It means that the prices are, up to some extent, ran-domized in an interval; such an interval depends on the center reserve price in the following way:
Suppose the interval [Vl ,Vh] and the probability distribution π
• Parameters Vl ,Vh are increasing in the center’s reserve price r holding the number of interme-diaries n fixed.
• The parameter Vh is increasing in the number of intermediaries n holding center’s reserve price r fixed.
As already stated there exists an analytic proof of
results here included and I refer the reader to (2) for a formal analysis.
It’s fundamental to understand that such resul-ts hold just under the stringent assumption of one buyer per intermediary; luckly the case with many advertisers per intermediaries is not so different.
The main result indeed seems to hold again: the op-timal auction mechanism is a second price auction with randomized reserve price.
All of the result above holds in a situation of sym-metric equilibria in which all of the intermediaries have the same number of buyers, the authors of (2) suggest that, with a lack of symmetry, the result could dramatically change and conjecture a second price auction with fixed reserve price to be a possible solution.
5
ALGORITHMS AND SECURITY
Now that the dynamics of the marketplace are clear let’s analyze what could be the issues of a practical implementation of the exchange model.
Real Time Is A MustA first concern is that all the transactions have to be carried out in real time (10-
100 ms) therefore all the auctions, the algorithms and any mechanism involved in the trade should be implemented considering speed as a fundamental feature.
AlgorithmIn the paper “Adaptive Bidding
for Display Advertising” (3) two real time algorithms (Le-
arn-Then-Bid and Guess-Double-Panic) for bidding in an exchange marketplace are designed and their pseudo code is given. The main idea behind both the implementations is to divide the bidding process in two parts: as first the bidding agents (either the AdNetworks or the Advertisers) probe the market to build a PDF of the highest bids (Exploration Phase) and in a second moment they make their own bid (Bidding Phase).
In real markets who’s the auction winner is either notified only to the winner himself or to all the par-ticipants; the first scenario is called Partially Obser-vable Exchange and the second Fully Observable Exchange. In the latter context it is easy to get the knowledge of the PDF since it is enough for a player i to bid bi=0 to discover the highest bid; in the former case a penalty occurs at every round of the explora-tion phase since, to be notified about the winner’s identity, a player’s bid bi has to be the highest. Both the algorithms implement an optimal behavior in both of the cases and have a computational com-plexity compatible with real time implementation.
The lack of information (Partially Observable Exchange ) does not handicap the Guess-Double-Pa-nic algorithm so much and the results in the two sce-narios are not so different.
I refer the reader to (3) for the pseudo code and further analysis.
ProxyAt a certain point the exchange seeks
bids from the AdNetworks, at a system level this could be accomplished in many ways among which:
• Load the Ad campaign of the the AdNetwork ai in the Exchange’s physical system
• Host the ai bidding software in the Exchange’s servers
• Make HTTP calls to ai servers and wait for the AdNetwork’s bid and Ad (bi ,di).
Even though the two first mechanisms are faster than the last one they don’t allow an AdNetwork to update its campaign or tune some quality parameter in real time. HTTP calls are resource consuming but allow a greater flexibility, let’s understand what is the tradeoff in this context.
On the long run the exchange knows what are the preferences of its AdNetwork and could decide to share the informations (E(w),E(ρ),E(u)) with just a subset of them. The AdNetwork themselves could benefice from this since otherwise it could be hard to handle the huge amount of HTTP calls coming from the exchange (if not filtered). This problem could be stated as in (4):
Each AdNetwork i has bandwidth budget Bi. Say E has bandwidth budget of B. Design an online algori-thm for E that for each incoming call (wj , uj , ρj ), chooses a subset Sj ⊆ S(E(wj ),E(uj ), ρj ) of networks to
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call such that no AdNetwork i gets more than Bi calls per second, E makes fewer than B calls per second, and optimizes the expected• number of bids, ie, number of nonempty
(bi(j),di(j))’s received at E, or
• efficiency ∑j maxi bi(j), or• sales revenue∑j max i | bi(j)≠maxi bi(j)
bi(j), or• profit for E.
SecurityAnother serious requirement the exchange system has to fulfill is to guarantee integrity to all the tran-
sactions involved in the trade. This mainly means to guarantee that:
• All the auctions are closed envelope, so that no participant can see any other participant’s bid.• All communications and computations are performed correctly.
To guarantee all of these a reliable system of cryptography should be adopted, the problem is that there exists a tradeoff between reliability and complexity of the system itself. Complex systems are often not fast enough for the purpose of online auctions and good standard solutions are yet to be discovered. The main improvement in this direction is represented by the Zero Knowledge Proof Of Correctness that requires few informations about the input to prove that an output is actually correct with a probability of almost 100%. In the Exchange setting the input is represented by the advertisers bid and the outputs could be the winner or any of the computations involved in the process. Further details could be found in (5)
Examples And Conclusions
Double click is one of the larest Ad Market and implements a special model of Exchange mar-ketplace: the OSP AdX model.
This model represents the situation discussed before but uses a slightly different second price auction cal-led “Optional Second Price” (OSP).
In this setting:
• Each network i that participates submits man-datory bid bi and an optional bid oi≤bi (which could be 0).
• AdX runs a second price auction, using Publi-sher-specified ρ as the reserve price, and char-ges winner i, max{maxj≠i bj ,oi , ρ}
Apart from being truthul the main feature of this
model is that it is easily implementable and adap-table to the infrastructure, interactions and context already existing in the on-line marketplace. Google’s DoubleClick AdExchange uses the OSP auction sin-ce 2009 and keep using it also today becasue of it’s great felxibilty and good performances; the optional bid feature is being used especially to let Google’s Adwords network bid via Ad Exchange, where this feature is used to simulate AdWord’s native second price auction seamlessly.
Wrapping up nowadyas AdExchange marketpla-ces represent, together with Sponsor Research, the satandard way to trade Ads on-line; they guarantee real time performance and reliability. They also of-fer to the participant enough felixibility to choose what startegy to implement (when there are no legal constraints). Even though some research has already been done a further insight on the Game Theory of Advertisers and practical solutions and algorithms would be of great interest, both theoretical and eco-nomic.
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REFERENCES
1. "Bidding for Representative Allocations for Display Advertising" Arpita Ghosh, Preston McAfee, Kishore Papineni,Sergei Vassilvitskii
2. "Auction With Interemediaries" Jon Feldman, Vahab Mirrokni, S.Muthukrishnan, Mallesh M.Pai
3. “Adaptive Bidding for Display Advertising” Arpita Ghosh, Benjamin I. P. Rubinstein, Sergei Vassilvitskii, Martin Zinkevich
4. "Ad Exchanges: Research Issues" S. Muthukrishnan
5. "Strictly-Black-Box Zero-Knowledge and Efficient Validation of Financial Transactions" Michael O. Rabin, Yishay Mansour, S. Muthukrishnan, and Moti Yung
1. Social networks
A social network can be defined as a social structure made of nodes, which are usually individuals
or organizations tied by one or more specific types of relations, such as financial exchange,
friendship, passion, trade, web links, airline routes, hobbies.
1.1 Mathematical models for a social network
In order to model a social network, it's necessary to introduce the definition of scale free random
graph: a scale free graph is a graph whose node degree follows a power law distribution.
It means that the fraction of nodes that have k neighbors, denoted by P0(k ) , is proportional to
k−γ
for large values of k, that is:
P0(k )∝k−γ
with 2<γ<3
A realistic social network has a number of user in the order of 106 or larger, so we can assume
the model of the social network as a infinite scale-free random graph G(V,E).
1.1.1 Social network as a scale free random graph
This model analyzes the statistical properties of a social network, using a scale free random graph.
The purpose of this model is to use it to study the dependency among nodes that may occur even if
nodes are connected with multiple links to each other. Since this type of multipel-nodes interaction
is generally difficult to solve exactly, the solution is done constructing a local mean field of an
arbitrary node r.
Let's notice that each user of a social network is represented as a node in the graph G(V,E).
The starting point is a randomly chosen node r∈V : since r is randomly chosen, according to the
property of a scale-free random graph, r has deg (r ) neighbors, where deg(r) follows the
power law distribution.
Notice that the influence to node r is indipendent between any two sub-trees.
Since there exist a recursive tree structure, we can easily analyze the overall influence by all nodes
to the root node r. We obtain the degree distribution for the root node r and its children nodes as:
Root node r: Prob[deg(r)=k ]=P0(k )=C⋅k−γ=
k−γ
ζ( γ) for k=1,2 ,…
where C is the costant such as C∑k=1
∞
k−γ=1 is satisfied and ζ (γ)=
1
C
Children node of r: P1(k )=k1−γ
ζ (γ−1) for k=1,2 ,…
The degree distribution of the children nodes of r follows a shifted power-law distribution P1(k )
1.1.2 Social network as a scale free random graph with high clustering coefficient
In a social network, two common friends of an user are usually friends of each other. This implies
that graphs of social network usually exhibit high clustering coefficient.
We define the clustering coefficient of a graph G(V,E) as
c=1
|V|∑v∈V2t v
k v(kv−1)
where |V| is the cardinality of the nodes in the social network, k v is the degree of node v and
t v is the number of edges in the neighborhood of node v.
Now it's not possible to model the scale-free graph as a tree. Indeed, we use the following structure:
Let's call the edge between sibling nodes as the cross edge: in the structure shown above, node b
connects with j children of a's. Since the purpose of the model is to analyze the dependency
between nodes, these j children can be seen as b's children. Here it comes a modified structure:
We can call the children nodes as descendent nodes; to compute the degree distribution of
descendent nodes in the local mean field tree, it's necessary to determine the probability that a cross
edge appears: we can assume that all croos edges appear with probability c.
We obtain that:
P1(k )=∑m=1
∞ m−γ
ζ (γ)⋅∑j=0
m−1
(m−1j )c j(1−c)(m−1− j )⋅
k (k−1)⋯(k− j)k−γ
∑k=1
∞
k (k−1)⋯(k− j)k−γ with k=1,2,…
2. Social networks websites
A social network website is a website that meet some basic required features:
• The website must contain user profiles and contents
• There must be a method that permits users to connect with each other and post comments on
each other's pages
• There must exist virtual groups that can be joint by users and that are based on (their)
common interests such as fashion or politics.
An example for a social network website is Facebook: it is one of the fastest growing social
networks. It consists of many networks, each based around a school, workplace or region.
Each user has a personal profile and most users belong to one or more networks.
A user can join various interest-based groups on Facebook or may even start a new group.
Recaping, we can say that two user can be connected in three different ways:
◦ User a is friend of user b
◦ User a and user b belong to the same networks.
◦ User a and user b belong to the same groups.
The important proven characteristic in Facebook is that when a user makes a recommendation, his
friend usually accept recommendation of informations by their friends
In this way, it may be possible to apply this principle to recommendations of products.
2.1 Business model of a social network website
Social networks are mainly used in 2 areas:
• Corporate envinronment, in which business companies use social network services to
support their product or customer services
• Online advertisment. In this case retailers and corporations place online ads on social
network sites to take advantage of the large volume of visits by potential customers.
Now we focus on online advertisement and how it's obtained the revenue collection.
Almost all social networks websites have revenues from these methods:
• Advertising: the company which holds the social network website is paid for putting up
advertisement of other organizations.
• Subscription: the company which holds the social network website collects fees from the
subscribers in exchange for access to content or services.
• Affiliate: the company which holds the social network website gets paid for referring people
to other services/companies. This method works similarly to the online ad: the user clicks an
ad hosted on the company's website and the user gets redirected to the advertiser's website.
Instead we can notice that the cost of the website are not so much relevant, compared to the possible
revenues:
• Cost of gaining new customer is praticallty nothing since users usually join voluntarily
( despite this there are marketplace-like websites which holds social networks that offers
their new customers a fee to be used in their websites for future purchases)
• Cost of running the sites' web servers is relately low
We can conclude claiming that low-cost social network sites could be highly profitable.
Therefore, in order to remain competitive, an online social network site must provide innovative
and quality services to recruit new users and retain existing members.
The quality of the services and features that a service provider provides will determine whether
people would be hooked to the social networking sites.
2.2 Advertising on social network websites
New trends go in the direction of using social networks to make online advertisement.
Indeed people usually live in some communities an are associated with potentially multiple social
networks; there are two important potential benefits for advertising associated to social network:
1. Advertising propagated through a social network can be expected to be more trustable.
Indeed people in social networks are often more willing to trust and accept
recommendations from their neighbours or to be influenced by them and their actions.
2. Social networks potentially allow us to obtain valuable information about users through
observing their activities. On the same time, social communities of users can be leveraged to
infer a single user's interest in the same spirit as collaborative filtering.
Related to advertising, we can say that it's possible to potentially leverage social networks to
better model users and improve effectiveness of advertising.
2.2.1 Targeted advertising for online social network websites
Targeted advertising is the type of advertising in which shown ads should match user interests.
In order to achieve this type of advertising content-based advertising (CBA) is used.
CBA's state of art currenntly uses member demographics and stated interests on social networks
websites profiles for delivering ads; but these retrieved info don't necessearily represent
monetizable user intents and interests.
Furthermore this explicit way of retrieve info may lead to the issue of reactance: reactance is the
motivational state when consumers resist something they find coercive by behaving in the opposite
way to the one intended; indeed, it happens frequently that targeted ads are felt intrusive and
invasive of users' privacy, as explained before.
For instance, a way used by Facebook to reduce reactance is to publicly alert users to privacy
policy's changes, make them aware of this and give them control to take decision upon it; by doing
this users react more positively to personalized ad content and click on personalized ads.
Anyway there's the need for retrieving more information from public online venues such as forums
and marketplace where intents are readily expressed and representative of a user's current needs;
in advance, the retrieved info will be less targets of privacy concerns, since posts are already public.
Content analysis system for targeted advertising model
a) Identifying monetizable user intents by crawling user posts and extracting keywords.
The first component is the crawler that crawls, cleans and ingest user post from a social
networks websites.
The second component spots keywords in a post thread that is a post and its replys in a
thread. To achieve this task we cannot rely on word frequencies alone, since this type of
algorithm doesn't take in account ill-formed or fragmented sentences and misspelled
keywords ( due to slang terminology too).
This process is achieved in two step.
1. The algorithm processes every previously crawled post in the dataset and saves every
spotted unique keyword in a global dictionary.
2. Using a basic window-based spotting technique backed by the global dictionary, the
algorithm goes through each post again and spots keywords missed in the first round;
these keywords are called variants or variations of keywords and so we can record each
keyword with its own transliteration.
A possible way to achieve this record is to use Levenshtein string similarity based on
edit distance between a saved keyword stored in the global dictionary at the point 1 and
a window of word of the currently analyzed post. Then we apply a threshold on the
similarity to claim if there is a variant and, if so, to record the transliteration.
b) Eliminating off topic content through a clustering mutual information based algorithm
We define two clusters to be used in this algorithm:
1. Cluster 1 (C1 ) : we assume that the title of a user post ( which is mandatory) is
representative of the post's content for finding relevant keyword in the post. This
assumption and not finding keywords in the title will be drawbacks of this algorithm.
Therefore, cluster 1 is composed by all spotted keywords in the post's title.
2. Cluster (C2) : cluster 2 is composed by all spotted keywords in the post thread that is
the main post and its replies.
Mutual information is used by this algorithm to measures how strongly keyword in the post's
thread are related to keyword in the post's title. After considering all keywords in C2, and
sequently increasing C1, C1 houses all informative, non noisy keywords stored in the post.
Mutual information between two words wi and w j is defined as:
I (wi ,w j)=n(wi ,w j)
N⋅log
n(wi ,wj)N
n(wi)n(w j)
where N is the number of the token in the web, n(wi) is the count of word wi in the
web and n(wi ,w j) is the co-occurence count of words wi and w j
Mutual information of cluster 1 is defined as:
I (C1)=∑wi,wj
I (wi,wj)
where wi,w j∈C1 and i≠ j .
Information content of cluster 1 is defined as:
IC (C 1)=I (C1)
(|C 1|2 ) where |C1| is the cardinality of the cluster 1
Information gain of cluster 1 shows the change in IC(C1) by adding a keyword k:
IG(C1,k )=IC (C1, k )−IC (C1) where IC (C1,k) is the IC after adding k
Algorithm steps:
a) Measurement of IG(C 1,ki) where ki is a keyword taken from the cluster 2.
If the computed IG is negative, the keyword ki is eliminated.
Notice that this step is computed only when C1 stores only keywords taken from the
title.
b) Keywords with positive IG are removed by C2 and added to C1 in an ascendent order.
That is the algorithm starts by adding keyword with the lowest positive IG: indeed the
ascending order intuitively implies the smallest changes in the characteristics of C1.
c) The algorithm proceeds to consider the remaining words in C2, greedily adding
keywords that have the lowest IC (C1,k) score at each step.
d) The algorithm terminates when it has either evaluated all keywords in C2 or when no
more keywords result in positive IG(C1,k) scores.
The algorithm complexity is O(N2) where N is the number of unique spotted keywords.
2.2.2 Social advertising
In social advertising, ads are targeted based on underlying social networks and their content is
tailored with information that pertains to the social relationship.
In other words, a social advertisment is an online ad that incorporates user interactions that the
consumer has agreed to display and be shared.
In the case of Facebook, for example, a social ad is tailored
with the name and/or the profile picture of one of our friends;
this means that our friend belongs to our social network.In the
case of the right, only name of the friend tailored the ad
Model
Targeted user by the ad
There are 2 general types of user, according to their interests:
◦ Targeted: they are the users that are interested in the topic of the ad
◦ Untargeted: they are the users that are not interested in the topic of the ad
We assume that both of these types of user didn't "like" yet the ad that has to be published so
they can be targeted by the social advertising. This means that if a user has friends that
"liked" the page we want to advertised, this user is targeted with a ad related to his social
network, regardless its actual interests.
Of course, the efficiency of the ads depends on the type of the user.
Ad-text conditions
There are different messages to be published with our ads. In this case, varations in
messages and different types of wording to evoke social influence give different results; in
general, any explicit advertising message is effective. Notice that these variations in
messages don't include explicit attempts to harness social influence.
Results
Results are expressed with a click-through rate that is the proportion of people that clicked on that
ad during a period of time
• Social advertising is more effective than regular display advertising.
• Regular display advertising are the ones that are not socially targeted. Therefore, social
targeting and friend's endorsement increased the average click-through rate and this result
holds during the time, if the ad still persists, of course.
• Explicit attempts to harness social influence are reducing or even damaging the results of the
advertisment.
• Ads that lacks of friend's endorsement but that are shown to user whos friends are involved
in the topic of the ad ( so social targeting still holds) are less effective; anyway they are
more effective than the regular display advertising.
• Social advertising improves both the targeted and untargeted campaigns.
• Intrusive or highly personal advertising is more acceptable if done algorithmically by a
faceless entity such as a computer than when it is the result of evident human agency.
So it's not efficient for the firm to highlight directly previous consumer actions to positively
influence the consumer's response.
Interpretation of the results
• Endorsement of the friends is informative
• Homophily is the behaviour of friends acting in similar way.
According to this behaviour, it may be possible that social targeting uncovers people who
will be more likely to be interested in a topic.
