attribution modeling - case study
DESCRIPTION
One of the crucial trends nowadays will be the growth of attribution modeling. However, many savvy marketers are still missing the opportunity to reap the benefits of attribution modeling, hence this whitepaper is aimed at providing a comprehensive overview of what marketing attribution is all about.TRANSCRIPT
Attribution ModelingGet the most out of Attribution Modeling - Measure the true value of all marketing channels
Foreword
If we are to summarize the current top 10 marketing topics around the world, attribution modeling must be one of
the latest hot topics within the industry. According to the report conducted by Econsultancy and Adobe in November
2012, only 26% of advertisers worldwide and 36% of advertising agencies carried out marketing attribution. It is truly
evident that attribution modeling is rapidly growing and its value is being recognized by a vast majority of marketers
nowadays. Based on the report, 29% of advertisers that do measure attribution say it has signi�cantly bene�ted their
business while 60% of those realized that it is bene�cial. Marketers can better understand their budget allocation,
gain insights into a�liate marketing e�ectiveness and optimize their marketing mixes.
However, attribution modeling is still at its initial stage of gaining popularity within China. Many of the marketers are
not familiar with attribution modeling and the purpose of this whitepaper is to elaborate on the use of attribution
modeling and demonstrate its e�ectiveness on measuring the success of your marketing e�orts.
Co-founder of iClick – Ricky Ng
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Table of Contents
Part One Why do marketers need attribution modeling?
- Why do marketers need attribution modeling?
- What is the biggest value of attribution modeling?
Part Two What is attribution modeling?
- What is attribution modeling?
- Commonly used attribution models
Part Three How attribution modeling creates value to marketers?
- Case analysis
- How to make use of attribution modeling to analyze your campaign?
Part Four An introduction to XMO attribution modeling
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Part OneWhy do marketers need attribution modeling?
For many marketers, managing marketing budget and maximizing ROI (Return On Investment) are the biggest
objectives of every campaign. With the challenges faced by marketers on the complexity of media channels, it is
relatively di�cult to conclude the ideal channel to be used. When you plan to utilize your marketing budget for a
campaign, will you have the following di�culties?
- How to optimize channel mix to maximize ROI?
- Which channel is most suitable for my products?
- How do you manage the whole media buying process to measure the e�ectiveness in real time?
- Will there be any impact to the channel in the case of adding or reducing marketing budget?
- Any di�erence on user pro�le from di�erent media channels?
- Does this channel truly bring my marketing campaign with the most desirable results?
Why does attribution modeling gradually become critical to marketers? Below is an example to help you easily
understand:
For example, assume 10 successful conversions are received in a week from search engine marketing and display
advertising. If marketers could only track the conversions based on last click, then the result would show:
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Last Click Conversion
1 Search Engine
2 Search Engine
3 Search Engine
4 Search Engine
5 Display Ad
6 Display Ad
7 Search Engine
8 Search Engine
9 Search Engine
10 Search Engine
As the above table illustrates, marketers may think that the conversion rate appears to be extremely low for display
advertising. In this case, marketers will intuitively allocate more budget to search engine marketing.
However, with end-to-end conversion tracking available, marketers can now better understand the process behind
each conversion more thoroughly:
Based on the analysis of conversion path, online display advertising has actually assisted 6 out of the 8 conversions
made from search engine marketing.
Do marketers now have a new perception of online display advertising based on its results? By learning the insights
from the conversion path report, marketers can now understand more about the “assist e�ect” amongst di�erent
advertising channels.
The main advantage of attribution modeling is to re�ect the real value of the contribution made to each channel. For
example, if 1 credit will be given only if the channel has contributed in a conversion, in this case, the value of search
engine marketing and display advertising will be calculated as follows:
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Last Click Conversion Conversion Path
1 Search Engine Display Ad → Search Engine
2 Search Engine Display Ad → Search Engine
3 Search Engine Display Ad → Search Engine
4 Search Engine Search Engine
5 Display Ad Display Ad
6 Display Ad Display Ad
7 Search Engine Display Ad → Search Engine
8 Search Engine Display Ad → Search Engine
9 Search Engine Display Ad → Search Engine
10 Search Engine Search Engine
Last Click Conversion Conversion Path Search Engine Display Ad
1 Search Engine Display Ad → Search Engine 1 1
2 Search Engine Display Ad → Search Engine 1 1
3 Search Engine Display Ad → Search Engine 1 1
4 Search Engine Search Engine 1 0
5 Display Ad Display Ad 0 1
6 Display Ad Display Ad 0 1
7 Search Engine Display Ad → Search Engine 1 1
8 Search Engine Display Ad → Search Engine 1 1
9 Search Engine Display Ad → Search Engine 1 1
10 Search Engine Search Engine 1 0
Total 8 8
The biggest value of Attribution Modeling
The above example demonstrates the importance of attribution modeling. Not only it helps the marketers with the
ability to monitor performance of di�erent media channels, but it can also increase ROI (Return On Investment)
signi�cantly by re-allocating budget amongst channels. With some critical points mentioned above, more and more
marketers are willing to adopt attribution modeling in the long run.
Attribution Modeling - Bene�ts to Marketers
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Able to reallocate budget across channels and improve ROI
Better understand how digital channels work collaboratively
Gained valuable insights into consumer makeup and behavior
To provide objective reasons to justify more marketing budget
Increase understanding on the role of online/o�ine media interactions
72%
63%58%
54%
44%
Data Source: Google analysis <Marketing Attribution: Valuing the Customer Journey>
Part TwoWhat is Attribution Modelling?
Attribution modeling is a set of rules that determines the sales or conversions assigned to each touch point in
conversion paths.
Savvy marketers understand that you don’t attract your customers with just one simple message, just one image,
or just one ideally positioned advertisement. It is a complicated process of planting the seed, nurturing it and at
last harvesting the fruits of your marketing e�orts.
Right before your customers buy or convert, they may encounter various parts of your online marketing campaign
including paid and organic search, email, a�liate marketing, display ads, mobile placements, etc. Each of these
factors has a signi�cant impact on the campaign results.
In the past, the value of the marketing campaign is only determined by the last click of the users in the media
channel. But when you think thoroughly, the user may be a�ected not just on his/her last click but also in other
areas during the conversion. Attribution Modeling o�ers a series of di�erent methods to determine the role that
channels play throughout the conversion journey.
Before the user completes a conversion, they will usually encounter with various advertisements many times.
Some media channels help to expose the ad to the users, while others may use to assist conversion.
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Day 1: User views ad on website. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Day 2: User search for “smartphone”. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Day 4: User clicks on Banner Ad. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Day 35: User sees a video ad of a smartphone brand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
20 mins later: User searches for that smartphone brand. . . . . . . . . . . . . . . . . . . . . . . . . . .
Cause
Promote
Promote
Promote
conve-rsion
-
-
-
Last-Touch Attribution
The Last-Touch Attribution Model attributes 100% of the conversion
value to the last referring channel with which the customer comes
across before purchasing or converting. This model is extremely
common among most marketers, hence it is a great baseline for
comparison with other models.
Appropriate use: If your advertisements and campaigns are
developed to drive customers tra�c at the time of purchase, or your
business is mainly transactional with a sales cycle that does not
involve a consideration phase, the “Last-Touch Attribution” model
may be ideal.
First-Touch Attribution
The First-Touch Attribution model attributes 100% of the conversion
value to the �rst channel with which the customer comes across.
Appropriate use: If your advertisements or campaigns are developed
to maintain awareness with the customer, this model �ts you
perfectly. For example, if your brand is not commonly known, you
may primarily focus on exposing your brand to customers through
keywords or di�erent channels.
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Commonly used attribution models
To optimize the use of attribution modeling, marketers must �rst clearly understand and identify its marketing
objectives regardless of whether to increase conversion quantity, increase user registration or download discounted
coupons, etc.
In the meantime, marketers should also understand how credit should best be assigned to each conversion funnel.
Below are the most commonly used attribution models and its appropriate use:
Last-Touch ModelORGANICSEARCH REFERRAL PAID AD DIRECT
The direct conversion value to the last referring channel
conversion value
100%
100%
First-Touch ModelORGANICSEARCH REFERRAL PAID AD DIRECT
Credits received from organic search is based on the �rst interaction.
conversion value
100%
100%
Time-Decay
If the sales cycle involves only a short consideration phase, then this model may be appropriate for you. It will assign
the most credit to touchpoints that occurred closest to the time of conversion.
Appropriate use: If you run one-day or two-day promotional campaigns, you may wish to assign more credit to
interactions during the promotion. In this case, interactions that occurred a week before have smaller value as
compared to those touchpoints near the conversion. The “Time Decay” model may be appropriate for assigning
touchpoints during the day or two to generate conversions.
Position-based
This model allows you to use a combination of “First-touch Attribution” and “Last-touch Attribution” models. Other
than assigning all the credits to either the “First-Touch Attribution” or “Last-Touch Attribution”, you can easily allocate
the credits between them. One commonly seen scenario is to assign 40% credit each to the �rst and last interactions,
and assign the remaining 20% credit to the middle interaction.
Appropriate use: If you primarily value touchpoints that sell your brand to your customers and �nal touchpoints that
resulted in sales, you can simply use the “position-based”model.
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50%30%15%5%
50%
30%
15%
5%
Time-Decay ModelORGANICSEARCH REFERRAL PAID AD DIRECT
50%
30%
10%10%
50%10%10%30%
Position-Based ModelORGANICSEARCH REFERRAL PAID AD DIRECT
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Part Three – How attribution modeling creates value to marketers?Case Analysis
- Customer: Vertical e-Commerce
- Objective: To increase online conversions
- Cost Per Acquisition (CPA): $380
- Promotional Period Oct to Dec 2012
- Promotional Results See below
Channel Consumption Conversion Share CPA
Google – Paid Search $512,236 1,980 31.9% $259 1
Google – Organic Search - 138 2 2.2% -
Baidu – Paid Search $1,403,232 3,123 50.3% 3 $449
Baidu – Organic Search - 29 4 0.5% -
Ad Network $308,983 178 2.9% $1,736 5
Ad Exchange $63,459 760 12.2% $84 6
Grand Total $2,287,910 6,208 100.0% $369
Assume the marketer has no assist from attribution modeling, the results on every channel will be indicated as
follows:
1. Google – Paid Search: CPA is ideal, but recommend to increase budget
2. Google – Organic Search: Low conversion channel generating poor performance
3. Baidu – Paid Search: Key conversion driver, but CPA exceeded and then require to lower CPA
4. Baidu – Organic Search: Low conversion channel generating poor performance
5. Ad network: High CPA but low conversion, exceeded the target CPA, hence recommended to drop this channel
6. Ad exchange: CPA is ideal but low conversion and require to increase budget
Note: The performance �gures are speci�c to this particular case study only. It does not represent the actual performance of the advertising channel in general.
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But with the data provided by attribution modeling, the conversion value of each channel will be truly re�ected as
follows:
Conversion E�ective
Channel Consumption Conversion Share CPA Conversion Share Real Conversion CPA
Google – Paid Search $512,236 1,980 31.9% $259 2,099 33.8% $244 1
Google – Organic Search - 138 2.2% - 287 2 4.6% -
Baidu – Paid Search $1,403,232 3,123 50.3% $449 2,820 3 45.4% $498
Baidu – Organic Search - 29 0.5% - 233 4 3.8% -
Ad Network $308,983 178 2.9% $1,736 590 5 9.5% $524
Ad Exchange $63,459 760 12.2% $84 179 2.9% $355 6
Grand Total $2,287,910 6,208 100.0% $369 6,208 100.0% $367
Main changes of each channel:
1. Google – Paid Search: CPA remains ideal, and e�ective conversions increased slightly
2. Google – Organic Search: E�ective conversion has increased, in other words, this channel can assist other channels
for conversion
3. Baidu – Paid Search: E�ective conversion has lowered, in other words, this channel relies heavily on other channels
for conversion
4. Baidu – Organic Search: E�ective conversion has increased, in other words, this channel can assist other channels
for conversion
5. Ad network: E�ective conversion has increased signi�cantly, in other words, this channel is mostly used for
assisting other channels
6. Ad exchange – CPA has increased signi�cantly, indicating such channel belongs to the last part of the conversion
funnel
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How to make use of attribution modeling to analyze your campaign?
When marketer gained a better idea of the actual conversion value from each channel through attribution modeling,
how he/she should practically apply the insights to optimize the campaign?
Attribution modeling goes beyond just the �rst step of optimization for marketers. In the next step, marketers should
look for relevant insights from other reports. In this case study, the marketer has the following insights and actions:
Insight 1:
Conversion E�ective
Channel Consumption Conversion Share CPA Conversion Share Real Conversion CPA
Google – Paid Search $512,236 1,980 31.9% $259 2,099 33.8% $244
Google – Organic Search - 138 2.2% - 287 4.6% -
Baidu – Paid Search $1,403,232 3,123 50.3% $449 2,820 45.4% $498
Baidu – Organic Search - 29 0.5% - 233 3.8% -
Ad Network $308,983 178 2.9% $1,736 590 9.5% $524
Ad Exchange $63,459 760 12.2% $84 179 2.9% $355
Grand Total $2,287,910 6,208 100.0% $369 6,208 100.0% $367
The actual amount of conversion has decreased in
Baidu Paid Search after analyzed by attribution
modeling, in other words, the conversion from this
channel has in fact bene�ted from the contribution by
other channels. According to the XMO conversion path
report, 7% of the conversion comes from Ad Network
and Baidu Organic Search to Baidu Paid Search. Hence,
the focus of the optimization should lie on the basis of
these two channels instead.
Conversion should take place as below :
Baidu Organic Search:
Based on the keyword search report on the left,
marketers should ensure conversion driven keywords
are included in the paid search campaigns so as to keep
a constant conversion rate.
Baidu Organic Search - Search terms report (Simpli�ed version )
Search terms Cost Conversion Share CPA
Online Shop $ 54,935 184 3.5% $299
Online Shopping Site $ 54,618 137 2.6% $399
Shopping Discounts $ 30,702 74 1.4% $415
Free Delivery $ 18,205 58 1.1% $314
Discounted coupons $ 10,135 47 0.9% $216
Auction $ 17, 691 37 0.7% $478
Other Search Terms $ 1,729,183 4,733 89.8% $365
Grand Total $ 195,468 5,270 100% $363
Rank Conversion path report Share
1 Baidu – Paid Search 143%
2 Google – Paid Search 32%
3 Google – Paid Search → Ad Exchange 9%
4 Ad Network → Baidu – Paid Search 4%
5 Baidu – Organic Search → Baidu – Paid Search 3%
6 ⋯⋯ ⋯⋯
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Insight 2:
Conversion E�ective
Channel Consumption Conversion Share CPA Conversion Share Real Conversion CPA
Google – Paid Search $512,236 1,980 31.9% $259 2,099 33.8% $244
Google – Organic Search - 138 2.2% - 287 4.6% -
Baidu – Paid Search $1,403,232 3,123 50.3% $449 2,820 45.4% $498
Baidu – Organic Search - 29 0.5% - 233 3.8% -
Ad Network $308,983 178 2.9% $1,736 590 9.5% $524
Ad Exchange $63,459 760 12.2% $84 179 2.9% $355
Grand Total $2,287,910 6,208 100.0% $369 6,208 100.0% $367
After the analysis of attribution modeling, the actual
conversion coming from ad exchange platform drops
from 12.2% to 2.9%, which means such channel
bene�ts from other channels in order to get the
conversion.
Rank Conversion path report Share
1 Baidu – Paid Search 143%
2 Google – Paid Search 32%
3 Google – Paid Search → Ad Exchange 9%
4 Ad Network → Baidu – Paid Search 4%
5 Baidu – Organic Search → Baidu – Paid Search 3%
6 ⋯⋯ ⋯⋯
Ad Network Conversion Performance report
Region Cost Conversion Share CPA
Beijing $ 372,417 1,247 20% $299
Shanghai $ 336.163 1,093 18% $308
Guangdong $ 332,110 963 16% $345
Chengdu $ 312,168 749 12% $417
Other $ 953,052 2,156 35% $434
Total $ 2,287,910 6,208 100% $369
Ad Network:
As Ad Network is de�ned as the top-notch “assisting
channel”, it is mostly capable of arousing brand
awareness to acquire new customers.
To enhance the e�ectiveness of Ad Network, marketer
can re-allocate their marketing budget based on
conversion district, as such to allocate more budget to
cities with higher conversion rates such as Beijing,
Shanghai, etc.
From the conversion path report, we can derive that the Google Paid Search is mainly the assisting source for ad
exchange platform. Although Google Paid Search itself is an extremely e�ective channel, there are still some users
who fail to be converted through this channel alone. Hence, it is recommended to adopt search retargeting to ensure
the campaign running in ad exchange can capture the losing users from Google Paid Search.
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Insight 3:
Conversion E�ective
Channel Consumption Conversion Share CPA Conversion Share Real Conversion CPA
Google – Paid Search $512,236 1,980 31.9% $259 2,099 33.8% $244
Google – Organic Search - 138 2.2% - 287 4.6% -
Baidu – Paid Search $1,403,232 3,123 50.3% $449 2,820 45.4% $498
Baidu – Organic Search - 29 0.5% - 233 3.8% -
Ad Network $308,983 178 2.9% $1,736 590 9.5% $524
Ad Exchange $63,459 760 12.2% $84 179 2.9% $355
Grand Total $2,287,910 6,208 100.0% $369 6,208 100.0% $367
From the data analysis combining attribution modeling
and conversation path, it is obvious that Google Paid
Search is a highly e�ectively channel, whether it serves
as a conversion channel itself or assists other
advertising channels to convert.
Therefore marketer may consider to focus on the
optimization e�ort for this single channel, for example,
to perform keyword expansion to boost the tra�c
volume.
Rank Conversion path report Share
1 Baidu – Paid Search 143%
2 Google – Paid Search 32%
3 Google – Paid Search → Ad Exchange 9%
4 Ad Network → Baidu – Paid Search 4%
5 Baidu – Organic Search → Baidu – Paid Search 3%
6 ⋯⋯ ⋯⋯
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Conclusion:
Attribution Modeling may not be able to answer all the questions arose from online marketing. Marketers should
make use of other in-depth data analysis and continuously try out di�erent optimization methods in order to
constantly improve their campaign performance. Below are some suggestions for the marketers:
Identify your marketing objective
Establish a clear and solid marketing objective is the �rst step to success. Is your primary objective based on attracting
new users, improving conversion directly or increasing the return rate of existing clients? Di�erent objectives
determine di�erent attribution models to be selected.
Refer to other reports to generate practical insights
Attribution modeling does not mean automation of all optimization procedures. Marketers should review other
reports (such as conversion path, conversion keyword reports, etc.) to conclude a feasible optimization solution.
Attribution modeling can help understand their product’s conversion funnel
Apart from increasing the conversation quantity, we suggest marketers to try shortening conversion time, for
example, add redirect function, or o�er discounts to those returning users generated from the ad as to increase the
chance of conversion.
Keep trying out di�erent optimization strategies
Invest time to try out di�erent optimization strategies and study their e�ectiveness instead of focusing on building a
perfect attribution modeling.
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Part FourAn Introduction to XMO attribution modeling
iClick’s cross-channel optimization platform, XMO is capable to generate predictive analytics to assist marketers in
marking data-driven marketing decisions. Our product design aims at every detail from ad tracking, data analysis to
optimization. Our product edge include:
- Tracking code:
Capture every interaction of the user, from their �rst exposure to the ad until the last conversion completed to allow
marketer to better understand customers’ online behavior.
- Integrate conversion path with cross-channel analysis:
Provide channel assist report to analyze the relationships among di�erent channels so as to understand the real
value of the channels.
- Provide multi-dimensional and customized conversion funnel analysis:
Marketer can customize their unique conversion funnel to cater to di�erent features of their promotional products,
aiming at increasing the relevance of data analysis.
- Various types of attribution modeling:
Use di�erent attribution modeling on di�erent promotional products, allowing the data analysis to better re�ect
the actual performance.
XMO user can download attribution modeling reports from a range of attribution modeling
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Assist E�ect Report – Better understand the real value of channel conversion Conversion Path – Understand the
frequent conversion path can allow
channel conversion
About iClick
iClick is the leading digital buy-side platform in Asia that integrates search, display, social media and mobile marketing capabilities to allow marketers to plan and manage their cross-channel campaign in one single destination.
Harnessing the power of programmatic buy and ad technology, the proprietary platform XMO (*Cross-marketplace Optimization Platform) is designed to deliver maximum ROI and greatest e�ciency to marketers.
Visit www.i-click.asia and follow us at weibo.com/iclickasiaSales enquiry: [email protected]