Affiliate Marketing: Maximizing Conversion Rates - A Framework -

Affiliate Marketing: Maximizing Conversion Rates - A Framework -

Affiliate Marketing:
Maximizing Conversion Rates
- A Framework A Dissertation Draft
submitted to the Committee on Doctoral Studies
of the California International Business University
Marc Uhlig
What is the conversion rate?
number of goal achievements
conversion rate =
number of visits
2
What is affiliate marketing?
Online marketing models
- Pay for placement
- Pay per impression
- Pay per click
4
Performance marketing
-Pay per sale
5
Which of the following channels for
driving customer acquisition are very
cost-effective?
2008
53%
Email marketing
52.5%
48%
Affiliate marketing
51.5%
36%
Paid search
32%
7%
Mobile marketing
Online display advertising
2007
14.5%
3.5%
6.5%
0%
15%
30%
6
45%
60%
What percentage of your affiliates
earned commission last month?
up to 5%
more than 5%
37%
63%
7
Pareto rule
- 20% of the affiliates generate 80% of
the affiliate revenues
8
Super-affiliates
Affiliates rate merchant
communication
“Info is kept up to date and is helpful.”
21%
“They don’t communicate enough, but when they do it is helpful.”
37%
“Info is kept up to date, but not very helpful.”
26%
“I am on my own.”
17%
0%
10
10%
20%
30%
40%
Communication
"I use the Commission Junction e-mail function & if
I write to a merchant I would like a reply."
"Email coming from an actual person."
"Direct communication with the merchant
partner."
"Also when the merchant would like feedback."
"Send content for publication."
11
Training
"Tips on how to get more click throughs on web
page banner ad."
"I would like to see better advertising info. About
your product and not so much about how we get
paid. I depend on your banners & links (more links),
because the banners take up to much space and site
load slower. Content links take over ones website."
"Let me know my performance and tips for my site
only."
12
Customization
"For a customer to be able to add multiple items
to a shopping cart system, and from there purchase
the products from the affiliate website."
"Turn-key store modifiable to our look and feel."
"More creative ability to advertise individual
products and having more creative license in
creating ad campaigns."
13
Outline chapter 1
1. Introduction
1.1 Background
1.2 History and genesis of affiliate marketing
1.3 The affiliate marketing model
1.3.1 Entities involved in affiliate marketing
1.3.2 The affiliate profile
1.3.3 General categorization for affiliates
1.3.4 Types of websites used by affiliates
1.3.5 Compensation methods
1.3.6 Pay-Per-Click strategies vs. affiliate marketing program
14
Outline chapter 1
1. Introduction
1.3.7 Specific characteristics of super affiliate
1.3.8 Factors to consider while approving affiliate applications
1.4 Benefits of affiliate marketing
1.5 Success factors for affiliate marketing
1.5.1 Communication
1.5.2 Training
1.5.3 Customization
1.6 Challenges of affiliate marketing
1.7 Conclusion
15
Hypothesis: It is hypothesized that merchants
who maintain higher levels of communication,
provide better induction and training material
and therefore maintain a good relationship
with their affiliate,
tend to have affiliates that can achieve better
overall conversion rates.
Research questions
emanating from hypothesis
Do variables such as level of communication,
amount of training, level of information provided
by merchant and customization of services offered
by the merchant affect the affiliate conversion rate
positively?
How do these variables correlate to the affiliate
conversion rate?
17
Survey questionnaire
- Independent variables
- Communication frequency
- Training frequency
- Customization level
- Dependent variables
- Conversion rate
18
Linear model
19
f (X) = a + (β1 X1 + β2 X2 + β3 X3 )
where X1
=
communication frequency
X2
=
training frequency
X3
=
customization level
f (X)
=
conversion rate
Non-linear asymptotic model
21
f (Z) =
b 1 − b2 bZ
3
f (Z) =
b1 − b2 e−b3 Z
"
!
b1 1 − e−(Z+b2 )b3
f (Z) =
f (Z) =
b1 − e−(b2 +b3 Z)
f (Z) =
b1 − e−b2 bZ
3
1
Z
−
b
b
2 3
b1
f (Z) =
f (Z) =
eb1 − b2 bZ
3
f (Z) =
f (Z) =
#
b1 + b2 e
−b3 Z
1−b4
b1
−b3 Z
− b2 e
1
$ 1−b
4
where Z = f (X)
Non-linear sigmoidal model
23
f (Z) =
f (Z) =
f (Z) =
f (Z) =
−eb2 −b3 Z
b1 e
b1 e−e
−b Z
b2 3
Z−b2
−e b3
b1 e
−b2 e−b3 Z
b1 e
f (Z) = b1 + b2 e−e
f (Z) =
−b Z
b3 4
Z−b3
−e b4
b1 + b2 e
f (Z) =
b1
b
1+e 2 −b3 X
f (Z) =
b1
1+e
f (Z) =
b1
1+e
f (Z) =
−b X
b2 3
b1 +
−
X−b2
b3
b2
1+e
−b X
b3 4
where Z = f (X)
f (Z) =
b1 +
b2
1+e
f (Z) =
b1 +
f (Z) =
f (Z) =
f (Z) =
!
b2 Z b2
b
b32 +Z b2
−b Z
b2 3
1+e
!
!
X−b3
b4
b1 b2 +b3 Z b4
b2 +Z b4
b1
f (Z) =
f (Z) =
−
b1
Z−b3
1+e b4
b1
" b1
4
"b 4
1+b3 e−b2 Z
!
" b1
b1
1+b3 e−b2 Z
f (Z) = b1 1 − e−b2 Z
f (Z) =
4
b3
"
−b3 Z b4
b1 − b2 e
where Z = f (X)
Outline chapter 2
2. Research
2.1 Research methods for data gathering
2.2 Quantitative - experimental designs like surveys
2.3 Research methodology
2.4 Regression models
2.5 Linear multiple regression
2.6 Non-linear multiple regression
2.6.1 Asymptotic regression models
2.6.2 Sigmoidal regression models
26
Outline chapter 2
2. Research
2.6.3 Variables
2.6.4 Correlations
2.6.5 Outliers
2.6.6 Fit of a model
2.6.7 Predictions
2.6.8 Assumptions
2.7 Assumptions and limitations of the study
2.8 Significance of the study
27
Survey
- Start date: 10/09/09
- End date: 20/11/09
28
Survey
- Steps taken
- Broad targeting of survey participants
- Invite individuals within my network
- Twitter
- Facebook
- LinkedIn
29
Survey
- Next steps
- Broad targeting of survey participants
- Press release
- Narrow targeting of survey participants
- Identify and invite individuals engaged in
affiliate marketing on social media platforms
like Twitter
30
Thank you very much!