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? conversion rate = number of goal achievements 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 2007 Email marketing Affiliate marketing 53% 52.5% 48% 51.5% Paid search 32% 36% Mobile marketing 7% 14.5% Online display advertising 3.5% 6.5% 0% 15% 30% 45% 60% 6
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% 20% 30% 40% 10
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 +(β 1 X 1 + β 2 X 2 + β 3 X 3 ) where X 1 = communication frequency X 2 = training frequency X 3 = customization level f(x) = conversion rate
Non-linear asymptotic model 21
f(z) = b 1 b 2 b Z 3 f(z) = b 1 b 2 e b 3Z ( ) f(z) = b 1 1 e (Z+b 2 )b 3 f(z) = b 1 e (b 2+b 3 Z) f(z) = b 1 e b 2 b Z 3 1 f(z) = b 1 b 2 b Z 3 f(z) = e b 1 b 2 b Z 3 f(z) = b 1 + b 2 e b 3Z f(z) = ( b 1 b 4 1 b 2 e b 3Z ) 1 1 b 4 where Z = f(x)
Non-linear sigmoidal model 23
f(z) = f(z) = f(z) = f(z) = f(z) = f(z) = f(z) = f(z) = f(z) = f(z) = b 1 + b 1 e eb 2 b 3 Z b 3 Z b 1 e eb 2 Z b2 b 1 e e b 3 b 1 e b 2e b 3 Z b 4 Z b 1 + b 2 e eb 3 Z b3 b 1 + b 2 e e b 4 b 1 1+e b 2 b 3 X b 1 1+e b b 3 X 2 b 1 1+e X b 2 b 3 b 2 1+e b b 4 X 3 where Z = f(x)
f(z) = b 1 + b 2 1+e X b 3 b 4 f(z) = b 1 + b 2Z b 2 b b 2 3 +Z b 2 f(z) = f(z) = ( b 1 b 2 +b 3 Z b 4 b 2 +Z b 4 b 1 1+e b b 3 Z 2 ) 1 b4 f(z) = ( 1+e b 1 Z b 3 b 4 ) b4 f(z) = b 1 (1+b 3 e b2 Z ) 1 b4 f(z) = b 1 1+b 3 e b 2 Z f(z) = b 1 ( 1 e b 2Z b 3 ) f(z) = b 1 b 2 e b 3Z b 4 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!