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Instructor

Allen Dwayne Ball, Instructor - Retail Customer Acquisition

Allen Dwayne Ball

Dr. A. Dwayne Ball has been teaching and consulting in marketing for over 30 years. After receiving a PhD in mathematical psychology from the Ohio State University, he spent four years managing consumer research at Procter & Gamble, and then moved to the University of Nebraska, from which he retired in 2017 as professor emeritus. Dr. Ball developed the first courses at the University in strategic database marketing and advanced marketing analytics, which he still teaches, and has consulted with many companies small and large.

How to acquire valuable new customers in retail settings.

  • Instructor received PhD in mathematical psychology from the Ohio State University, he spent four years managing consumer research at Procter & Gamble, and then moved to the University of Nebraska, from which he retired in 2017 as professor emeritus. 
  • Learn how to value customers financially, and to recruit financially valuable new customers. 

Course Description

Online or bricks-and-mortar: - Measuring and identifying the best customers and prospects, - Using analytic tools and databases to identify the best prospects for new customer acquisition, - Covering all of the situations in which you have or do not have access to vendor databases, time for testing acquisition approaches or not, and access to the use of multivariate or machine learning algorithms or not. - Working knowledge of the programming/analytics language R is assumed.

What am I going to get from this course?
Understand how to value customers financially, and to recruit financially valuable new customers.  It covers situations where you do or do not have access to vendor databases of potential customers, time to test acquisition promotions, or access to multivariate techniques such as regressions and neural nets.  You will learn how to use the programming/analytics language R to analyze customers, select customers from vendor databases, and mine test promotions to achieve efficient acquisition of valuable new customers.  The point is to recruit as many of the most valuable new customers as you can afford to, so you can improve the value of the firm as rapidly as possible.

Prerequisites and Target Audience

What will students need to know or do before starting this course?
You need to know the basics of retail operations, the basics of the R programming language, statistics up through multiple OLS regression, how to use Excel spreadsheets, and have knowledge of, or access to legal advice on, customer privacy law.
Who should take this course? Who should not?
If you work for an on-line retail organization or a bricks-and-mortar retail organization that wants to grow its customer base with valuable new customers, this course is for you.

Curriculum

Module 1: : Actual Module 1: Introduction
Lecture 1 Actual module 1: Introduction (Syllabus is under "Resources")
01:43

This course teaches you to understand how to value customers financially, and how to recruit financially valuable customers in situations where you do or do not have access to vendor databases of potential customers, time to test acquisition promotions, or access to multivariate techniques such as regressions and neural nets.  You will learn how to use the programming/analytics language R to accomplish this.  The point is to recruit as many of the most valuable new customers as you can afford to, so as to improve the value of the firm as rapidly as possible. You should have already under your belt: Some knowledge of the retail decision environment (bricks and mortar or on-line). Some knowledge of the programming language R. Some knowledge of statistical methods up through OLS multiple regression. Some knowledge of customer privacy law in your local environment, or access to expertise on the topic.

Module 2: Actual Module 2: Customer data
Lecture 2 Customer Data
14:20

Describes typical structure of customer data files and introduces a sample master customer file for an imaginary retail business in .csv format Excel knowledge required), reading it into R using the R Studio graphical user interface, and summarizing it. Also introduces a products file.

Module 3: Actual Module 3: Purchasable Consumer Data
Lecture 3 03. Purchasable Consumer Data
11:33

The various sources of customers data, strategy of what to purchase, and a discussion of costs.

Module 4: Actual Module 4a. Customer Valuation by Customer LIfetime Value, Part I
Lecture 4 4a. Customer Valuation by Customer Lifetime Value, Part I
19:53

This is part 1 of a discussion on how to calculate Customer Lifetime value, In order to cherry-pick good future customers from among your non-customers, it is extremely helpful to have a measure of “good.” That is, what is the value of a customer to you now, and what is your best projection of his or her value into the future? The best available measure of “goodness” is Customer Lifetime Value, variously known as LTV or CLV. Under "Resources" you will find an incomplete Excel spreadsheet you can use to follow along with the lecture and build your own CLV calculation spreadsheet. Part II (module 5, called "4b") fills in the remainder of the discussion of how to use CLV and why it is the preferred measure when it is possible to calculate.

Module 5: Actual Module 4b. Customer valuation by customer lifetime value, Part II..
Lecture 5 4b. Customer valuation by Customer Lifetime Value, Part II
06:49

This short module finishes the calculation of CLV and addresses why CLV is the superior measure of customer valuation and how it can be used.

Module 6: Actual module 5. Customer Valuation by other methods
Lecture 6 5. Customer Valuation by other measures
11:29

Customer Lifetime Value, the subject of the last modules, is sometimes difficult or impossible to calculate. So, here is a collection of other measures of individual customer value that can be used to identify “good” non-customers for acquisition – not as connected to firm value, but workable. In future lectures, when we use CLV as our measure of customer value, you can, if you must, use one of these.

Module 7: Actual Module 6. Overview of Methods for Acquiring New Customers
Lecture 7 6. Overview of methods for Acquiring New Customers
07:13

How you go about acquiring new customers will depend upon whether or not you have a good customer database (and can thus calculate and use a measure of customer value), 2) whether or not you have access to a good vendor database of noncustomers at reasonable cost, 3) whether or not you have time available for running a test and data-mining the test results, and 4) the which analytic techniques you have the software, data, and competence to use. This module discusses which of the following modules will be of most use to you, given your situation.

Module 8: Actual module 7. No Vendor Data, No Testing, No Multivariate Methods
Lecture 8 7: Customer database, but no access to vendor databases, not time to test, and no multivariate analysis
12:50

Here you are still in a bit of a bad spot. At least you have a reasonably large customer data base, but you can’t afford to access vendor data bases of non-customers, you can’t afford either the time or expense for testing, and you don’t have the software or the expertise for multivariate data analysis. So, we’ll do the best we can with what we’ve got, which may not be particularly effective.

Module 9: Actual Module 8: No Vendor Data, No Multivariate Methods, But Time for Testing
Lecture 9 8: No Vendor Data, No Multivariate Methods, But Time for Testing
05:23

If you haven’t already, you should review module 7, because this one is just a variation on it. Here, you don’t have access to a vendor database or multivariate methods, but you do have time and resources to run tests to find the most effective means of new customer acquisition among those available to you.

Module 10: Actual Module 9a: Vendor Data, But No Multivariate Methods and no Time for Testing Part I
Lecture 10 9a: Vendor Data, But No Multivariate Methods and no Time for Testing Part I
23:26

This situation is somewhat better than the previous ones, because we can use vendor databases to both enhance the information we have on our current customers, and also to cherry-pick the consumers from the vendor databases that look like our best customers. The cherry-picking is less efficient, because we can’t use multivariate methods, only logical “IF” type statements. Furthermore, since we can’t spend the time for testing, we can’t refine our approach to cherry-picking. But, the use of vendor databases represents a significant improvement in our efficiency of valuable new customer acquisition.

Module 11: Actual Module 9b: Vendor Data, But No Multivariate Methods and no Time for Testing Part II
Lecture 11 Actual Module 9b: Vendor Data, But No Multivariate Methods and no Time for Testing Part II
12:09

This situation is somewhat better than the previous ones, because we can use vendor databases to both enhance the information we have on our current customers, and also to cherry-pick the consumers from the vendor databases that look like our best customers. The cherry-picking is less efficient, because we can’t use multivariate methods, only logical “IF” type statements. Furthermore, since we can’t spend the time for testing, we can’t refine our approach to cherry-picking. But, the use of vendor databases represents a significant improvement in our efficiency of valuable new customer acquisition.

Module 12: Actual Module 10a. Vendor Data, Time for Testing, But No Multivariate Methods Part I
Lecture 12 10a. Vendor Data, Time for Testing, But No Multivariate Methods, Part I
11:14

Even better, now we have the time to test, which will allow us to do some data-mining of the results of that customer acquisition attempt to refine our customer acquisition strategies when we “roll out” the full promotion. Our approach here will be to: Send a test promotion to a large random sample of non-customers in our vendor database, and Mine the results of that customer acquisition attempt to try to maximize the return on our costs of customer acquisition. However, the lack of multivariate methods means we could still do much better.

Module 13: Actual Module 10b. Vendor data, time for testing, but no multivariate analysis
Lecture 13 Actual Module 10b. Vendor Data, Testing, but no multivariate analysis, Part II
15:54

Continuation of Topic 10a.

Module 14: Actual Module 11. Vendor Data, Regression Methods, but No Time to Test
Lecture 14 11: Vendor data, regression methods, no time to test
19:24

We have another big improvement in our fortunes, which is the availability of regression methods. OLS regression (or some other form you might choose to use) can be used to predict the CLV of a non-customer, as part of the decision of whether or not to attempt to acquire him/her. That will make our customer acquisition more efficient, in terms of return on investment, than the cruder forms of data-mining seen in earlier modules. However, in this module we have assumed there is no time for testing, so we have no opportunity to mine the results of a test and refine our decisions about whom to approach in vendor databases.

Module 15: Actual Module 12a. Vendor Data, Regression Methods, Time to Test, Part I
Lecture 15 12a. Vendor Data, Regression Methods, Time to Test, Part I
17:56

Now, we are really in the catbird seat. We have vendor data, we can use regression methods, and we have time to test. This will make the customer acquisition activities a bit more complex, but far more efficient. Furthermore, we can predict the financial results of the final roll-out of the customer acquisition attempt with reasonable accuracy.

Module 16: Actual Module 12b. Vendor Data, Regression Methods, Time to Test, Part II
Lecture 16 Topic 12b. Vendor Data, Regression Methods, Time to Test, Part II
15:54

Continuation of 12a.

Module 17: : Actual Module 13a: Vendor data, Neural nets but no time to test
Lecture 17 13a: Nerual Nets, but no time to test
14:34

In this case, we will learn a new tool, neural nets. Unfortunately, without time to test. we lose a good opportunity to make the new customer acquisition really efficient, but we will be testing in the next module.

Module 18: :Actual Module 13b: Neural nets, notime to test, Part II
Lecture 18 Neural Nets Testing
13:12
Module 19: : Actual Module 14a: Vendor data, neural nets, time to test, Part I
Lecture 19 Actual Module 14a: Vendor data, Neural Nets, and time to test
12:42

The most powerful situation. We have a powerful and flexible multivariate method, access to vendor data, and time to test.

Module 20: : Actual Module 14b: Vendor data, Neural nets, time to test, Part II
Lecture 20 Actual Module 14b: Vendor data, Neural nets, time to test, Part II
14:14

Continuation of actual module 14a.

Module 21: : Actual Module 14c: Vendor data, neural nets, time to test, Part III
Lecture 21 Actual module 14c: Vendor data, neural nets, time to test, Part III
13:08

Continuation of actual module 14b.

Module 22: :Actual module 15: Automated Marketing and Machine Learning
Lecture 22 Actual module 15: Automated Marketing and Machine Learning in Customer Aquisition
18:47

Teaching all of the software necessary to achieve automatic marketing and machine learning in the customer acquisition problem would be well beyond the scope of this course. However, we can present the conceptual framework for that approach here.

Reviews

6 Reviews

Empty user
yu L

August, 2017

An appropriate program for retail professionals. It challenges the beginner to work on his or her own to learn more. It is a great preparatory course for embarking on the retail profession Some best practice concepts are included, too. One of the best courses i've taken on how to get invaluable new customers in retail environments.

Empty user
Thomas P

August, 2017

I was carried away by the instructor's enthusiasm, knowledge and teaching skills. Great course. By following this course we can come to know how to evaluate clients financially, and to gain financially valuable new customers.

Empty user
Sharath Reddy V

August, 2017

I picked up a lot about measuring and knowing the best customers and prospects, and running analytical means and databases to find the best prospects for new customer acquisition. Very interesting even if a little complex at times

Empty user
Thomas P

August, 2017

A really insightful course on dealing with all of the times when you have reach to vendor databases, time for testing acquisition means or not, and gain access to the use of multivariate or machine learning algorithms.

Empty user
Jorie S

October, 2017

If you need to figure out the best way to acquire new customers, this is your course! If you don't have access to databases of non-customers, this course will show you how to make the most efficient use of your promotional dollars to acquire new customers. If you have access to supplier databases, this course shows you how to use simple IF statements, and multivariate methods up through neural nets to identify the best people to try to acquire. Customer lifetime value is a concept used throughout, but if you can't calculate that, you can use whatever customer value measure you've got. The instructor even shows you how to use the R language to do all this. Best course I've taken so far!

Empty user
Jan O

October, 2017

This course is easy to follow and covers all that you need to know about the analytics of retail customer acquisition. The course covers a lot of current data sources for finding new customers, and then how to cherry pick the most promising, high-value prospects to acquire. All the possible cases are covered, from analysis useful for mass marketing, all the way up through using neural nets to identify the best prospects. Overall a complete course and I highly recommend it to anyone who is interested in this topic! Tip: Instruction in the language R is included, but at a higher-than-basic-level, so you should know some R.

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