Part 1: Inflow - acquiring new customers
Our focus is direct marketing, so we will not look at advertising campaigns but instead focus on understanding marketing campaigns (e.g. direct mail). This is the foundation for almost everything else in the course. We look at measuring and improving campaign effectiveness including:
- The importance of test and control groups. Universal control group.
- Techniques: Lift curves, AUC
- Return on investment. Optimizing marketing spend.
Part 2: Base Management: managing existing customers
Considering the cost of acquiring new customers for many businesses there are probably few assets more valuable than their existing customer base, though few think of it in this way. Topics include:
1. Cross-selling and up-selling: _Offering the right product or service to the customer at the right time._ - Techniques: RFM models. Multinomial regression. - b. Value of lifetime purchases.
2. Customer segmentation: _Understanding the types of customers that you have._ - Classification models using first simple decision trees, and then - random forests and other, newer techniques.
Part 3: Retention: Keeping your good customers
Understanding which customers are likely to leave and what you can do about it is key to profitability in many industries, especially where there are repeat purchases or subscriptions. We look at propensity to churn models, including - Logistic regression: glm (package stats) and newer techniques (especially gbm as a general tool) - Tuning models (caret) and introduction to ensemble models.
Part 4: Outflow: Understanding who are leaving and why
Customers will leave you – that is a fact of life. What is important is to understand who are leaving and why. Is it low value customers who are leaving or is it your best customers? Are they leaving to competitors or because they no longer need your products and services?
Topics include: - Customer lifetime value models: Combining value of purchases with propensity to churn and the cost of servicing and retaining the customer. - Analysing survey data. (Generally useful, but we will do a brief introduction here in the context of exit surveys.)
The students are expected to be comfortable using R and understand basic marketing concepts.
Students should have access to a recent version of R with the additional packages gbm, caret, and survey installed with their dependencies and suggested packages.
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course - Introduction to Data Visualization with Tidyverse and R
Well thought out and high grade planning materials.
Andrew - Office of Projects Victoria - Department of Treasury & Finance
Course - Forecasting with R
Wasn't boring, the trainer could keep the attention, the topics were covered in depth.
Marta - Ministerstwo Zdrowia
Course - Advanced R Programming
Very tailored to needs.
Course - Data Mining with R
The subject matter and the pace were perfect.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
At the end of the class, we had a great overview of the language, we were provided tools to continue learning and were provided suggestions on how to continue learning. We covered AI/ML information.
Victor Prado - Global Knowledge Network Training Ltd
Course - R
the clarity with which he explained the entire course, as well as the willingness to return to the syllabus when necessary
Carlos Eloy - AMERICAN EXPRESS COMPANY MEXICO
Course - Data Analytics With R
It was very informative and professionally held. Wojteks knowledge level was so advanced that he could basically answer any question and he was willing to put effort into fitting the training to my personal needs.
Sonja Steiner - BearingPoint GmbH
Course - R Programming for Data Analysis
The trainer was so knowledgeable and included areas I was interested in.
Course - Data Mining & Machine Learning with R
Elena Velkova - CEED Bulgaria
Course - Predictive Modelling with R
Good detail on what R is used for and how to start using it right away