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Marketing Analytics – Stage 1

Marketing Analytics – Stage 1 (previously Marketing Analytics – an Introduction) is the basic Marketing Analytics one (1) day short course for beginners and those seeking refreshment in Marketing Analytics.

Marketing analytics is the analysis of data that leads to improved marketing performance. Virtually all firms use marketing analytics of some sort, which can be as simple as spreadsheet operations or using advanced statistical software. With almost limitless sources and volumes of consumer data available, it is imperative now more than ever to use marketing analytics for a competitive edge. This course will utilize cutting edge and traditional methods to analyze consumer data. We will be looking at Surveys, Target Marketing, Consumer Choice Modeling and regression in two three-hour sessions. This course uses an interactive, hands approach and will be held in a computer lab with all necessary software and data sets provided.

This program is particularly useful for
This program is particularly useful for all those involved or interested in marketing analytics for their organisation:

Industry Practitioners
Students, Researchers, Academics

Program topics

Surveys, Regression Analysis, and Target Marketing
Target Marketing
Consumer Choice Modeling
Choice Modeling and Logistic regression

Course outcomes
Upon completion of this course students will:

Understand how to analyze survey data and ensure analytical results are representative of the market
Understand consumer choice and how specific segments respond to changes in the marketing mix
Determine a customer’s willingness to pay for a product or service attribute and how to rank the importance of attributes

Prerequisites: Pre-reading

Held in a UTS computer lab – software provided

Presenters

Dr. Ingo Bentrott – BA (Berkeley), MA (Iowa), PhD (UTS), Lecturer, School of Marketing, UTS

Ingo is currently a lecturer in the Marketing Discipline group at the University of Technology, Sydney. He is a Marketing and data science professional with many years of “big data” experience, and has worked comprehensively with relational databases and other large, unstructured data systems. Ingo’s area of expertise is using data mining in marketing research and fraud/anomaly detection, and he has over 12 years of industry experience in manufacturing and in marketing research. Ingo has a blend of commercial, academic, and international experience which creates distinctive approaches in the use of data mining in marketing, such as creating hybrid data mining and discrete choice models. Ingo looks at ways to improve marketing models with preference heterogeneity and missing data by using data mining to detect important, localized interactions, which have been shown to improve model accuracy and profitability for companies.

Ingo has a blend of commercial, academic, and international experience which creates a distinctive approach in the use of data mining in marketing. He creates hybrid models of data mining analysis with discrete choice models. Ingo looks at ways to improve marketing models with preference heterogeneity and missing data by using data mining to detect important, localized interactions, which leads to improved model accuracy and profitability for companies.

Additional Information

Assessment within Short Course
Post Short Course follow up and engagement
Survey and feedback process
Online readings

Fees

Standard 1 day $800 (GST free)

UTS Alumni and staff- 10% discount
2 or more from the one organisation – 15% discount
Interstate participant – 25% discount
Enrol in any 2 stages – 5% discount in addition to discount already eligible (upfront payment)
Enrol in all 3 stages – 10% discount in addition to discount already eligible (upfront payment)

Please select discount option with drop down box before entering your credit card details. Only 1 discount applicable per person.
Group bookings must be made individually with the 15% discount selected and credit card processed separately for each person.

Credit Card – proceed to the ‘BOOK NOW’ button and follow the prompts

Payment Options :
To be invoiced – Please complete the Manual Enrolment on Invoice Request Form and email short.courses@uts.edu.au or Tel: +61 (02) 9514 2913.

Contact Information
For specific queries regarding course content, please contact Colin Wise, Advanced Analytics Institute Tel: +61 (02) 9514 9267 or email colin.wise@uts.edu.au with questions relating to this course.

https://shortcourses-bookings.uts.edu.au/ClientView/Schedules/ScheduleDetail.aspx?ScheduleID=1921

When

2nd April 2015 09:00 am
To 2nd April 2015 05:00 pm

Where

UTS
235 Jones Street, Ultimo
Sydney 2007

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