Instructor Newsletters

Volume 2, Number 1

Posted in Instructor Newsletters

With the spring semester well underway, our Marketing Engineering team has been busy further improving our products. A new software release, new case and a new model await your review. We appreciate your continued support and always look forward to your suggestions to further improve Marketing Engineering.

This issue contains:

  • ME>XL News:
    • Release 1.5 is now available. This release introduces a new model, Latent Class Segmentation, along with several other minor enhancements to other our models.
    • A new case, Ford Hybrid Car, is included in Release 1.5 giving students exposure to new product forecasting using the Bass model.
  • Instructor Forum:
    • Daniel Soto, marketing research consultant and instructor at Essec Business School shares his Marketing Engineering experience.
  • Upcoming Events:
    • Webinar: Customer Lifetime Value with ME>XL May 20, 2009
    • Webinar: Advanced Tips and Hints using ME>XL July 15, 2009
    • Live Seminar at EMAC May 26, 2009
    • Live Seminar at Marketing Science June 4, 2009

To connect with us, please contact us through the support center.

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All the best,
Gary Lilien, Penn State University 
Arvind Rangaswamy, Penn State University

Arnaud De Bruyn, ESSEC Business School 

Marketing Engineering for Excel News

We are pleased to announce Marketing Engineering for Excel Release 1.5, available for download in the instructor section of our website.

Included in this release in a new Ford Hybrid Car case, a topical case which allows students to work with our Bass forecasting model for forecasting the time path of adoptions of products and technologies. If you missed Dr. Rangaswamy’s recent webinar on Bass (March 18) you’ll find it at our website under Archived Webinars.

While several minor enhancements are included with this release, of particular note is our new Latent Class Segmentation model. This model may be advanced for some of your students, but we hope it may be useful for your research, or use by your more advanced students. Latent class segmentation techniques reveal segment structures among customers that are unknown a priori. Thus, LC segmentation is particularly useful for determining unexpected groupings of customers that may point the way to new ways of identifying and targeting customers. Our implementation of LC supports variables of mixed scale (both nominal an interval-scaled variables), not available in our standard segmentation. Also, it allows you to explore numerous segmentation solutions with a single run, which enables automatic determination of number of segments, as well as identification of niche segments in the market. However, typically, LC segmentation requires more data (more respondents) than traditional segmentation methods.

Marketing Engineering: My Teaching and Consulting Experience

Daniel Soto, InSites Consulting, Belgium and ESSEC Business School, France
This email address is being protected from spambots. You need JavaScript enabled to view it.

I have been involved with Marketing Engineering since 1999 and am delighted to provide some commentary. Over the course of the past nine years I have seen a dramatic improvement in usability and flexibility that impacts both my teaching experience, and my professional use of the tool.

I am a full time marketing consultant/analyst at InSites Consulting, in Ghent, Belgium and a part time instructor at ESSEC Business School in France, near Paris and I use the Marketing Engineering software in both venues. As a marketing professional, I particularly appreciate the ease of use and flexibility of the software; since Marketing Engineering is now fully integrated into Excel, it makes the transition from analysis to client reporting very simple. There are many benefits to me as an instructor which I will summarize below.

In my teaching experience, I have found that marketing is misperceived by many students; in particular many are unaware (or skeptical) of the analytic and scientific aspects of the field. Marketing Engineering provides an ideal entree into analytical marketing without overwhelming the students with mathematical complexities.

The course we offer at ESSEC focuses on segmentation, targeting, positioning, conjoint analysis, resource allocation, and Customer Lifetime Value. This mix exposes students both to the most widely used techniques in marketing, and to two of the main challenges companies face in today’s economy: customer value assessment and resource allocation. While ESSEC students learn about these concepts in a (generally) descriptive, qualitative introductory course, in our Marketing Engineering course, they see what it takes to create a perceptual map, design a segmentation and targeting program or develop and defend the allocation of resources in a marketing budget structure. I believe this experience is invaluable for future executives.

As much as possible, I stress that, although they may not choose to become marketing analysts or consultants, in order for to ask the right questions, they must understand generally how to obtain information from data (and judgments). Quantitative marketing can be challenging for students, but I rarely refer to the mathematics beyond the tools during class, unless students ask (and some do). We also barely talk about the software; indeed, the tutorials in the software do a fine job of teaching about the software and students can work those at their leisure. In class, I focus on problem identification and framing the problem in a fashion that readily admits analysis. I only talk about the software during the first session to make sure students get familiar with the interface. However, I often refer to the options in the software as many of those options make teaching points (why does the software have an option to standardize the data in segmentation/cluster analysis? What do the constraints mean in Resource Allocation? etc.?) Indeed, I think Marketing Engineering provides a valuable framework to lead students towards asking the right questions. To me, this framework is often the most valuable lesson students can take from the course.

When I compare Marketing Engineering to more widely known commercial packages, it is clearly much simpler and permits students to get to a "quick and dirty" answer with little fuss. I would both need a teaching assistant and, likely, separate software tutorial classes if I taught with one of Marketing Engineering's commercial competitors.

My favorite piece of software is the “Positioning Analysis” tool. It is the best implementation I have come upon (commercial or otherwise), and I use it frequently in my commercial practice. The use of Excel is at the core of InSites' commercial activities, and the integration of the Positioning tool in this environment is a huge time saver. The charts are also easy to customize and adjust to our reporting needs. Students find the tool easy to use and – after some thorough explanations – to interpret. Hence, I can bring very recent commercial experience with the same tool they are using to the classroom, addressing student skepticism about the "applicability" of what they are learning. Positioning Analysis is the most popular tool in the Marketing Engineering suite among my students (more than half use it in some way their term project).

If you would like more information, I would be happy to share more my experience with teaching this exciting material in more detail please contact me at This email address is being protected from spambots. You need JavaScript enabled to view it..

Upcoming Events

Our Instructor Webinar Series continues, with two upcoming sessions of interest:

May 20, 2009 Webinar: Customer Lifetime Value with ME>XL
July 15, 2009 Webinar: Advanced Tints and Hints using ME>XL

To enroll in either of the above webinars, or view any of our previously recorded webinars, please visit our webinar page.

We will also have two live seminars coming up. If you’re planning to attend either EMAC or Marketing Science, please consider joining us.

May 26, 2009 Live Seminar at EMAC (Audencia, Nantes, France)
June 4, 2009 Live Seminar at Marketing Science (U. Michigan, Ann Arbor)

For more information on these live events, please visit