Session 2 Updates and HW (Mohali)

Hi all,

Session Recap:
Session 2 got done today. We ventured into psychometric scaling and attempted to measure complex constructs using the Likert scale, among others. We also embarked on a common-sensical approach to survey design.

There were some Qs that "jump ahead" in the sense that I hope to cover them in Session 3 - Questionnaire Design. And Qs that seem to want to "force" a 'right' answer in a multiple choice context. Well, one issue with a lot of MKTR is that it is context-sensitive, so its hard to proclaim 'right' answers that will hold true in general. "It depends" is usally a better bet. Wherever possible I do try to point out general principles and frameworks but in many cases, the problem context decides whether something is true or not.

For example, "inferring scale reliability via analysis of demographic profiles" raised quite a few Qs [PsyScaling Q7]. Well, there are product categories where demographics alone can explain enough to evaluate scale relibility on their basis. But in an increasing number of product categories, demographics do not explain product choice very much. In such instances, its hard to conclude definitely about scale reliability on their basis. At least, that was the limited point, I was making.

Study Group Formation details:

• Since there's no project, there's no project group. However, a number of homework activities are group-based, hence pls form HW or study groups.
• Regarding group formation, pls send an email (only one per group) to the AA in the format prescribed.
• To help in group formation, pls find the list of all final registrants for MKTR_146 on LMS.
• If you are unable to find group partners and would like to be allotted to a group, let the AA know.
• Choose a well-known brand as your group name and write your group name next to your PGID and name in the spreadsheet.
• Pls complete the group formation exercise well before the start of session 3.

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Pls read *any 2* of the articles from the business press below. The following 2 HWs are based on the above articles.

• (a) The appeal of 3D movies can lead to a survey estimating preference for -> willingness to pay for -> likely demand for movies in the 3D format among a particular target segment. Here's the management problem sourced from the Economist (July 2011) The appeal of 3D movies - Cinema's great hope
• (b) Here's a desi innovation that might get a huge fillip in demand as demographics start to favor it. Demand soars for a "House-call doctor services" for the elderly and the chronically infirm. Source is Economic times, 2012.
• (c) This Economic times article from a year ago talks about a recent phenomenon they call 'showrooming'.Consumers spot deals in stores, close them online; showrooming threatens to make life difficult for electronics retailers.
• (d) Here's an interesting possibility that requires folks to look at reeeally new products - akin to forecasting email's effect on postal services in 1994 - the impact on small-scale manufacturing of 3D printing services. This too is sourced from the Economist (Dec 2011).
• (e) Here's an interview with the boss of the cafe coffee day chain and he describes some interesting looking initiatives CCD is taking in trying to leverage facebook and other social media to provide speedy feedback on CCD Ops nationwide etc.

HW Part 1: Reducing an M.P. to a D.P. to an R.O.

For each article,

• Q.1.1. write a short description of what a mgmt problem (M.P.) may look like.
• Q.1.2. Write one D.P. corresponding to the M.P.
• Q.1.3. Write an example or two of R.O.s that correspond to the D.P.

HW Part 2: Construct Analysis

• Q.2.1. List a few major constructs you find (if any) in each of the two articles that are of MKTR interest.
• Q.2.2. Pick any one construct you have listed in Q.2.1. and break it down into a few aspects.
• Q.2.3. Make a table with 2 columns. In the first column, write the names of the aspects you came up with. In the second column, corresponding to each aspect, write a Likert statement that you might use in a Survey Questionnaire to measure that aspect.

Session 2 HW submission format:

• Use a plain white blank PPT.
• On the title slide, write your name and PGID.
• For slide headers, use format "HW1: [Article name]" (and so on for the next article chosen)
• Pls mention clearly the Question numbers you are solving in the slide body. Use fresh slides for each new article
• Use a blank slide to separate HW2 from HW1.
• Save the slide deck as session2HW_yourname.ppt and put in in the dropbox on LMS before the start of session 4.

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Session 2 HW part 3 - Survey filling

Pls complete the following two surveys latest by sunday (01-Dec) midnight. I reckon it'll take you max 15 minutes on each survey.

Note: Pls answer as truthfully as you can. The data will be used to illustrate MKTR tools and R's analysis prowess in the classroom. It will *not* be shared with anybody outside the classroom.

Survey 1 (for JSM and perceptual mapping)

Survey 2 (Standard psychographic Personality profile questionnaire)

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Session 3 Preview:
In Session 3 we cover two broad topics. For the first, we continue the "principles of survey design" part and wade into Questionnaire Design Proper. Be sure to read the pre-read on Questionnaire Design as it covers the basics. It'll thus help lighten my load considerably in class. And who knows if there's another pre-reads quiz lurking somewhere in Session 3 as well...

For the second broad topic, we do Data Reduction via Factor Analysis. For this we'll need R. Two ways to get R:

(i) The easy way is to copy the .exe files for both R and Rstudio putup by Ankit on LMS. First install R by clicking on the .exe file and following instructions. Then repeat the same for Rstudio.exe.

(ii) the second way ios to directly download and install R from the following CRAN link for both the Windows and Mac versions:

Download and Install R

Download and install Rstudio (only *after R has been installed)

If you have any trouble with R installation, contact IT and let me know. Watch this space for more updates.
That's it for now. See you in the next class.
Sudhir

Welcome Message and Session 1 Updates (Mohali)

Hi Co2014 @ Mohali,

Welcome to MKTR.

The first session got done today. We covered some subject preliminaries and the crucial task of problem formulation.

Reading for session 2:
"What is Marketing Research" (HBS note 9-592-013, Aug 1991) in the coursepack.

About pedagogy going forward:
The parts of the pedagogy that make MKTR distinctive : pre-reads quick-checks using index cards, in-class reads, this blog and R.

About this blog:
This is an informal blog that oncerns itself soley with MKTR affairs. It's informal in the sense that its not part of the LMS system and the language used here is more on the casual side. Otherwise, its a relevant place to visit if you're taking MKTR. Pls expect MKTR course related announcements, R code, Q&A, feedback etc. on here.

Last year, students said that using both LMS and the blog (not to mention email alerts etc) was inefficient and confusing. I'm hence making this blog the single-point contact for all relevant MKTR course related info henceforth. LMS will only be used for file transfers and email notifications to the class only in emergencies. Each session's blog-post will be updated with later news coming at the top of the post. Kindly bookmark this blog and visit regularly for updates.

About Session 2:
Session 2 deals with psychographic scaling techniques and delves into the intricacies of defining and measuring "constructs" - complex mental patterns that manifest as patterns of behavior. This session also sets the stage for questionnaire design to make an entry in Session 3.

There will be a series of 2 homework assignments for session 2. These concern merely filling up surveys that I will send you (this data we will use later in the course for perceptual mapping and segmentation). Nothing too troublesome, as you can see.

Any Qs etc, pls feel free to email me or use the comments section below.

Sudhir Voleti

End-term updates

Hi all,

Update: R tutorial announcement:

22-Nov Friday 4-6 pm at AC8 LT (tentatively). Will get a venue confirmation and update here. Would be nice if every group is represented at the tutorial.

Sudhir

1. Exam related Cases:

There are two full-length cases in your course-pack: The 'Coop' case, and 'The Fashion Channel' case.

At least one of these two cases will feature in the end-term exam. I'd rather you not try to read the case for the first time in the exam hall. Pls read them at home beforehand.

Preferably, discuss them in a group on the lines of the following Qs:

• What is the management problem? Describe also the major symptoms.
• What are some of the likely decision problems (DPs) that emerge based on the management problem?
• List a few research objectives (R.O.s) that emerge based on the DPs.

2. End-term exam pattern Notes

• There are a total of 50 Qs, 2 marks each.
• The Qs are broken down into 8 Question-sets, each having tables or figures and Qs based on them
• The Qs are all short-answer - True/False, fill-in-the-blanks, write expression for ...., name these factors, type of stuff.
• If any Q comes from any pre-read, the concerned pre-read will be specified in the Q itself. So bring your course-pack to the exam. Not all pre-reads are relevant, only the ones I've specifically asked you to read. Properly speaking, those pre-reads are a part of the course.
• Nothing that was not covered in class will show up anywhere in the exam.
• At least one question set relates to a full-length case (see above)
• Time will not be a problem - you'll have 150 minutes for a 120 minute paper.

Pls use the comments section to this post for any Q&A so that it is visible to the class at large.

See you in class for our last classroom meeting. Any feedback you have on how to improve any aspect the course etc is welcome at any time.

3. R tutorial and R in your resume:

From the project point of view, if you want an R tutorial at anytime between now and 24-Nov (when I leave for Mohali), pls let me know. A quorom of minimum 5 people must signup for the tutorial which can go as technical as the attendees want. Ideally, one person from each project group would attend.

If you want to include R in your resume, then provided that you have made a good-faith attempt at installing and running R for your HWs, provided that you intend to continue to invest in R going forward and provided that you have been able to read the code sent and get a "sense" of the analysis, pls consider amending and using any relevant subset of the following (as applicable):

• State what you have done w.r.t R:
• Have developed a familiarity with the R environment
• Have used R to apply and analyze a wide variety of Mktg Research tools (from structured hypothesis testing to text analytics and social media analysis)
• Have gained some understanding of the flexibility and extensibility of the system (installing and using packages and interfaces with external repositaries)
• Have analyzed a full credit course project on the platform
• State what you will do going forward:
• Intend to continue investing in and developing greater insights into the R platform
• Are attracted by the low-cost, license-free unrestricted use terms and rapid-analysis capabilities of the open-source platform
• Believe in R's promise of substantially expanding enterprise analytics capabilities while keeping a tight lid on costs
• Believe in the philosophy of collaborative design, rapid rollout and innate scale-ability
• Bottomline: are convinced of R's compelling cost/benefit calculus for delivering enormous value to the organization

Again, folks, ensure that *only* that subset that applies to you in a bona fide way is used for your statements of purpose, on the resume etc. Making false claims has a habit of coming back to bite you at inconvenient times.

Good luck for the exam and going fwd for the placements as well.

Sudhir

Session 9 Updates

Update:

Hi folks, pls install java on your machines. Needed for rJava and text analysis packages to run. Alos, you'll need to have a twitter account to use twitteR. Just saying.

Announcement 1:

Your practice exam is up on LMS. No solution will be provided. Expect a similar Q pattern in the end-term.

Announcement 2:

This famous article from Wired magazine 'The Long tail' by Chris Anderson is the reading for Session 10. Its an excellent article on a new economic paradigm enabled by technology. Pls read and come, I will discuss both the McKinsey article pre-read for Session 9 and this one in Session 10. Also, a pre-read quiz may be lurking round the corner...

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Hi all,

This is a hurried post, and will deal mainly with the HW part of session 9.

There are two parts to Session 9 HW. Part 1 deals with plain descriptive analysis of session 2 survey data. Part 2 involves extracting web data from amazon product reviews, and then analyzing it. Here we go:

HW part 1:

• First ensure all the packages required are installed. If you're having trouble, given the paucity of time, run your HW off a friend's machine.
• Open 'Session 9 HW part 1 R code.txt'.
• Open excel file 's2 survey data for s9 HW.xls'.
• The first worksheet 'Questions reference' gives the 4 Qs and associated Q numbers that you'd answered.
• The second worksheet contains your data itself as 4 columns (one for each Q)
• Copy paste and save each column's data on a notepad. Since survey data from websurveys routinely come in the form of .csv files, the point here is get you to go from .csv to .txt to R.
• Read the notepad into R and run the relevant R codeon it
• Make a corpus-level wordcloud and dendogram, see if any broad themes emerge from them. Write a few lines on these.
• Repeat the exercise with the same code for the other 3 columns

HW part 2:

• Open 'Session 9 HW part 2 R code.txt'.
• Check the URL given in the code - does it work - what page opens on a browser?
• Run the code given to extract the data from the webpage
• Check is the saved data look OK etc
• Now perfrom downstream analysis as given in the code sent.
• Execute R code line by line reading the commentary given to get a sense of the analysis flow
• Make a corpus-level wordcloud and dendogram, see if any broad themes emerge from them. Write a few lines on these.
• Segment the reviewers.
• Run sentiment analysis for positive and negative words by segment.
• What themes emerge in the sentiment wordlcouds by segment? Are the segments distinct in their needs and focus?
• Optional but additional points for trying: Install twitteR
• Search for "xbox" on twitter. Collect some 100 tweets
• Run descriptive analysis on the tweets.
• Submission guidelines:
• Paste the plots and your analysis on PPT and submit in the relevant dropbox.
• Name the PPT session9HW_yourname.ppt
• Title slide should contain your name and PGID
• Submission deadline is this Thursday midnight.

Shall update this post as more info (e.g., queries regarding the project or the end-term) comes in. Watch this space.

Sudhir