Group Homework for Session 3 - Using APIs

Class,

First, some context. Recall the Google maps example we did for spatially plotting commercial entities of interest in Hyderabad.

There, we were trying to know the distribution of purchasing power over Hyd [or more generally, *any* other] city. How to know – quickly, cheaply, scaleably and reliably?

i. Replicate that classwork example at home. Download code from Linkstreet. Pls view the Linstreet video on how to create your own account and get data.

ii. Now pick a city as your focal city. Any city except Hyderabad (since it's already done in class).

iii. You are consulting for a client who is a major hospital specializing in cardiac care. The client wants to advertise their emergency numbers, ambulance services etc.

iv. The client wants to build/hire 4 billboards (hoardings) on which to display its messages. Client asks you to look for 4 optimal billboard locations.

iv. Profile your client's target segment, who could be either individuals or organizations [e.g., lower, middle or upper SEC; high net worth Individuals; startups, SMEs, service businesses such as in education or healthcare, large MNCs etc]

v. Pick a list of entities from the entity list in Google places API that could serve as proxies for the presence / purchasing power / needs of your target segment. Pick around 2-3 proxies in all. E.g., in the classwork example, we picked banks, malls and hospitals as proxy entities to indicate nearby presence of middle and upper middle class SEC population.

vi. Collect data on these proxy entities in the focal city from the Google Maps API and plot them on Google maps. Interpret what the map is saying.

Your deliverable will be a markdown document in HTML form ( a webpage basically) with these maps' screen caps should be visible.

Highlight at least 4 areas of particular interest for your client. In markdown documentation, explain why your chose those areas as interesting for your client.

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Deliverable:

Your markdown submission should ideally cover the following:.

a. Title and detail: City and your Client's Business. Also, names and roll numbers of group members. Name the webpage as group_name.html [Pick a group name if you haven't already]

b. Problem Formulation: State in brief your client's business problem, using, say 1 D.P and 1-2 R.Os

c. Description: State why you picked your focal city.

d. Entity List: List the proxy entities you are going to search for. Justify your list in 1-2 lines for each entity type you have chosen.

e. Results: Ensure google map with proxy entities on it is clear. Highlight which areas of interest you have chosen. Choose 4 promising areas.

f. Interpretation: Justify your choice for the areas picked in a few lines.

g. Bonus points if you could build a distance matrix, cluster the proxy entities and display the clustered entities in a separate map. [Check the classwork for this, I did something similar there].

h. Code: Ensure you submit your code inline in the markdown which we can test and run using our AppIDs here.

i. Submit the document in the dropbox before deadline. Or upload a text doc containing Rpubs URL and group details into the dropbox

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Deadline is midnight of Saturday, 12-March-2016.

Any queries etc, contact aashish_pandey@isb.edu or me. Use the comments sections for general FAQs.

Sudhir

Individual assignment for Sessions 1-2

Hi Class,

A series of Assignments are coming your way. This is your first individual assignment (i.e., one submission per student).

Pls watch this ~ 20 minute video carefully. It features Scott McDonald of Condé Nast holding fort on where Marketing Research is headed in the next decade.

“Social Technological and Economic forces affecting Marketing Research over the next decade”

Now, for your HW, pls answer a few simple Qs (True-False, fill in the blanks variety) about the above talk in the following survey:

Questions based on the video

Some Notes:

(i) This is an individual-only assignment. Since it involves no R/Python, consulting peers is not permitted.

(ii) I found that using earphones works great in making out what the speaker is saying much more clearly than ordinary speakers. FYI.

(iii) Deadline: The assignment should be completed and submitted latest by midnight 06-March Sunday.

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

Sudhir Voleti

Group Assignment for Sessions 1-2

Class,

This group homework is based on (a) Session 1 - problem formulation, (b) Session 2 - survey questionnaire design and part of (c) Session 3 - Qualitative methods.

It aims to familiarize the intricacies, advantages and limitations of the Questionnaire tool by actively getting you to design that tool. This is a group based homework. Only one submission per group. If you don't know who your group is, pls ask Aashish about this.

I hear some groups have enrolled 5 members whereas I'd specifically specified 4 per group. You have a choice to either let one member go (in which case we'll assign him/her) or be prepared to accept a higher burden of expectations when it comes to grading. Your call.

Problem Context

First read the following (small) newspaper articles from the past year's Economic Times.

How new startups like LiftO, Shuttl, rBus are trying to solve urban commuting problem

Ola launches social ride-sharing feature

If security concerns not addressed, on-demand service startups could spell disaster for firms

Your project consulting client is a startup in the urban social-commuting solutions space in India's top metros is still in the process of figuring out the contours of their revenue/business model which crucially depends what the demand levels are like for such services at what price, who to target and how.

Pick any one of the firms mentioned in the first two articles as your consulting client.

Task

Your task is to (1) Formulate the client's D.P. and corresponding R.O.s. (My suggestion: Choose a sharply defined D.P. that can be well-covered by at most 1-2 R.O.s; choose a suitably narrow demographic as your target population that isn't too heterogeneous in its likely needs and preferences).

(2) Next, identify the main construct(s) of interest ones that will likely drive demand for your client, ideally based on your R.O.s. (Hint: Think in terms of the average target customer's motives/needs and the his/her self-perception of the requirements)

(3) Design a questionnaire that: [a] surveys target segment respondents on their propensity to use app-based on-demand commuting solution services;
[b] can be taken in <15 minutes on a good net connection;
[c] collects info on the distribution of quantities of interest (such as awareness levels about these services, interest levels in using them, what price levels might be viable, etc.)

My suggestions before starting:

1. To understand this target segment's needs and preferences, do some preliminary, quick qualitative research: E.g., conduct a few interviews (these could be casual conversations or telephonic ones) with a few people in that target segment about the subject. Find out what they think, what they need, what they see others around them doing etc.

2. Write (or 'Program') your survey into Qualtrics. Obtain the "launch" survey link.

3. Bonus points for using SKIP logic in Qualtrics (or any other free websurvey software such as surveyMonkey or zoomerang), pretesting the survey with a few folks first, accounting for order effects etc in questionnaire design, etc.

Submission Format

You can either markdown (in Jupyter, or in Rstudio, or in Blogs) or a traditional PPT for this assignment. All future assignments will involve code and hence only markdown will be allowed.

Below is the submission format for a PPT. That for a markdown will be similar. Just divide the markdown webpage into sections [Title, Data, model, results etc]

Start with a plain white PPT. Save it as groupName_session1.pptx

Title slide: Homework name and names+ roll numbers of group members.

First slide: Brief description of your client and their business (Also, a line or two to justify why you picked them)

Second slide: Statement of D.P and corresponding R.O.s

Third slide: Brief Description of qualitative research carried out to first narrow-down what topics to cover in the survey.

Fourth slide: Make a table that maps the 1-2 major constructs to the corresponding survey question numbers.

Fifth slide: Deliverable - websurvey link. Should be a working link. Also, attach the word or PDF version of your questionnaire onto this slide. The Q numbers in the 4th slide should match the ones here.

Sixth slide: Any learnings you as a group made - E.g., what constructs were the easiest to measure? hardest? ON the average, how many Qs per construct did you have to use? Etc.

Update:

In the past, I got quite a few Qs asking if a scale other than Likert can be used etc. Sure, it can. Likert is important in the context of behavioral constructs. For regular, descriptive Qs, use other scales by all means. *Not* every Q has to be a likert.

Whether PPT or markdown, wrap your submission inside a story, as far as possible.

The instructions for how to get a qualtrics account will be put up on Linkstreet, if they haven't been done so already.

Deadline for this is midnight of 05-March (Saturday). Drop box for the PPT/ markdown webpage will be set accordingly.

Any queries etc, let me know.

Sudhir

Classwork Uploads

Hi Class,

I expect that all of you have by now (i) formed your groups and (ii) installed all necessary analysis software (Rstudio and Python).

Aashish will upload all classwork related files - slides + code + data - in the next 2 days. Below are some tips for what to do re code and data

About Code:

• Code files will be primarily be script files (.R for R and .py for Python) but in some cases, markdown files will also be available.
• Open .R files directly via Rstudio and .py files via Spyder or Jupyter.
• Markdown files will appear as .Rmd files in R (for Rmarkdown) which open in Rstudio and as web pages for python.
• If unfamiliar with R (or python), pls read & execute each line of code + documented comments individually.
• Issues etc, first ask Google or your peers before reaching out to Aashish.

About Data:

• Data files are usually available as .txt in LMS.
• In a few cases, you'll have to signup for an API key and then scrape the dataset yourself. Follow instructions diligently in such cases.
• Issues etc, first ask Google or your peers before reaching out to Aashish.

Pls ensure you are very comfortable with replicating classwork examples over the next week-10 days odd. The homeworks + deadlines will start coming in after that.

Recall that your assignment submissions will be in markdown format and the core insights therein should ideally should be wrapped in a narrative / storyline.

Here's a link to how markdown works. Its a very simple 1 page get-started guide in case you're 100% new to Markdowns.

And this page here, from the same author is about a few useful writing tools for how to craft a narrative into your markdowns. Again, use your judgment and don't follow the articles to the letter.

Recall the blog page of Astronomer Julia Silge I'd shown in class? This is the link to her page. Its a nice intro to how to craft simple narratives around regular R code and workflows. Would be great if you can reproduce her workflow on your twitter feed, for instance...

OK. That's it for now. Feel free to use the comments section in case of anything.

Ciao and Cheers.

Sudhir

Hi again

Well, folks.

Our 5 sessions together are done. Am happy to note they went by smoothly enough. Thanks for being a nice class.

Watch this space for homework assignments, additional reading material etc that I'll put up. Feel free to explore blog entries from previous years to gain some idea regarding assignments and readings.

It won't be possible for me to put-up links to every topic and sub-topic mentioned or covered in class. However, searching the web will often reveal the info required.

For example, from session 5, if you want to know more about ROS or Baxter or a Turtlebot, just google search and explore the results.

Here are the class pictures we took. It's a tradition of sorts with me the past year odd, clicking pics with every class I've taught on the last day of class.

This is for Section A (I think)

And this with Section B.

One important perspective to keep in mind is that you're all in this learning journey together. You'll have a choice between adopting a collaborative mindset versus a competitive mindset.

I urge you to collaborate as a class to accomplish more learning for the class as a whole. Its better for everybody if everybody is willing to help/share with peers, than if everybody seals themselves off into silos. But crucially, this requires that *everybody* buys into the idea.

I encourage you to use the comments section of this blog for queries, ideas, feedback etc regarding the DC course.

Cheers and Ciao.

Sudhir

Hi Class

A big "Hi" to everybody.

This is a pro-forma welcome message from me to CBA batch 6 taking Data Collection (DC) in Feb 2016.

DC will use some R like it has in the past but this time, for the first time, I will try Python in the classroom.

This blog can be a repository for related R and Python code + assistance. Feedback, Q&A etc are always welcome via the comments sections.

Pls download and install both R + Rstudio and Anaconda (with Spyder & Jupyter) from LMS, if you haven't already.

Looking forward to smooth sailing.

Sudhir Voleti
Assistant Professor of Marketing
ISB Hyderabad