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Profile Evaluation for PhD in Marketing


felixn

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Hello there,

 

I'm an MBA student who is interested in pursuing a career in academia, and I would love to hear some recommendations from you guys.

Test Scores (GMAT/GRE): 760 (51Q 42V)

Undegrad GPA: 3.3/4.0 in Business Economics from a business school in Southeast Asia (top nationally, but not well-known internationally)

Graduate GPA: 3.9/4.0 MBA in Marketing Research with a good portion of Quant courses (Psy Exp Analytics, Marketing Analytics, Multivariate Analysis, Machine Learning, Clustering...)

Research Experience: senior thesis in Business Econ, class marketing research project. (meh :blue:, I know)

Teaching Experience: 2 TA semesters in Statistics

Work Experience: ~ 3 years in Product Management, with some programming and ML experience

Concentration Applying to: Marketing (Quant), or maybe Innovation

Number of programs planned to apply to: 10

Dream Schools: UT Austin, USC - Marshall, Maryland, OSU

 

 

Other Questions:

 

What made you want to pursue a PhD?

I love to do independent research, on a topic of my own desire. Academia lifestyle is also probably a better fit for my personality than corporate.

 

Questions or concerns you have about your profile?

Low UG GPA, not many Math classes in UG, and almost zero research experience.Thanks!

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  • 2 weeks later...

Your profile seems good. Not exceptional, but certainly not bad either.

 

It looks like you have already identified the problems you have. So, you know your profile is not bulletproof, and that may keep you out of some schools. The schools you listed seem to be very strong, but I guess you will apply in a wider range.

 

You will probably be expected to explain why you want to move to academia, since you already have a professional career and just did an MBA. Since you have almost "zero research experience", it may be harder to convince schools that you "love to do independent research", since it's hard to know we love something we don't know much about. Better to think some strong reasoning for that.

 

When I read "on a topic of my own desire", I immediately thought: "what is going to happen if it is NOT a topic of your desire?". After all, during the PhD you may be involved in other people's research projects, not necessarily the ones you want to.

 

And of course you will have to explain why your personality matches the academia lifestyle. Be careful with your explanation here, you must show you have a pretty good understanding about the academia lifestyle in a motivation like this. Otherwise, people will think you have no idea what you are getting yourself involved with.

 

Play with your strengths. It looks like you have a good knowledge about programming, and that experience as TA in statistics is a good thing that is not easy to find in applications.

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I agree with Brazilian. You seem to have a good, but not great profile. You correctly identified your potential concerns. I appreciate that your dream schools listed are reasonable in terms of goals. They will be difficult for you to gain acceptance to, but not impossible.

 

So I think that if you apply widely and have a strong SOP, you'll get somewhere. Honestly I'd guess somewhere in the top 30.

 

Good luck!

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Thanks for the great replies guys!

 

The schools I listed are my dream schools, and there are some profs there I want to work with, but realistically I would be very happy to get into a top 40 program :).

 

Regarding research experience, would industry researches matter? Since my program is a specialized one with good industry connections, we have the chance to work on some projects like doing user behavior research for Microsoft, or shopper behavior for Walmart... I know academic research is much more rigorous, but would taking on more projects like those help my profile in any way?

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Regarding research experience, would industry researches matter? Since my program is a specialized one with good industry connections, we have the chance to work on some projects like doing user behavior research for Microsoft, or shopper behavior for Walmart... I know academic research is much more rigorous, but would taking on more projects like those help my profile in any way?

 

The generic answer is that industry research does not matter that much, and that's not going to make a big difference in your profile.

 

But I think it depends a little on how you're going to use that kind of thing in your application, the school you're applying to, and your research interests, for example.

 

Do not try to sell the idea that industry research experience is directly relevant for academic research. It could give the impression that you don't know the differences between them. It's not just that one if more rigorous than the other, for example. One could do a very rigorous research in industry, and we can see many examples of academic research that can't really be considered that rigorous.

 

However, industry research experience may still be useful to make your application stronger in some ways, you will need to evaluate in which ways it might work for you.

 

I'll give some examples.

 

My industry research experience was important to explain my academic research interests. There were important questions that I was not able to answer while I was in industry, and doing a PhD is giving me the opportunity to look for those answers in a way that I wouldn't be able to if I stayed in industry.

 

My school and particularly my advisor have close and strong connections with the industry. Sometimes, I see here projects that are a collaboration: a firm is doing some industry research and we are doing some academic research, and each one helps the other. In a scenario like this, previous industry research experience can help with communication and collaboration, for example.

 

My research interests are more empirical/strategical in nature, not theoretical for example. So, understanding what is going on in the industry can be really helpful. One feedback that I often get is that I'm good at picking topics that are relevant, that draw the attention of researchers in general (in academia and the industry), and that improve the odds of getting published. And I think the understanding I got from previous experience in the industry is what allows me to see what topics are of general interest.

 

So, the idea is that industry research experience may not matter that much directly. But maybe some skills and knowledge that you developed while doing industry research can help you to become a better academic researcher, for some schools and types of projects.

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  • 1 month later...

Hey guys, it's me again.

 

Since posting this thread, I've been trying to improve my academic research experience. I'm having some new questions in the process:

 

- I'm working on a research project for my Human-Computer Interaction class (it's a PhD level class) with a PhD candidate in Marketing and another one in Computer Science. The goal is to have a publishable paper by the end of this semester, but I wouldn't bet on getting published (historically only 1 or 2 papers of a total ~15 from the class got published each year). I wonder if this would help with my application? Moreover, how do Marketing researchers usually view studies in other fields like HCI?

 

- I learnt that my school offers an option to do independent study even for MBA students. I'm planning to do one next semester, and I already have a research topic in mind. How should I approach a professor to be my adviser? I'm afraid that professors would be too busy to help with an MBA student's research project.

 

Thanks in advance for your help with my dumb questions!

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Yeah, it can help your application. Of course it's better if you get it published. But even if that's not the case, it is an indicator that you know what is academic research, that you are able to get results, that you are committed to it, etc. You can also add the paper as a sample of your work in the application.

 

I don't think studies in fields like HCI are a problem. I've seen research in marketing that would be very closely related to HCI. For example, the use of HCI and robots in customer service. However, some professors will love it, and some professors will not care about that kind of thing at all. It will probably have different effects depending on the schools (e.g., tech-savvy schools).

 

Professors are busy, but many of them are willing to listen, guide and help students. But, of course, do it in a way that does not waste their time. Be ready to show something interesting, do not go to a professor whose interests are completely unrelated to your project, show how your project could match or help the type of research the professor does, etc. If you make them interested in your project, even if they are too busy to really advise your, they may make the effort to find a way to help you. Professors expect that students who are interested in doing a PhD in the future will look for them for help, instead of waiting until it's too late.

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Thanks for the reply, Brazilian!

 

On the topic of research interest: At the moment, I'm interested in a question that I had during my time in industry, "The effects of robo-adviser on customer investment choices", i.e. would the interaction with a robo-adviser instead of a human adviser increase/decrease individual investors' risk appetite? Do you think that's an appropriate Marketing research topic? I want to have a concrete research question before approaching a professor.

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It's not totally unrelated, but to me it looks like you are interested in investors' choice and not customers' choice. All right, I understand that an investor can be seen as a specific type of customer, but it is a type of customer that probably people in Finance or Economics have much more interest.

 

So, for a Marketing PhD, I think it will harder to find professors who are interested in investors. In that case, finding schools with a good research fit would be a challenge. I may be wrong, if you have found a lot of Marketing professors who do research about investors, then it's ok. I did a quick search and I didn't find papers that looked like that published by a top journal in Marketing, but maybe I didn't dig deep enough.

 

And how do you expect to do that kind of research? The best method to me seems to be the manipulation of the robo-adviser interaction in a controlled environment with a good control sample and then measure risk appetite outcome (which is a consumer behavior variable). And then this would be a behavioral experiment, suited for a CB applicant but not Quant.

 

Another possibility that I see is to do a purely theoretical research, without the need for data. That would be Quant, but also would raise another set of issues.

 

So, to me, that topic of yours makes me stop and think:

- Is this really Marketing? Isn't Finance/Economics better?

- Is this really Quant Marketing? Isn't CB better?

Schools obviously are expected to prefer applicants who are clearly a good match, instead of ones that they have to stop, think, stretch, to see if maybe it could be a fit.

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And how do you expect to do that kind of research? The best method to me seems to be the manipulation of the robo-adviser interaction in a controlled environment with a good control sample and then measure risk appetite outcome (which is a consumer behavior variable). And then this would be a behavioral experiment, suited for a CB applicant but not Quant.

 

I disagree with this. Your research interests seem to align perfectly with Behavioral Economics, which is definitely quant. The use of an experiment does not preclude a quantitative bend to research.

 

Now in terms of research, I'm a bit concerned that your interests are too narrow at this point. I would say that you are largely interested in risk. The context you want to study it in would be investor's, but the real meat of the issue is risk. There are plenty of faculty studying risk type of questions in marketing. You may need to adjust your research interest slightly to get to a more marketing focus lit stream (i.e. Brazilian is right on that investment research is largely outside of our marketing area), but looking at consumer's risk perceptions are definitely within our realm.

 

I think you're off to a good start, though. Good luck!

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Yeah, just to make it clear, I'm not saying it cannot be Quant Marketing. But, in its current form, it's not the typical stuff of Quant Marketing, so you can improve on that to make a more compelling application.

 

I cannot give details, but I've actually been working on a research project related to this subject of methods used in Quant Marketing. And experiments are not considered as relevant for Quant Marketing, even if they can still be used.

 

I'm into a Quant Marketing track. What I've seen and learned is that there are 3 major subgroups in Quant Marketing:

- The theoretical guys. They are mainly interested in proving things with pure math, without even the need for data.

- The empirical guys. They are mainly interested in using large data sets, and analyzing them with statistical software

- The Marketing Strategy guys. Marketing Strategy is a lot closer to Quant Marketing than it used to be, and these guys are interests in topics like sales management, brand management, marketing-finance interface, and distribution channels.

 

For the first 2 types, I see them using experiments as a secondary method:

- A theoretical researcher develops a new theoretical model to predict risk appetite, using mathematical proofs. And then, to provide evidence that the theory holds, an experiment is conducted to see the results.

- An empirical researcher use a marketing model to analyze big data, and then reach some conclusions. However, given the statistical challenges in showing causal effects from observational data, an experiment is conducted to provide further evidence that the results are for causality and not only correlation.

 

In both cases, they can do experiments, but experiments are usually not the preferred way. So, even if quant guys can use experiments, lots of us will not see it as a primary method. It's a lot easier to find Quant professors who love analyzing big data than those who love experiments.

 

For the third type, there is a different issue. For Marketing Strategy guys, external validity is often very important. And external validity is often an issue for experiments, especially lab experiments. So, it can be done, and it's often done, but you have to be careful.

 

Of course these are not the only subgroups in Quant, but those outside these subgroups are rare.

 

So, maybe it's perfectly ok to apply to Quant Marketing. But it's a lot easier to convince Quant professors when your topic clearly looks like math or number crunching research. And so far, yours don't. All I'm saying is that you need to improve, so that when Quant professors see your application, it's very clear to them that what you want to do is Quant Marketing.

 

For example, when I applied I said that I wanted to research marketing-finance concepts like customer lifetime value and brand equity, and use datasets to do my research. It was pretty easy to find empirical and marketing strategy professors who might be interested in that, that have experience with that, that have access to datasets for that kind of thing, etc. And I have no trouble at all showing this is Quant Marketing or Marketing Strategy. In your case, I think you will have a harder time if you don't adjust your research interests to make them more appealing to Quant Marketing professors.

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Yep Empirical and Analytical are both quant types (arguably strategy is it's own beast). But again Behavioral Economics is quant based with experiments included. Obviously you need to find some BE people, but to say that they aren't Quant, or that they aren't as respected as Quant I don't think is fair.

 

But yeah, if you're looking for straight up math, stats and econ, go the traditional Quant route. Don't try to talk an analytical quant person into doing an experiment.

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XanthusARES, now I feel like you are putting words in my mouth. Because the comparison I'm doing is not about "as respected as", like you wrote.

 

I'm talking mainly about two things:

 

1 - That experiments are not as relevant for Quant Marketing.

 

Relevant and respected are very different thngs. I respect a lot of things that are done in science,but that doesn't mean they are all relevant to my own field.

 

It doesn't mean experiments are less respected or can't be used. But, for Quant Marketing, mathematical proofs and data analysis with statistical software are much more relevant than experiments.

 

If a Quant Marketing applicant is bad at experiments (e.g., no knowledge, no experience, no strong interest), but excellent at math proofs or data analysis, I believe that most Quant professors will not make a big deal out of it.

 

But if a Quant Marketing applicant is bad at math and data analysis, it's going to be a problem even if that applicant is excellent at experiments.

 

It's not about respect, but relevance for Quant Marketing.

 

 

2 - That, as I wrote, "those outside these subgroups are rare".

 

Again, rare and respected are very different things.

 

If an applicant chooses a topic that is rare among Quant Marketing researchers, then research fit becomes even harder to find than usually is. If that's what the applicant chooses to do, that's ok. But at least it's a conscious choice, that is taking into consideration the risks of that choice.

 

 

Of course there are Behavioral Economics researchers who do experiments and are highly respected. This is a topic that has been getting Nobel prizes, after all. But I'm not talking about respect.

 

And, in my opinion, it's better in an application to show things that are more relevant and not so rare for the track that you are applying to. I think that improving the research interests in that regard is going to make the application stronger, and increase the chances of acceptance. That's my goal here. Respect was never the issue for me here.

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Absolutely no disrespect. Sorry for the confusion. I, definitely, incorrectly put words in your mouth. That's on me and I'm sorry about that. I think that this is a point on which we are going to have to agree to disagree. I see BE as a major subfield of Quant marketing, but perhaps you do not. I took that to mean that you felt it wasn't respected (or respectable). I see that you didn't mean that, but perhaps simply don't believe it makes up as big of a portion of the field as I believe it does. To be fair, you are definitely correct that it is significantly smaller than either empirical or analytical, but it's not so insignificant that if the OP really wants to do experimentation and quant work that they wouldn't be able to find multiple schools with faculty studying these areas.

 

All of that to say, I'm sorry for the misunderstanding and for mischaracterizing your point of view. Thank you for clarifying it!

 

To the OP, again I can't agree more with Braz, if you want to quant marketing, the best bet is to go with empirical or analytical work. There are way more opportunities there then in experimentation.

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Hey guys, sorry my question created a confusion among you, and thanks for all the responses!

 

@Brazilian: Your point is a very valid one, and I myself is unsure about the appropriate methodology as well. It's just a very basic research question at this initial stage, one that I'm curious to know (since my background was in Fintech), and couldn't find much literature on. I also have have doubts on whether it's more Marketing, or Behavioral Finance.

 

@XanthusAres: Behavioral Econ is my initial approach as well, since that's what I'm familiar with. I was able to find a few BE papers that studied similar things (financial advice, but in other settings).

 

I imagine there is an empirical approach to the question as well, by analyzing investment history of individual investors over a long period, who have switched from personal advisor to robo-advisor. That dataset would be quite difficult to get a hold of though. I concur it would be easier to pick a different research topic, maybe I'll come back to that later if I have the chance.

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