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Thread: Profile Evaluation for PhD in Marketing

  1. #11
    A long long time ago XanthusARES's Avatar
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    Re: Profile Evaluation for PhD in Marketing

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    Quote Originally Posted by BrazilianPhD View Post
    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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  2. #12
    Within my grasp! BrazilianPhD's Avatar
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    Re: Profile Evaluation for PhD in Marketing

    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.

  3. #13
    A long long time ago XanthusARES's Avatar
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    Re: Profile Evaluation for PhD in Marketing

    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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    Re: Profile Evaluation for PhD in Marketing

    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.

  5. #15
    A long long time ago XanthusARES's Avatar
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    Re: Profile Evaluation for PhD in Marketing

    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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  6. #16
    Trying to make mom and pop proud felixn's Avatar
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    Re: Profile Evaluation for PhD in Marketing

    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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