Qualitative and quantitative marketing research.

Now, before we actually get into the subject,

I want you to know that you've actually been exposed to the value

of marketing research fairly early on in the course.

You remember the Steve Jobs video you saw where he talks about that when

he was young, he used to start with the technology and

then figure out all the great things that he could do with it.

And as he got older, he realized that the real challenge

is not starting with the technology but starting with the customer,

figuring out what kinds of compelling experience to deliver to them and then

working your way back to the technology or working his way back to the technology.

Now, why is this essential?

This is essential because technology is never enough.

It rarely lives up to its full promise.

And even when it does, the adoption of technology is full of pitfalls.

One more story, the birth of Cisco.

Sandy Lerner and Leonard Bosack were handling the systems at,

IT systems at Stanford University.

They realized that as the number of computers were growing and

using different languages, that they were not able to communicate with each other.

So they built a router that would allow machines to communicate with each other.

They decided to gauge interest among potential buyers.

And they were very glad that they did.

Why? Because the very first person they took

it to said, I have two machines, your product works on one machine, but

doesn't work on the other.

So right away they knew that they had to fix their problems so

that they could then gain access to a broader market, with the result

that no matter what machine you were working, their product would always work.

So technology is never enough.

What we are going to words is customer insights and understanding.

So first let me bust a myth.

I've been busting a lot of myths in the past several sessions, and

most people who do not like marketing research or who have a beef against

marketing research say that marketing research is not relevant.

And we ask them why.

And they say, well,

because customers can't tell us what they want in the future.

Well, guess what.

That is an incorrect understand of marketing research.

That's not what marketing research is about.

Supposing I was to ask you a different kind of question.

Supposing I was to ask you that before product development, would you,

dear entrepreneur, invest in understanding and

gaining insights about customers problems and needs.

What would you say?

I guarantee you that about 100% of you, maybe even 110%,

because some of you may raise both hands, might say yes, you know, we will invest

in understanding and getting insights about customers' problems and needs.

Well, folks, that's exactly what marketing research is all about.

It is a methodology.

It is a set of methodologies and tools that allow you to invest in understanding

and gaining insights about customers' problems and needs.

And this process of customer discovery and customer validation

is what we typically refer to as the customer development model.

And the customer development model can be related to the technology life cycle and

it comes very early.

Why? Because the earlier we understand

what a customer wants, the quicker we can develop a winning configuration

of customer value, which will then allow us to cross the chasm easily and

go from the early adopters and innovators to the mass market.

So let's align.

I had earlier said that marketing research is a set of tools and methodologies.

Let's align these tools and methodologies along the innovation spectrum or

continuum.

On the left-hand side we have incremental innovation, and

this is where the traditional marketing research methods come into play,

observation, qualitative marketing research, quantitative market research.

In the middle, as you're moving from incremental to breakthrough,

customer interaction methods that stress ethnography, user experience, and

design thinking come into play, and then as we move to the far right,

breakthrough innovation, that's where experimentation and co-creation and

prototyping come into play.

In this particular session, we will just take a look at the traditional methods,

and even then, just two of them, qualitative marketing research and

quantitative marketing research.

Again, the three pillars of qualitative research are observation,

you know, actually observing people behave.

Focus groups, you know, and you've heard of what focus groups are.

Collect about 10 to 12 people in a room.

We engage them in a dialogue.

And through the process of dialogue, through indirect suggestions and

questioning, we understand how they approach certain kinds of problems.

So, for example, let's say we are talking to a number of,

let's say, museum curators, people who are in charge of running museums.

And there is a certain technology that's been discovered to work on art that has

been disfigured to bring it to life, to restore it to its original pristine glory.

And the focus group then is with these museum curators and

administrators to understand how they will respond to that technology,

will they embrace it, what do they like about it, what do they not like about it.

In-depth interviews are very often done when you want to understand a single

person's point of view and where there may be discrepancies between the status and

the prestige of different respondents, so you don't want to mix and match them.

For example, in a hospital, physicians have more status than nurses, so

nurses may not be very comfortable speaking out in front of physicians.

So if you really want to understand whether or

not robots will replace human beings and performing surgeries,

let's not lump the cardiovascular surgeons and the nurses together in a focus group.

Let's do in-depth interviews with them.

Let's talk to the cardiovascular surgeons separately and the nurses separately.

Now, let me give you a case study of qualitative research.

Singapore, yes, the country of Singapore,

they have made high tech a national priority and they have a major pain point.

The major pain point is that there is an SME gap, SME,

small medium enterprises, in the high-tech sector in Singapore.

What does that mean?

There's not enough of them.

There are the large multinational companies from Europe and

America, but the small medium enterprises that

are often homegrown are just not there in large enough number.

The objective of the study was to develop a comprehensive

understanding of the reasons underlying the gap.

And what's the methodology that the Singapore Ministry of High Tech

promotion used?

They developed indefinite reviews with senior management of target SMEs

to understand what were the barriers to growth of organizations like theirs.

Quantitative research is different from qualitative research.

The output of qualitative research is words.

The output of quantitative research is numbers.

And surveys happen to be the cornerstone of quantitative research.

You may or may not have heard of Gartner's four quadrant methodology.

But if you have,

you will observe through this table that surveys form a very important part

of the data collection methodology before they develop their quadrants.

If you haven't, you may want to go to the Gartner website to take a look at what

the four quadrants are, but they're basically,

the four quadrants is a classification tool of technologies

which tell you how hot the technology is and how likely it is to be adopted.

And you can see the second row of their surveys conduct formal and

informal surveys of IT users, technology providers, investors, businesspeople,

academicians, and other researchers, a large variety of target markets and

segments in order to inform the development of the four quadrants.

Some samples of a quantitative survey, again I've already told

you that the output of a quantitative survey is data, numbers.

Would you like to personalize high-tech products?

Yes, no, one, zero.

I can also ask that question as a rating scale.

On a ten-point scale, where ten is very likely and

one is not at all likely, how likely are you to personalize high-tech products?

I've asked the question differently.

My data is now interval scaled and no longer just a nominal one, zero data.

How would you like to personalize your products?

Providing your own image?

Selecting image from a list of existing design images and personalization ideas?

I can also ask the question slightly differently to get ratio data.

Again, I'm asking you to check boxes over there so

you can give me multiple responses.

I can ask it two, one of two ways.

I can now, again, ask each one of them on a ten-point scale, but let's not do that.

Rather, I give you a hundred points and I say divide a hundred points between

the two methods of personalizing your products, providing your own image or

selecting from a bank of images, and now you give me your allocation.

And your allocation then suggests which one is relatively more important or

useful for you.

And lastly, who would you get the product personalized for?

Myself, family member, friend, other?

I can also ask the question, now,

this is multiple response because you can check a number of them.

But I can also ask the question slightly differently, and

I can say rank order the people below for

whom you may get the product personalized, myself, family member, friend.

And now you're getting ordinal deal.

So depending upon how I ask the question, I change the nature of the data.

Depending upon the nature of the data,

my ability to analyze the data becomes limited or enabled.

And we will talk about analytics in the next subtopic.

Some of the most common errors that are made at this stage is people

generally don't have respect for

marketing research, and I've never quite been able to understand that.

I think that it is important to remember that marketing research is necessary,

it is demanding, and has its own rules.

Very often people approach marketing research

casually as opposed to rigorously.

Framing the problem can also be an issue.

I'll be trying to figure out what are the barriers

to the growth of SMEs in the high-tech markets in Singapore or

are we trying to figure out how to get SMEs to adopt high-tech innovations,

very, two very different things in terms of how we frame the problem.

There is also the question of bias, failure to ask the right questions and

hearing only what one wants to hear.

The first bias is dramatic, because the way I ask the question,

I already demonstrated that to you, will generate different kinds of data.

And if I'm only hearing what I want to hear, then what am I doing?

I'm actually engaging in a self-fulfilling prophecy.

I'm validating what I already know.

I'm not hearing what you, dear customer, has to tell me.

And finally, after collecting the data, a lot of companies do insufficient analysis

of the data, and they don't spend enough time reflecting on its meaning.

In summary, developing insights into customers' needs, wants, desires, and

preferences is non-negotiable.

It is not something that we can haggle about.

Marketing research is an indispensable tool to help develop insights and

understanding into those needs and desires.

Traditional marketing research has two dominant categories or

two dominant branches.

Qualitative marketing research, the output is words.

Quantitative marketing research, the output is numbers, and using the two

in conjunction is always more powerful than pitting one against the other.

So it is not qualitative versus quantitative.

It is, how can I use qualitative and quantitative methods so that I get,

I develop a deeper, more rigorous understanding of customers' needs and

wants and desires and preferences.

Qualitative and quantitative marketing research

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