4.3 Datos secundarios y escalas de medición

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Del curso dictado por IE Business School

Investigación de mercados y comportamiento del consumidor

98 calificaciones

IE Business School

Investigación de mercados y comportamiento del consumidor

98 calificaciones

Curso 1 de 5 en SpecializationEstrategia de marketing

El primer curso de este especialización consta de dos bloques que te proveerán de los conocimientos necesarios para comenzar tu trayectoria en Marketing. Aprende las herramientas y técnicas para convertir una decisión en una investigación real, esto lo verás en el primer módulo: Investigación de Mercado. Cómo plantear la investigación, analizar los datos recogidos, interpretarlos correctamente y comunicarlos a través de recomendaciones precisas serán algunas de las cuestiones tratadas en este curso. El segundo módulo se enfoca en el proceso de toma de decisiones por parte del consumidor, resaltando los momentos clave en el proceso de compra y consumo de un producto. Adapta tu enfoque “cliente-céntrico” en decisiones de marketing mediante el análisis de cómo tus clientes toman sus decisiones, reflexionando en qué sucede en sus corazones y mentes al momento de tomar decisiones y analizando las variables que son influyentes para tomarlas.

De la lección

Marketing Research Data Collection & Analysis

En el último Módulo de este curso, aprenderá con mayor detalle los distintos tipos de datos recopilados durante el proceso de estudio de mercado y cómo evaluarlos. También se explicará la importancia de una encuesta eficaz y cómo crearla. En la segunda mitad del curso, explorará el mundo de los estudios de mercado.

4.1 Datos primarios I2:47

4.2 Datos primarios II3:36

4.3 Datos secundarios y escalas de medición4:45

Conoce a los instructores

Shameek Sinha
Professor
Marketing

[MUSIC]

In the last video, we have looked at the different types of primary data,

which you can use for your current study.

Here, we are going to start considering secondary data.

If you remember, secondary data is a type of data which is not usually collected for

the current study.

But rather it has been collected by somebody else for some other purpose, and

you get access to the data in order to use it for your study.

Now usually secondary data is available in different formats or

in different scales of measurement.

The first type of measurement for secondary data Is the nominal measurement.

Here there's no ordering or levels for the different categories which are at a level.

So let's think about an example.

When you are asked that, okay,

you have three different brands, maybe Heinz tomato ketchup.

The store brand private level and also preferably enhanced.

Out of these three, which one do you prefer most?

Of course, here there's no specific ordering of the product

which are from which you have to choose your preferred brand.

So, this is where nominal data is useful.

The second type of secondary data is called ordered.

Here, of course, there is some ordering, but importantly,

the distances between the different categories are not relevant at all.

So again, let's think about our example of tomato ketchup.

Again, we have, let's say, three different tomato ketchups, Hunt's, Heinz,

and the private label.

In this case, you are given a three category scale like, do you prefer it?

Do you not prefer it?

Or are you indifferent?

Here, of course, there is some ordering in the three categories which you are given,

but still, there's no specific distance between these categories.

It's not the case that

you prefer something is exactly half of what you are indifferent.

And if you are indifferent,

that's exactly half of if you are not preferring the product.

So the distances are not at all relevant in this case.

The third type of secondary data is called interval data.

Here however, the distances between the different categories

start to become more meaningful.

So let's think about the situation where you have again these three

brands of tomato ketchup Heinz, Hunts and the private label.

However, in this situation, you are given a seven point scale from one to seven,

and you're asked to rate each of these brands on that seven point scale.

Of course, here the seven scales refer to the seven

different categories which are very important in terms of.

So this is where a type of secondary data becomes more

useful because you can exactly measure the importance of the different [INAUDIBLE].

The fourth type of secondary data is ratio data.

Here there is a natural origin, like zero, and

the distances between the categories are becoming more and more meaningful.

So again let's think about the example of the three tomato ketchup brands.

However here you are probably measuring the sales of the three brands, or

maybe the revenues, or

maybe the profits the firms earn from the three different brands.

In this situation of course it's very important to look at the exact numbers.

And that's why this type of secondary data

is probably the most prevalent in any kind of any marketing research analysis.

So as you'll see as we look at these different types of secondary data.

Or the different measurement scales of secondary data

Each of them has increasing amount of information compared to the last one.

So starting from the interval scale to the ratio scale,

everything becomes more important because the distances between the different

categories become more relevant.

So in the next video, we are going to start looking at different types

of data collection methodology in primary data starting from questionnaire design,

and then going into different psychological scales of measurement.

Thank you.

[MUSIC]

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