Design Thinking or quantitative research? Understand the difference between them and learn when to use each method

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Quantitative market research supports decisions in organizations from different segments, but the lack of depth can leave important questions unanswered. For a complex and user-centered data collection, it is best to use end-user methodologies such as Design Thinking.

These methods are different in relation to what they can offer as value, and in delivery, applications, support tools and process duration. In order to understand when to make use of Design Thinking or quantitative research you need to understand the difference between the two.

Concept
Design Thinking requires an in-depth analysis of user behavior. Based on face-to-face, field and in-depth research, the user’s needs, concerns and problems are identified. The raw data collected is analyzed by specialized professionals, who identify common points that will make up the persona(s). These profiles are the basis for directing the next stages, since they represent the end user, i.e. the target audience.

Quantitative research provides numerical data, which is obtained through objective questions on standardized forms. The methodology can provide numerical data on a voluminous sample, but there is no depth, which prevents the creation of complex patterns of behavior.

Goals
Design Thinking uses 4 different stages (Immersion, Analysis, Ideation and Prototyping) to achieve complex results. Numerical data is important to point to standards, but the main focus is to provide insights rich in strategic information.

In quantitative research, responses are brought together in order to obtain absolute numbers and percentages. The focus here is to obtain a large volume of responses, which could even lead to some kind of standardization. However, the needs and issues of the user are not known in depth and there is no qualitative analysis of the answers, since they are based on numerical data.

Samples
Design Thinking does not seek to obtain large numerical samples, but rather to understand how that cutout sample behaves. Quantitative research, on the other hand, is widely used to disseminate voting intentions statistics to the population. Therefore, the sampling needs to be larger and, consequently, more people will be interviewed.

Methodology
Design Thinking features in-person and in-depth interviews, group discussions, generative sessions, and other behavioral analyzes. The questions are complex and objective answers are avoided. The goal is to get as much information as possible from each user, which can also be recorded for more detailed analysis. In this process, individuals with different characteristics, such as age, gender and age group are questioned, obtaining a varied and rich sample.

In quantitative research, standardized forms are used to interview a very specific population cut, in terms of age, gender, income, geographic location, among other factors. The questions are objective and can be completed in online forms, since they are not very complex.

Tools
Design Thinking makes use of different tools throughout the design stages. In Immersion, we use Criteria Scoring, Sensitization Notebooks, Direct Observation and Cool Hunting. The creation of personas, Generative Session and Co-creation Workshops are used during the Ideation stage. During the Prototyping stage, in turn, it is possible to make use of paper prototypes, enacting, among others.

In the case of quantitative research, the tools used are limited to the online form, with standardized questions, and methods of numerical analysis.

Applications
Design Thinking can be applied to any business segment and supports both the launch of new products or services and internal processes of innovation. It is especially useful for getting to know the end user in depth and to propose assertive solutions.

On the other hand, quantitative research leads to numerical deliveries and is ideally suited to provide statistical data, such as in polls.

As you can see, Design Thinking and quantitative research have significant differences from the methodology and tools used, to its applications and deliveries. However, if used correctly, they can complement one another.

The Design Thinking methodology is made up of 3 distinct and complementary stages:

. Immersion
The stage in which the problem is approached. The team seeks to delve into the implications of the challenge by studying both the company’s and the end user’s points of view.

. Analysis
The moment in which the data collected during interviews is analyzed so it can be used to create personas.

. Ideation
The moment in which you truly begin to “think outside the box” to come up with solutions to the problem.

. Prototyping
The stage where is possible to make the selected ideas tangible. With the prototype in hand, it is possible to validate the solution with the end user. This process seeks continuous improvement, and the tests aim to enhance and deliver the best possible version of the service/product.

Do you want to learn (even more) how Design Thinking can support your business decisions? Check out our infographic:

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