Stages For A Successful Quantitative Analysis

Market research is a group of techniques applied to understand consumers and suppliers. Over time these techniques are increasingly sophisticated and numerous. However, within the large classes of methodologies that we have available to study people, the quantitative one stands out because it offers us the possibility of anticipating behaviors based on mathematical calculations.

Regardless of the passage of time, there is a process that is well known and followed by all quantitative analysts when it comes to translating data into clear and executable findings. Each of these steps involves data experts own resources of time and knowledge. Next, we outline the essential stages that any quantitative analysis must cover.

  1. Obtaining. This step includes several tasks; both in the field and on the desktop. Sometimes a work team must be assembled, trained, and sent to collect data from the reporting units. In other cases, we can satisfy our needs with databases generated by third parties. In any case, this step is crucial, since if errors are made in obtaining the input for the quantitative analysis, there will be no palliative process that can be used to correct shortcomings of origin.
  2. Cleaning. The next step in the process involves reviewing the records available to work with. This in order to discard those that do not have a minimum of quality and those that are recorded can distort the findings because they are unusual extremes. Many times it is enough to run basic descriptive calculations. In other situations it will be worthwhile to group data that by their nature are expressed with different names in our databases; This task involves establishing rules based on documentary evidence.
  3. Examination. This is the most obvious phase and with which we traditionally identify quantitative analysis. Depending on the objectives of the study, the analyst will carry out a group of calculations or others, taking care that the results obtained describe the entire phenomenon and reducing the margin of error to the minimum possible. Fortunately, nowadays researchers have computers, programs and languages ​​that help reduce analysis times and human error derived from accidental mistakes if they are done by hand.
  4. Display. The results of the analysis are usually expressed numerically. In this form the findings are unintelligible to non-data science specialists. Here the expertise of the analyst go into choosing and designing the most effective charts to show each class of results. Each type of graph responds to specific visualization needs, so it is not just a matter of choosing between a pie or bar graph for its aesthetic value: the choice must be the most suitable to fulfill the established purposes and avoid an erroneous reading.
  5. History. The last step in the quantitative examination of the data is to convert the research results into a report that tells a logical and sequenced story. This part is very complex since it requires communication elements from the researcher. If the findings are not shared in a correct and accessible way, they run the risk of turning them into a tangle of ideas and seemingly disjointed and meaningless graphics.
Steps in the quantitative analysis process. Credit to whom it may concern.

Carrying out a quantitative study is a task that often exceeds the capabilities immediately available. That is why at Acertiva we put our specialists at your disposal in each of the stages of data processing. Write to us now so that you can tell us your needs and thus plan your next success story together to the email contact@acertiva.com