What Does Data Science Do In Market Research?

Data is perhaps the most valued input in Market Research. Throughout the 20th century, a race was carried out to get as many of these in the shortest possible time. Thanks to computer solutions, a transition was achieved in obtaining it. We went from using paper questionnaires to digital files with a huge number of records. This leap caused many people to worry because it quickly went from having limited availability to an excess of resources to analyze.

The demand for science and engineering that has always been dedicated to understanding data saw its demand increased by multiple brands and companies. For some years now, organizations have sought help to understand and take advantage of what we have now called Big Data in a viable way. Fortunately, this task involving repetitive actions can be performed using different programming languages. This adds a demand for trained programmers and engineers to reduce research times. The conjunction of informatics and disciplines involved in understanding data is now known as Data Science.

Next, we list some of the disciplines that are part of this new specialization so mentioned today and that has given so many advances to the understanding of the markets.

  1. Statistics. Perhaps it is the most recognized area for locals and strangers. Describing the distribution of characteristic values ​​in a population is a basic step in beginning to understand a data set. With this branch of mathematics, an initial evaluation of the data is carried out in order to assess whether its quality is valid or not. For example, if outliers are identified in a database, they should be eliminated to avoid distorted results.
  2. Data mining. Statistical methods and computer solutions converge in this area. Analysts who specialize in this discipline carry out mathematical models that make it possible to predict future behavior or define groups of individuals that share characteristics. It should be noted that partially or completely automated calculations are considered in data mining.
  3. Artificial intelligence. Thanks to the advances in the data processing capacity that computers have today, it is possible to develop solutions in digital learning. It could say that this implies that a computer is taught to solve or answer certain tasks or questions given certain conditions. This activity requires people specialized in programming for data analysis and the correct training of the systems.
  4. Historical analysis. We already mentioned before that at this moment we have several years accumulating data on the same activity or topic. Thanks to this, long periods of time can be reviewed in order to predict future behavior with great mathematical validity. The greater the quantity and quality of the inputs, the better the predictions made.

Market Research has greatly benefited from Data Science. More than a fashionable concept, this set of disciplines has obtained its own name given its great utility for our activities. At Acertiva we can help you with this and other needs that your brand may have. Write us today to tell you how we can be your potential regional ally in Latin America.