Market research results need to be analyzed using statistical analysis. Statistical analysis investigates relationships between quantitative data, data trends and any patterns.
Descriptive statistics, which are tools used to summarize and describe numerical data, are used to carry out statistical analysis.
Statistical analysis can help business managers to make better decisions as the risks are reduced when they are able to make more well-informed choices based on factual results.
Why analyze data from market research?
Businesses analyze data and information in order to find out the most likely outcome of a business decision, forecast the future, find variations, check for quality, etc.
Once the market research has been carried out, the results need to be presented and analyzed for both qualitative research and quantitative research:
- Qualitative market research, such as information obtained from in-depth interviews and focus groups, a focus panel or test market, is usually presented in the form of written reports, tables, infographics and pictograms. Qualitative research provides non-numerical answers such as opinions, beliefs, feelings, attitudes, perceptions, motivations, choices, views, etc. Managers can use this information to evaluate their current products and decide whether changes need to be made to how products are being marketed.
- Quantitative market research consists of data, usually lots of numbers, from surveys / questionnaires and secondary market research that is presented in the form of charts, histograms, spreadsheets and databases. Quantitative research provides numerical answers such as data about company products, customers, markets and competitors. Raw numbers have no meaning on their own, hence managers need to put them in context; present in a way that will be understandable for the audience.
Sometimes companies find data already analyzed by government or other responsible agencies – looking at ‘forecasting and predicting from data’ and ‘measures of central tendency and dispersion’.
Statistical analysis of the market research results
These unprocessed information and data are called ‘raw’. Now, it has to be analyzed by the researchers and presented in a way that will assist business managers in making better business decisions.
Interpreting and analyzing statistical data from market research surveys / questionnaires can start with an attempt to identify key features of the data and establish any underlying trends (or lack of thereof).
Here are the most common thirteen methods of descriptive statistics used in business management. They have been grouped in five categories for your convenience:
1. AVERAGE
Shows the center point of the data:
a. Arithmetic mean – Average value
b. Median – Middle value
2. FREQUENCY
Shows how often the data occurred:
a. Mode – Most frequent value
b. Frequency data – Most frequent average value
c. Grouped frequency data – Frequency of values within different groups
3. DISPERSION
Shows how widely the data are spread:
a. Range – Difference between highest and lowest values
b. Quartiles – Distribution of all values into 4 equal groups
c. Inter-quartile range – Range of the central 50% of the dataset
4. DEVIATION
Shows distance of the data from the center point (mean):
a. Variance – Spread of data from the mean
b. Standard deviation – Average difference between data and the mean
c. Mean deviation – Average of differences between data and the mean
5. CHANGE
Shows how the data changed over time:
a. Index numbers – Changes in values
b. Weighted index – Changes in values of unequal importance
After the data is analyzed, it will then be in the format which will allow the users to make better business decisions. Better decisions are indeed possible based on the analysis. However, some data is unreliable, out of date, collected in less than a thorough way, or incomplete.
The next few articles will show in details how numerical data might be summarized using the aforementioned statistical techniques.
