Conducting Factor Analysis
Because factors cannot be observed directly, they must be inferred from the variables under consideration. As making changes in the products
to test the variable can prove to be very expensive, companies use factor analysis to test the variables with the help of methods such as focus groups and surveys. Surveys give you the information regarding what the customers and potential customers look for in a product before purchasing. You can use this information to identify which factor of marketing you should focus on and what changes are to be made in the product. For example, you can display the three different packaging version of your product before a focus group and ask them which one they like the most and why. Then you can modify the packaging to attract more and more buyers.
When conducting factor analysis, keep the following points in mind:
- The sample size is sufficient to give a reliable data.
- Factor analysis is possible when the variables are correlated. Whether a correlation is strong or weak is demonstrated by Measure of Statistical Adequacy (MSA).
- Variables are correlated if the minimum MSA factor loading is 0.4 (1.0 being the perfect correlation). So variables with a factor loading below 0.4 are eliminated, since they fail to correlate with anything.
Observing the Variables
There are a huge number of variables. To know what effect a factor has over the sales of a product, you have to change only one factor at a time while keeping all other factors constant. It gives you the precise relationship between the particular factor and the outcome. Variables may include the product features such as size, color, packaging and price. Marketing strategies and distribution channels are also important variables that can be changed to observe the effect of change on total sales of the product.
How Factor Analysis is Important in Marketing
In the process of new product development, factor analysis helps you prioritize the issues or features to be focused. It’s equally useful in improving the existing product portfolio and expanding the product offerings in any industry.
A good example is the home loan business of financial institutions. A customer has many options with good credit. Banks use the analysis to determine the list of variables that the customers consider when choosing a bank for a loan. After reviewing the relevant factors, the financial institutions proceed to promote their products based on these factors.
Developing Customer Niche
An important role of factor analysis is to analyze the mind of customers. Satisfying the customers and developing a long lasting customer relationship is the key to survival of business, which is impossible if you can’t understand their requirements and expectations. Attitude and buying behavior surveys serves this purpose. After executing factor analysis, you can understand the relationship between the variables and accordingly bundle up into groups. The categories of the customers may be “price-sensitive” “quality-oriented” or “brand loyal” ones.
When you reduce the number of distinct variables that are responsible for product selection and buying behavior patterns of the consumers, you can observe a clear pattern in the shopping habits of people and their frequent trips to specific markets. So this technique may open the door to potential test markets or the retail stores that fit into their buying habits.
Sales and Promotion
The analysis has the ability to bring out the basic features of your products before customers, and thus build the image of your company. Factor
analysis reveals your company’s position relative to the competitors in the market. You can check if the customers perceive your products as prestigious, value brand or low quality products. Based on this, craft your promotional campaigns with the message highlighting the specific attributes that reflect the company’s image. This technique is widely used in almost every business including, but not limited to, FMCG, automobiles and electronics.
A Cautionary Note
Factor analysis is a useful tool to obtain and manage market information. However, it requires expertise and experience to apply this technique effectively. Only experienced professionals understand the underlying ambiguity of factor analysis. The technique doesn’t allow assumptions about the data prior to collecting them. Based on the observed variables you have to create new factors and relate these factors with the consumer response. The point where most of the market analysts fail is when the factors created by them are ambiguous and difficult to relate with the industry and market. Worst, sometimes the analysts artificially manipulate the data just to come up with a result. But how can this result be accurate if it is based on artificially manipulated data? Use only the real facts and data.