Analyzing POS data
For stores that have installed cash registers, POS data can also be used for quantitative analysis. POS data includes sales data for each product, as well as data on the age and gender of purchasers. For example, if the analysis shows that a certain product sells well to women in their 30s, improvement measures can be considered, such as "changing advertising that was primarily aimed at women in their 20s to creative aimed at women in their 30s" or "improving the text on in-store POP to encourage the original target audience to pick up the product."
Product monitoring survey
Product monitoring surveys using multiple choice philippines telegram phone number list questionnaires and other methods are useful for converting product awareness and satisfaction into numerical data. Opinions can be collected from loyal users of the product, and regular monitoring surveys can be used to capture trends in customer satisfaction and changes in needs.
Points to note when conducting quantitative analysis
Effective quantitative analysis cannot be performed simply by looking at numerical data. When conducting quantitative analysis, be sure to pay attention to the following points.
Ensure sufficient data volume
A sufficient amount of data is required for accurate evaluation through quantitative analysis. For example, in the case of access analysis, data from only 2-3 days may be biased, which may lead to incorrect judgments. Quantitative analysis should be performed after accumulating data for at least one to several months. Multiple choice surveys also do not allow accurate readings of trends based on the opinions of just a few people. In order to collect data from hundreds of people, it is necessary to be creative when recruiting participants.