Panel Data

What is panel data?

Panel data is information derived from observations of a group of consumers, called a panel, representing a larger population or audience. It is gathered by consistently monitoring specific variables over time and at regular intervals, typically through surveys or interviews. Usually, many variables are observed to increase data size and reveal correlations. As a result, panel data can help marketers understand important consumer patterns such as purchasing habits, income, demographics, and household data.

What are the advantages of panel data?

Understanding buyers – Panel data allows organizations to collect detailed information about consumers, such as shopping habits, demographics, opinions, and household information. Marketers can use this information to personalize their marketing and sales strategies.

Discovering correlations – Because panel data combines multiple variables, marketers can make correlations between variables. This creates links between attributes of buyers and their purchasing behaviors, helping marketers to predict how these consumers might behave when introduced to their products.

Reveal future trends – Panel data allows organizations to review how variables are changing over time and how they could affect trends in the future. This may give them insight into how the market is changing or where consumers are likely to spend their money.

How is panel data collected? 

Panel data is collected through surveys and by point of sale systems. Surveys are conducted to collect basic information about consumers and their opinions and feelings about a brand or product. Point of sale systems collect sales data each time customers purchase products. Companies can then purchase this data from the vendors to understand how potential customers are spending their money.

Panel data use case

Panel data helps companies understand changes such as increasing or decreasing sales and adapt to or capitalize on these changes. For example, if a grocery store notices sales have increased, they can look at panel data about spending habits to see if they are attracting new customers or if current customers are spending more. In addition, they can see what people are buying and if any demographic attributes may be consistent among those spending more.