1. Simple random sampling: it is the most basic sampling method and the basis of other sampling methods. That is, the research objects are numbered first, and then sampled by random number table or lottery, touching the ball, computer lottery and so on. This method can only be used when the number of samples is small.
2. Systematic sampling: This method is to extract one unit from every certain number of mechanical units in a certain order, which is also called interval sampling or mechanical sampling.
3. Stratified sampling: Firstly, the subjects were divided into several layers according to their main characteristics (gender, age, occupation, education level, disease severity, etc.). ), and then randomly sampled at all levels to form a survey sample.
4. Cluster sampling: When sampling by this method, it is not individuals, but groups (i.e. groups) composed of individuals. In other words, the whole group is divided into several "groups", and each group contains several observation objects, such as villages, workshops, classes and so on. These groups are randomly selected from the same type of groups, and all the members of the unit are the research objects.
The role of collecting data
1. Understand the market demand: Data collection can help enterprises understand the market demand, so as to better meet customer demand. By analyzing customers' behaviors and preferences, enterprises can launch more popular products or services.
2. Improve customer experience: By collecting and analyzing customer feedback and behavior data, enterprises can improve products or services and increase customer satisfaction and loyalty. This helps to increase sales and long-term profits.
3. Optimize marketing strategy: Data collection can help enterprises understand information such as customer interests, purchase history and behavior patterns, so as to better formulate marketing strategies. Through personalized marketing, enterprises can improve the conversion rate and return rate.