The first of these allows us to identify patterns between different values, and the second allows us to predict how one parameter will behave when another changes. All of this is expressed in strict formulas, and calculations are made with numerical data.
Let's say marketers have determined list of usa number that the average cost of attracting one customer is 500 rubles. This means that if a company plans to acquire 10,000 new customers, the budget for an advertising campaign should be at least 5 million rubles.
Variance factor analysis
In this case, it is determined how some qualitative variables (factors) influence the value of a dependent quantitative indicator. One or several factors may serve as the initial ones for the study, based on which the analysis may be single- or multifactorial. The latter type is more complex: here it will be necessary to take into account all causal parameters and look for their relationship leading to optimal consequences.
Variance factor analysis
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For example, it calculates how the location of a retail outlet, its days of operation, the type of customer service (cashiers or self-service), etc. affect sales levels.
Cluster analysis
In this case, objects are grouped into classes (clusters) in accordance with key features by which classification can be carried out. This tool is most appropriate when working with client bases: here it makes sense to divide buyers into groups by income level, age, gender and other characteristics, and then formulate several trade offers designed for different categories of consumers.
Methods of descriptive statistics
Most often they are used to process "raw" data. In this case, a specific result can be presented in different forms: average values, as well as minimums and maximums (check size, number of repeat purchases, etc.), graphs, tables, etc.
Of course, this is not a complete list of analytical tools. Their selection should be made based on the business task. Different methods will be optimal for achieving certain goals.