First, collect data for analysis. Don’t forget to include data from
physical stores (offline) as well as e-
commerce sites (online). If you are running sales or discount campaigns, you ned to take into account that the prices are discountd from the regular price. In addition, since the amount of data is often huge, it is a good idea to secure analysis resources in advance.
②Set the standard values for each index of R, F , and M
The collectd data will be usd to actually phone number library group customers, but in order to do so, you will ned to set a standard value for each of the three indicators: R, F, and M. For R (latest purchase date), the values would be ” within 1 week , ” ” within 2 weeks , ” ” within 1 month,” ” within 2 months, or before that,” etc.
The optimal benchmark value will vary depending on the products and scale of your business. The benchmark you set will affect how you approach customers in the future, so you need to give it careful consideration.
3) Group customers and visualize them with graphs and tables
Once you have set the benchmark values for each of the three indicators, you can group customers according to those benchmark values.
You can then visualize the distribution and how to choose the best words? changes using graphs and tables to make the overall picture easier to understand.
Analysis can be done sufficiently using Excel , but if you want to perform more advanced analysis, if the amount of data to be analyzd is huge, or if it is stord in multiple departments, it is more convenient to use dedicatd software or tools.
The ultimate goal of RFM analysis is to effectively utilize the results of the analysis.
It is important to set current issues using the results of the analysis that dividd customers into groups, determine which group betting data should be approachd first to solve the issues, and then consider and decide on the best approach for that group, and link it to actual marketing measures . Make effective use of the results of RFM
analysis to solve issues such as retaining current good customers, digging up dormant customers, and winning back customers who have left .
