Take CRM system as an example to explain data analysis (importance introduction and analysis method)

seeing the name of a thing one thinks of its function ,CRM Refers to customer relationship management , yes Customer Relationship Management For short , Refers to the enterprise to improve its core competitiveness , Use the corresponding information technology and Internet technology to coordinate sales between enterprises and customers 、 Interaction in marketing and service , So as to improve its management , The process of providing customers with innovative and personalized customer interaction and services .CRM The main values of ：

  Doing it CRM front , We should first clarify what data we need to analyze , To make data valuable , It must go through the process of processing, analysis and display , Then present it to the terminal management and operation personnel for review 、 track , Understand the current business development , To achieve a breakthrough in growth , And the problems of operation and management . The first step in analyzing data is to follow up on key indicators .

Key indicators follow up

Focus on the passenger flow in daily operation 、 Intention information 、 Order 、 sales 、 Multiple indicators such as chargeback ：

• passenger flow ： Number of customers entering the store
• Information ： Number of intended customers
• Order ： Number of scheduled orders
• Main order ： Number of production orders
• Information retention rate ： The conversion rate of passenger flow to intended customers （ Number of intended customers / passenger flow *100%）
• Information conversion rate ： Conversion rate from intended customers to scheduled orders （ Number of scheduled orders / Number of intended customers *100%）
• Refund rate ： Number of chargebacks / Number of scheduled orders *100%
• Order conversion rate ： Conversion rate from pre order to production order
• Collect money ： Total amount collected
• Completion rate ： Payment collection completion rate

CRM The analysis process

The above key indicators are defined , We can start the specific process of data analysis , I will start from pre-sales 、 On sale 、 Start with three major aspects of after-sales , Customer relationship management is divided into six stages for specific analysis .

  pre-sale ： Get customers in the market , Clue analysis

In the pre-sales stage , We get customers through various channels and enter crm The system becomes a clue , We need to analyze market clues , Analyze the number of leads and the proportion of customers transferred , So as to further carry out marketing analysis .

  On sale ： Customer follow up , Business opportunity analysis

In the sale stage , Promote the business process through the follow-up of sales staff to customers , We need to analyze our customers , Analyze the number of customers and customer resources , So as to further analyze the business opportunities .

  after-sales ： After-sales service , Order analysis

In the after-sales stage , Through the implementation and completion of customer chargeback and other services , We can analyze and summarize the whole customer relationship management , Based on the overall situation , Analyze the order .

  In the specific analysis stage , There are still many details that need our attention , The most important is the analysis of the sales process and the stratification of customers , I will use external tools to explain the analysis of these two stages in detail .

Sales analysis ： Sales funnel

When we conduct sales analysis , Generally, the following analysis dimensions are involved .

• Sales efficiency analysis . Include sales or sales 、 Performance completion rate 、 Year on year growth 、 Customer unit value .
• Market analysis . Market share .
• Personnel analysis . Sales ranking .
• Profitability analysis . Gross margin on sales 、 Net interest rate 、 Cost rate and other financial indicators .
• Operational efficiency analysis . Inventory turnover 、 Turnover rate of accounts receivable 、 Unsalable inventory ratio .（ My company is a customized product , It does not involve finished product inventory , And the company is only responsible for terminal sales and services , So there is no material 、 Inventory analysis of semi-finished products .）
• Channel analysis . Channel sales / Proportion of sales volume 、 Channel gross profit margin 、 Channel customer unit value, etc .
• Product analysis . Product structure analysis 、 Hot item analysis 、 Analysis of product matching rate 、 Analysis of average unit price per customer .
• Customer analysis . Customer area analysis 、 Customer unit value analysis 、 Customer conversion rate analysis （ Sales funnel ）、RFM analysis
• Timing analysis . Time change analysis 、 Year on year and month on month analysis .

The picture above shows the classic marketing funnel , The image shows a sub link in the whole process from obtaining users to finally transforming into purchase .

The conversion rate of adjacent links refers to quantifying the performance of each step with data indicators , So the whole funnel model is to split the whole purchase process into steps , Then use the conversion rate to measure the performance of each step , Finally, find out the problem link through the abnormal data index , To solve the problem , Optimize this step , Finally achieve the purpose of improving the overall purchase conversion rate .

Experience template ：CRM System https://www.jiandaoyun.com/index/solution_center/crm

Customer stratification ：RFM Model

In the customer analysis stage , The pain point faced by many enterprises is that they will not tier customers , I don't know how to mine customers with these data ：

• What is our profit contribution to customers ？
• Who are our loyal old customers ？
• Which are our regular customers who need to tap their purchasing power ？
• Which high-value customers we need to focus on facing possible loss ？
• What are our new customers 、 Who are our regular low-frequency customers ？

To answer these questions , First, we need to present them with visible data analysis indicators . just as Peter · Drucker What I have said “ If you can't measure it , You can't grow it ”. Let these static data move , Become vital and valuable information , Help us achieve customer growth , Maximize customer value , Enhance customer stickiness ,RFM The model will help you achieve this goal ：

In many user value analysis models ,RFM Models are widely used .

  Take it down into a plane , Easier to understand ：

 R（Recency） ： The time interval of the customer's last transaction . F（Frequency） ： The number of transactions made by customers in the latest period of time . M（Monetary） ： The amount of the customer's transaction in the latest period of time .

The model is through a Customers' recent purchase behavior 、 The overall frequency of the purchase and how much it cost Three indicators , To describe the customer / User Value status and profitability .

  Visible from above , According to these three indicators, we can judge the type of customers , So as to further layer customers .

R（Recency） ：R The bigger the value is. , Indicates that the longer a customer transaction takes place , On the contrary, it means that the date of the customer transaction is closer .R The bigger the value is. , Prove that the longer this customer sleeps , The greater the possibility of loss . F（Frequency） ：F The bigger the value is. , The more frequent the customer deals , On the contrary, it means that the customer is not active enough .F The more valuable customers are our loyal customers , It's they that activate our store traffic . and F Low value customers , They have little stickiness with us , Loyalty is loose , You may face the risk of being robbed by your competitors at any time . M（Monetary） ：M The bigger the value is. , The higher the customer value , On the contrary, it means the lower the customer value .M The more valuable customers support our performance , If we use Pareto distribution to analyze , Maybe you will find , It is this. M Worth a lot of money 20% Customers , Supporting our performance 80% The sky of ！

Experience template ：RFM Performance template

summary

That's about crm All the dry goods of data analysis , All of them are the essence of years of work experience , Everything is difficult at the beginning , It doesn't matter at first , Believe in those who have aspirations , A way ！

I hope the above answers are helpful .

This article deals with CRM Implementation tools ：CRM Customer management system