What key indicators need to be analyzed in sales management?
From two aspects, one is to control the sales situation as a whole, and present important indicators in a report, usually reading daily or weekly sales reports to monitor data anomalies so as to find problems in time. The other is the analysis of specific problems, which leads to business thinking, mining reasons and solutions through the presentation of data. For example, in order to increase sales volume, product comparative analysis, channel comparative analysis, and the impact of return volume on sales volume.
Therefore, what indicators to analyze, you might as well ask the sales manager to understand their needs in depth and analyze the specific problems.
Or refer to the following sales data analysis system to seek analysis ideas.
Take e-commerce retail enterprises as an example. Mainstream sales volume, order volume, completion rate, growth rate, sales proportion of key commodities, and sales proportion of each platform. More can also track profits, turnover rate (conversion rate), per capita output and so on.
Basic performance analysis:
Establish a sales analysis system to monitor and count sales performance in real time through channel organization and commodity system.
Indicator tracking:
According to the logic between data, the problem of drilling identification is summarized from the anomaly of data, from time, brand series and regional latitude.
Commodity value analysis:
Analyze the value of goods according to sales volume, profit and other indicators.
Price range analysis:
Analyze the price with profit, and analyze the price with sales.
These indicators can be tracked from the following three levels.
3. 1 index monitoring
Generally, monitoring these indicators is traditional: email submission (although it takes a long time for business personnel to integrate data, it is better than nothing); There is also a relatively high-end: led screen real-time monitoring. Either way, it is also for this purpose. Now many companies have realized the automation of index monitoring, as well as multi-platform integration and mobile monitoring.
The following is an example of a data report built with FineReport:
The above picture aims to monitor the sales indicators of the previous day. The two most important indicators (sales volume and order volume) are displayed through the dashboard, and the target achievement rate is also displayed, so that the most important information can be grasped very conspicuously. Not up to standard? According to this information, you can ask the person in charge.
Others are mainly order distribution, that is, the number of orders at various price points: it reflects the distribution of customer unit price. If the data on a certain day is abnormal, such as the sudden increase in the number of customer unit price 150, it may be the effect of store promotion (if the customer unit price drops, but the sales volume does not increase much, obviously this activity is unsuccessful), or it may be the impact brought by the launch of new products. In short, by observing the distribution of customer unit price, we can grasp a lot of information.
Distribution of commodity sales and platform sales: mainly to grasp the distribution of sales. It is still difficult to see the problem through the data of this day, and it needs to be linked together. It will be mentioned below.
Order time distribution: analyze the order concentration in each time period. For example, as shown in the above figure, the peak consumption of users is around 9 pm, 10. Through this information, we can adjust our sales strategy in a targeted manner. Of course, if the order distribution suddenly changes greatly on a certain day, it is also worth analyzing the reasons in depth.
Not only tracking the daily sales index value, but also the accumulated data can produce different feelings, as shown in the following figure.
The first is the cumulative sales achievement rate, from which we can see the overall performance. The chart on the right can be associated with this chart. When the data is abnormal, you can further view the detailed data of each month.
Monitoring the cumulative value of sales indicators is the control of the overall sales performance, and the daily newspaper pays attention to the latest data. The two should be used in combination, not only to control the overall situation, but also to pay attention to the present.
3.2 Regular allocation of indicators
Many things, please look at them independently, it is difficult to find anything unusual, but after opening the time dimension and expanding the field of observation, there will be many new discoveries. As mentioned above, product sales and distribution and platform sales and distribution.
The above picture shows the order distribution of each platform. After careful browsing, it can be found that during February (Spring Festival), the overall order proportion of Tmall platform was high; The two flagship stores on the JD.COM platform occupy more and more time. This information will help the company adjust its sales strategy.
When the data changes abnormally, you can further browse the monthly detailed data, and you can know whether the decline of store orders is due to the decline of store performance or the improvement of other stores' performance. This kind of report is not only tracking data, but also tracking the responsible person.
3.3 Comparative analysis of indicators
For example, from the regional dimension, we compare the differences between regions from multiple angles, and give invisible pressure to relevant teams through data to remind them of abnormal situations and deal with them in time.
The above picture shows the sales situation of each region intuitively through the map, and you can choose different comparison standards to show it. The two charts on the right are linked with the map, showing the target completion and year-on-year comparison in this area respectively.
As can be seen from the above figure, the actual sales situation before February was better than the planned value, but it was slightly weak after February, and the accumulated amount completed in May has fallen behind the planned amount. The reasons for poor sales need further analysis. At this time, select the comparison index of planned completion rate. If the completion rate in all areas is low, it may be the overall environment. If the completion rate in most areas is low, it may be more of a problem for regional teams.
Through this layout, the regional sales situation can be fully displayed, and the performance of the team can not be displayed by a single standard.
For example, from the perspective of commodities, comparing the value contribution of different commodities will bring pressure to brand leaders and provide reference for adjusting commodity strategies.
In the above picture, the core is the commodity profit distribution map in the upper left corner, through which the value of each commodity is reflected. This chart is suitable for a large number of commodities, and can directly show the weight of each commodity.
The two line charts on the right can be linked to the bubble chart. Let's introduce them separately:
Weight chart: shows the weight distribution of goods, and the weight value = sales volume/weekly weight coefficient, which was introduced in the last article. It allocates the weight proportion of each day according to the sales volume of each day in a week. For example, the distribution from Monday to Sunday is:1.1.1.1.65438. The value calculated in this way should be a relatively smooth curve, but we can see from the figure that the sales volume on June 18 is obviously higher than the normal value, and it can be inferred that this day is an activity day. From the following figure, we can find that the unit price of June 18 is low, which can also prove that the commodity belongs to the promotion period of June 18.
At the same time, the sales situation on June 17 was lower than normal, probably because of the activities the next day. However, if the beginning of the month is low and the end of the month is high, it may be that the operation team is slack at the beginning of the month and catches up with the performance at the end of the month.
Of course, the above conclusions are inferred from the data. If we want to verify the conclusion, we need other methods, such as ab test.