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2025-04-06 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > Internet Technology >
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Shulou(Shulou.com)06/02 Report--
To use a less appropriate example, we will browse the moments when we have nothing to do. after watching it, how to live or how to live? there is no way to save ourselves from the predicament in the moments. Maybe the love shown in the moments actually makes us more miserable. But we will still watch, because this is a kind of information transparency, ah, I have such curiosity, I need to know this information. This is especially true for the performance of enterprises, such as real-time performance monitoring, that is, if they have nothing to look at, they will achieve the transparency and symmetry of information.
This kind of report has a little meaning of "keeping troops for a thousand days and using troops for a while". You can't show it when you don't have a chance. If you catch an opportunity, it will do a lot of work.
Second: the amount to reflect the value, but appears to be worthless
Because we are afraid that the report will have no value after it is made, we should be "serious" when planning, think of ways, find information, and take the time to sort out a set of analysis system, hoping that this analysis system can bring upgrading effect to the company's business, such as the commodity theme in the following figure.
So much content can be sorted out, and there may be more. Ideally, these contents are developed, so that enterprises have a comprehensive analysis and management of goods. But reality is rarely ideal, and nine times out of ten, when so much content is developed, it is not used by many people for the following reasons:
1. There is no corresponding responsible person. If a report is to be used, someone must be responsible for it. For example, the store manager hopes to get rid of the abnormal goods in the store, and too many abnormal goods must affect his kpi, then he will certainly pay attention to the abnormal goods in the store, low inventory should be prepared to order, negative gross profit to carry out price adjustment, sales should think about promotion / adjustment of shelves / counter-transportation, and so on. If you look at the product life cycle analysis, who will be responsible for it? No one cares about it, it just sounds awesome, how can it be used?
two。 put away the cup after taking a tiny sip. I did a lot of analysis, but I didn't go deep into one of them. Two concepts, one is that at the report level, there is only a general data presentation, even if the analysis, such as commodity abc, there is nothing else outside the list of abc products. The other is that it has not been promoted in depth. When a set of reports is completed, it needs to be physically improved, and at the same time, it needs to be matched with its usage, value description, looking for its responsible person, and follow-up promotion and application feedback, to give an example, such as commodity price analysis.
FineReport data decision table
From the point of view of the content of the report, it is necessary to show the transaction number, sku number, sales / gross profit margin of each price point in the commodity price range. A further step is to explain this report, such as:
Analyze the sales volume of each price, find the price point, and display more abundant goods near the price point, which can give consumers a feeling that the goods are rich and the price is moderate.
Analyze the number of sku in the price range, the number of transactions, etc., summarize the main consumers in the store, and then through the comparison of management reports, we find that if the goods in our store are far below the average level, we can start with the analysis of the price band to see if our crowd is mislocated.
Display the price belt of all kinds of commodities to see if there is a price gap, which should be avoided as far as possible.
If you find that the sales volume of your price-intensive belt is not the highest, it is necessary to further analyze whether your price point is mislocated.
Through the survey, we can analyze the competitor's price point and the depth of the price band, so as to analyze the competitor's crowd positioning.
The users of this report should be category managers and store managers, because they are responsible for category and store sales, and the analysis and use of price bands can obviously help to improve sales.
Similarly, the fluctuation analysis of sales, sales ratio and customer unit price is basically useless if we simply make such a report.
What does the increase in sales and the number of sales letters mean by the decline in the unit price of customers?
What does the increase in sales, the decline in the number of sales and the increase in customer unit price represent?
What does the decline in sales, the number of sales and the increase in customer unit price represent?
After all the above contents are added, the attention of the business staff will be attracted and the person in charge of the report can be found.
As can be seen from the above, it is not easy to make a good use of one of these valuable topic reports, so don't think about using all the content, focusing on a topic is much more valuable than doing a lot of analysis.
Third, users do not recognize value.
When the report is finished, it is really used. What is more touching is that the performance of each store is indeed better, but they do not think it is the credit of the report. This happens all the time, but it is difficult for me to explain it. I just want to say that I am worthy of my parents.
Conclusion: "intelligence" is too high for the majority of enterprises, for most enterprises, the value that data can bring is very simple, so simple that it is spoken in vernacular and can be understood without technical basis. Some are "simple" but useful, some are very high but no one uses them, and in general, the more "simple" it is, the more useful it is (this simplicity does not mean that the production is easy to promote, but it is simple to understand, or even common in daily work). Sometimes I wonder if I should forget "big data" when I really do something.
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