How To Do A Good Job Before The Sales Promotion Of Clothing Store Before Sales Promotion

Immediately after the National Day holiday, the shopkeepers are thinking about how to do a good job in sales promotion. When it comes to sales promotion, most of the planners first think of what activities to attract people. Putting the activity first, rather than putting the sales analysis first, Xiaobian thinks that this is a wrong approach and is likely to be promoted as a result of promotion. So, how to carry out sales analysis? What preparations should be made for the promotion of clothing stores in the coming national holiday? Now let's take a look.

Market environment analysis

If the market in which an enterprise is located is a municipal market, then the market will have a reference market. What is referring to the market? That is, the sales pace is slightly faster than that of the regional market. To put it simply, the sales structure and price of the next phase refer to the market structure and commodity price. So when you do sales analysis, referring to the market's performance is the important analysis reference.

Such analysis may be easier for chain enterprises, because sales records are very confidential business data, and no enterprise will easily disclose them. So the local retail enterprises can only get some piecemeal price information, and predict the future price changes of the market through these information.

　 Historical data analysis of sales

The analysis of historical data usually only analyzes one cycle upward, for example, this year's "eleven" sales forecast analysis. Only this year's may day and last year's May 1 and eleven can be analyzed. Historical data analysis projects include:

1, the sales of each brand of each category account for.

2. Sales of each subcategory in each category.

3. The proportion of each brand's classified sales is accounted for.

4, the sale of each category of price segment ratio.

5, the sales price of each brand is accounted for.

Through analysis, we can find out the dominant brands, advantages classification and dominant price segments of each category, the advantages of each brand and the superior price segments, so as to lay a solid foundation for identifying key promotional products. These analyses help operators to grasp the structure and changing rules of consumer demand, not only have a deep understanding of the static structure of sales, but also grasp the direction of the dynamic change of sales.

Then, what indicators are often used in the analysis of historical data? When analyzing these indicators, we should pay attention to the following questions:

Commodity sales structure

The first dimension to understand sales in subdivision level is the structure of commodity sales. The commodity sales structure refers to the proportion of all kinds of goods sold by enterprises in sales. It needs to calculate the proportion of single commodity in the total sales. Then, the sales ratio of all commodities is aggregated into a form, and the structure of the commodity sales of the enterprise is formed.

The formula is: Sales of single product = sales of single category goods. The total sales volume is 100%

To calculate the sales structure of an enterprise, it is necessary to classify the commodities sold by the enterprises. According to the categories of commodities, the companies can be classified into categories of refrigerators, washing machines, TV products, computer products, mobile phone products, kitchen and toilet products, digital goods and so on. For certain commodities, they can also be divided according to the subdivision of commodities, such as TV products, which can be divided into picture tube TV, LCD TV, plasma TV, rear projection TV and so on. They can also be divided into 21 inches, 25 inches, 29 inches, 32 inches, 42 inches according to the screen size. The sales structure based on different dimensions reflects different problems.

Year-on-year growth rate

The year-on-year growth rate refers to the growth of a certain area (sales, profits, etc.) and the corresponding growth in the same period last year.

The formula is: year-on-year growth rate = (data this year - last year's data). Last year's data X 100%

Sales of many products are seasonal or cyclical. The structure and intensity of the forces that affect sales factors in May and May of last year are roughly the same, which is the premise condition for using the year-on-year growth rate indicators.

However, in fact, this assumption is only established within a certain scope. There are always some differences between this year and last year. Therefore, when using the year-on-year growth rate index to analyze sales, it is necessary to add qualitative text analysis to assist the specific situation.

For example, the Spring Festival in 2017 is in January 28, 2017, and the Spring Festival in 2018 is in February 16, 2019. In this way, sales in January 2018 are much worse than those in January 2017, and sales of the products are much better than that of the sales. This example is obvious. There are still some situations that are more subtle and not easy to judge. For example, in August 2016, the sales of kitchen and bathroom products in a home appliance market dropped a lot compared with that in August 2015. How could we not find out the reason? Finally, we found out the original store manager and cabinet length to understand that there were several residential areas around the shop in August 2015. The owners went to this home appliance store to buy kitchen and bathroom products to decorate the new houses, which made the sales go higher. Therefore, when using the year-on-year growth rate index to analyze sales, we must carefully compare the specific situation before and after making a judgement.

Using the year-on-year growth rate index to analyze sales defects is far away from each other.

Cycle growth rate

The growth rate refers to the growth of one aspect (sales, profits, etc.) and the previous period.

The formula is: ring growth rate = (current data - above data). Last period data X 100%

Because time is not far away from each other, the factors that affect sales do not change very much, making the pre and post sale comparability comparable. This is the premise hypothesis of using the rate of growth rate to analyze the sales. The growth rate index has overcome the defect that the growth rate of the year is too far away and some hidden changes can not be identified. But it also has shortcomings: it is not suitable for sales analysis of cyclical products.

In addition, sales of obvious commodities during holidays are not suitable for the analysis of growth rate index. For example, the sales of household electrical appliances in Beijing are mostly concentrated on Saturday day promotions, making sales on the two day of the weekend heavier. If the number of weekends is less than that of last month, the growth rate index will be affected.

Therefore, both the year-on-year growth rate and the growth rate index have certain defects. The analysis of indicators alone can not reflect the whole picture of the problem.