How to calculate sales compared to last week
In business analysis and sales management, Week-over-Week (WoW) is an important indicator for measuring short-term performance changes. It can help corporate management quickly capture market trends and adjust sales strategies. This article will combine the hot topics on the Internet in the past 10 days, analyze the calculation method of last week's sales, and show actual cases through structured data.
1. Calculation formula for sales compared with last week
The month-on-month growth rate is calculated by comparing sales data from this week to last week and calculating the percentage change. Its core formula is as follows:
Month-on-month growth rate = (Sales this week - Sales last week) ÷ Sales last week × 100%
If the result is positive, it means sales are growing; if it is negative, it means sales are declining. For example: an e-commerce company's sales this week were 1.2 million yuan and last week were 1 million yuan, so the month-on-month growth rate is 20%.
2. Cases of comparative data in popular industries
Based on recent hot topics, we have compiled the sales comparison of the following industries in the past two weeks (the data is a simulated example):
| Industry | Sales last week (10,000 yuan) | Sales this week (10,000 yuan) | month-on-month growth rate |
|---|---|---|---|
| New energy vehicles | 8,500 | 9,350 | +10% |
| Prepared dishes | 3,200 | 2,880 | -10% |
| outdoor equipment | 1,800 | 2,340 | +30% |
3. Application scenarios of chain analysis
1.Promotional activity effectiveness evaluation: A certain live broadcast room found that GMV dropped by 15% this week through month-on-month comparison. The reason was traced back and it was found that no full reduction activity was set up.
2.Seasonal product adjustments: Air conditioner sales increased by 40% month-on-month, and stocks were prepared in advance based on weather forecast data.
3.Channel optimization decisions: A certain brand’s Douyin channel grew by 25% month-on-month, while Taobao’s channel only grew by 3%, so it decided to increase its short video delivery budget.
4. Key differences between month-on-month vs. year-on-year
| indicator | Comparison period | Applicable scenarios |
|---|---|---|
| month-on-month | Adjacent periods (weeks/tendays) | Short term fluctuation analysis |
| Year-on-year | same period last year | Long-term trend judgment |
5. Practical strategies to improve month-on-month growth
1.Dynamic pricing mechanism: Real-time adjustments are made based on price changes of competing products. A certain 3C brand achieved a month-on-month growth of 18% through algorithmic price adjustments.
2.Hot spot marketing takes advantage of the situation: A tea drink brand launched a series of colorful drinks based on the recent topic of "Dopamine Outfits", and its weekly sales surged 65% month-on-month.
3.Member day optimization: The original fixed Tuesday membership day was adjusted to the weekend, and the unit price per customer in a supermarket increased by 22% month-on-month.
6. Precautions
1. Special influencing factors (such as holidays, extreme weather) need to be excluded.
2. It is recommended to combine the moving average method (3-5 weeks) to smooth data fluctuations.
3. When the base number is too small (such as a new store’s first-week sales of 10,000 yuan), the month-on-month data may be distorted.
From the above analysis, it can be seen that chain calculation can not only quantify sales changes, but also provide data support for agile decision-making. During the sluggish sales period after the June 18th promotion, a certain home appliance brand accurately launched a trade-in campaign through month-on-month analysis and successfully achieved a V-shaped rebound in weekly sales. It is recommended that enterprises establish an automated chain monitoring system and refine the data granularity to the SKU level to obtain more accurate business insights.
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