Product demand forecasting service for the apparel industry
We analyze product data and weather data to provide insight into the relationship between temperature and timing for optimal sales per item.
It’s possible to forecast the demand for a specific item. First, tell us about your challenges.
case01Analyzing the relationship between weather and products (weather sensitivity survey)
Challenge:“First I need to know which products are weather-related.”
We analyze the sales data of multiple products versus weather data to visualize the relationship with weather, by timing and area.
| Sells more in hot weather |  |
 |
 |
|---|---|---|---|
| Not affected by temperature |  |
 |
 |
| Sells more in cold weather |  |
 |
 |
Use it to roughly understand the relationship between multiple items and the weather.
case02Visualizing the peak period
Challenge:“I need to know when a product will start to sell, peak, and taper off.”
We will summarize the timing of the product's “beginning of sales,” “peak” and “end of sales” cycle, as well as the benchmark temperature that triggers buying behavior, by area.
Leverage it for marketing and promotion purposes.
JWA weather forecasts and email alerts
By checking the weather forecast together with the results from the above analysis, you can understand the beginning,
peak and end of sales cycle for this year.
case03Forecasting demand
Challenge:“I want to predict how much quantity I can sell.”
We will perform analysis by matching the detailed product data such as POS, shipment volume, price and inventory, against weather data.
It is possible to forecast specific quantities and sales amounts.
Use it to adjust production volume, shipment volume, inventory volume, and for marketing.
case04Factor analysis
Challenge:“I want to understand the factors that affected sales in the past.”
We analyze past sales factors from the perspective of weather and economic factors to see which factors are critical. Objectively visualizing which factors have previously influenced sales will lead to more effective measures for the future.
| Rank | Factor | Degree of influence |
|---|---|---|
| 1 | Price | 40% |
| 2 | Temperature | 30% |
| 3 | Snow | 20% |
| 4 | TV commercial | 10% |
Use it as a resource when considering future measures.
Anticipated effects
Reduction of wasteful inventory
Avoiding out-of-stock items
Efficient production planning
Maximizing sales
by timing price reductions
Optimizing the timing of
advertising promotions
Sales activity support
Product demand forecasting service for the apparel industry
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