Product demand forecasting service for manufacturers

We analyze product data (shipping quantity and POS) and weather data to help you manufacture, ship and sell the right amount at the right time. 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 products by comparing sales amount against weather data to identify products that are related to the weather.

Sales
Weather sensitivity C B A
A Yogurt Soup Sports drinks
B Soy milk Ramen Ice cream
C Supplements Bread Cookies
Sales
Weather sensitivity C B A
A Yogurt Soup Sports drinks
B Soy milk Ramen Ice cream
C Supplements Bread Cookies
商材の優先順位をつけ、予測式作成など次のステップへ商材の優先順位をつけ、予測式作成など次のステップへ

Use it as a preliminary analysis to determine which products to focus on.

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.

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.

Units sold
Past Current Future
350個予測 500個予測 過去のデータから未来を予測! 350個予測 500個予測 過去のデータから未来を予測!

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.

前年より売上が増えた要因は? どのくらいの影響度があるの? 前年より売上が増えた要因は? どのくらいの影響度があるの?
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

01

Reduction of wasteful inventory

02

Avoiding out-of-stock items

03

Efficient production planning

04

Maximizing sales
by timing price reductions

05

Optimizing the timing of
advertising promotions

06

Sales activity support

Product demand forecasting service for manufacturers

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