From a long term perspective, forecasting customer demand and transport volume plays an important role in improving customer satisfaction as well as increasing corporate profits. The key to this process is to choose a suitable AI for demand forecasting with the minimum error and maximum accuracy.
Recently, the number of unpredictable external variables has made it more difficult to respond flexibly and quickly. Therefore, the demand forecasting AI that quickly learns large amounts of data and predicts with higher accuracy will minimize the lead times that cannot be reduced in the supply chain.
Data | Data type | Content | Use mode |
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Input data | CSV | Product price, transfer demand, advertising cost, competitor's information(price and demand, etc.) | API |
Output data | CSV | Demand (sales volume) prediction | API |
Payment | Subscription method | Attached file upon application |
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Prepaid charge | Online | Customer data required for model creation |
Application procedure |
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