Demand Forecasting

Use AI to forecast demand with improved accuracy and reliability

Improve forecast accuracy
Improve efficiency
Improve profitability

Demand forecasting

Table of contents

AI for demand forecasting

Demand forecasting is the process of predicting future demand for products or services. It helps businesses make informed decisions about inventory levels, production schedules and marketing campaigns, amongst other things.

Improved forecast accuracy unlocks improved efficiency, in turn unlocking improved profitability. It goes without saying—there are operational challenges to be solved, too—but, the accuracy of the demand forecast forms the foundation on which all improvements are made.

Given that so many factors must be accounted for when forecasting demand, it's a hugely complex task. A forecast must account for inputs such as historical sales data, seasonal trends, economic conditions and competitor activity, to name a few. That's why AI is the best tool for the job—AI excels at identifying patterns and trends in large datasets.


Using AI for demand forecasting provides benefits including:

  • Increased accuracy: AI improves the accuracy of demand forecasts.
  • Reduced costs: By way of producing more accurate demand forecasts, AI helps to reduce inventory costs, production costs and marketing costs.
  • Improved agility: AI can help businesses respond quicker to changes in demand, as it enables businesses to generate new forecasts faster.

Who it helps

AI demand forecasting solutions benefit businesses in a wide range of industries, including retail, manufacturing, healthcare and logistics. They benefit businesses of all sizes, from small businesses to large enterprises.

Some of the specific roles that can benefit from AI-powered demand forecasting solutions include:

  • Supply chain managers
  • Demand planners
  • Sales managers
  • Marketing managers
  • Product managers

How it works

A typical AI-powered demand forecasting solution by Datasparq works by analysing the following types of data:

  • Historical sales data
  • Seasonal trends
  • Economic conditions
  • Competitor activity
  • Real-time data, such as website traffic and social media engagement

This data is typically used to train a machine learning model to predict future demand. The model can then be used to generate demand forecasts for individual products, product categories, or entire businesses.

Getting started

As outlined above, by improving the accuracy, efficacy and timeliness of demand forecasts, AI can help businesses to reduce costs, improve profitability and improve agility.

Want to learn more about how an AI solution could help your business? Contact us today for a free consultation.

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