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The Complete Guide on Customer Demand Forecasting in Retail

When you can call a demand for certain product correctly, it is the ultimate advantage among the competitors. To build your strategy you need to be armed with the best technology, and that’s where Machine Learning comes into play. In this article, I would like to talk about the ways you can improve customer demand prediction. 

1. The 5 Determinants of Demand are the following:

  • Product price.
  • Customers’ income.
  • Prices of complementary goods or services.
  • Customers’ tastes.
  • Customers’ expectations.

2. How Each Determinant of Demand Affects It

A better way to understand how each determinant affects demand is to assume that all other determinants, except for this one, do not change. So, all other indicators being equal, let’s take a look at each of them separately:

  • Product price — When prices rise, demand falls – that’s what the Law of Demand tells us. Subsequently, when prices drop, demand rises. Purchasing decisions are usually guided by price if all other factors are equal.
  • Customers’ income — When income rises, demand rises as well. But it’s not always that you would like to buy twice as much of a certain good or service. For example, earning more does not mean you need two, three, or four different shoe horns, because one is enough for everyday usage.
  • Prices of complementary goods or services — The price of related goods and services will also raise the cost of using the product you need, so you will want less. The example might be a price for gas that rose $4 a gallon in 2008. Consequently, the demand for Hummers dropped for one reason — gas is a related product to Hummers.

 Demand rises also when the consumers’ tastes, preferences, and desires change, and they suddenly begin to like the product. And vice versa, if consumers’ tastes change to not favor a product, demand drops. Advertising a brand can influence consumers’ desires for a product. Expectations, along with actual desires, also affect the level of demand. That is when people expect that a product will have more value, they increase the demand for it.

3. Types of Demand Forecasting

The types of Demand Forecasting vary and can be influenced by multiple factors such as time span, the scope of the market, or the level of detailing. They are split into two groups: time period based and economy based. Let’s take a look at what subtypes correspond to each of these two types. 

3.1. Economy based

  • Macro-level prediction — This forecasting type considers the overall economic environment, dealing with the economy measured by the Index of Industrial Production, the country’s level of employment, national income, etc.
  • Industry-level prediction — Industry-level prediction, obviously, deals with the demand that a particular industry’s products will have. For example, the demand for cars in the USA, the demand for electric scooters in the USA, etc.
  • Brand-level forecasting — Brand-level forecasting means predicting the demand for the products of a particular brand or firm, such as Adidas, Nike, etc.

3.2. Time period based

  • Short-term forecasting — This one deals with a short time span such as six months or less than a year, but it depends on the nature of the industry. Short-term forecasting is more suited for fast decisions rather than strategy.
  • Long-term forecasting — Long-term forecasting implies making forecasts for a long period of time, such as two to five years or more. This forecasting type can give valuable strategic information to a business (e.g., moving to another market segment, extending a plant’s capacity, etc.).

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