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What is the most effective demand estimation method for your product?

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Demand estimation is the process of predicting how much of a product or service consumers will buy at different prices, income levels, and other factors. It is essential for businesses to understand the demand for their products, as it affects their pricing, production, marketing, and profitability decisions. However, not all demand estimation methods are equally effective for every product. In this article, we will discuss some of the most common methods and how to choose the best one for your product.

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1 Survey Method

The survey method involves asking potential or existing customers about their preferences, willingness to pay, and purchase intentions for your product. You can use different types of surveys, such as interviews, questionnaires, focus groups, or online platforms, to collect data from a representative sample of your target market. The survey method is useful for obtaining direct feedback from customers, testing new product concepts, and estimating demand for niche or innovative products. However, it also has some limitations, such as high costs, low response rates, biased answers, and inaccurate predictions.

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Parag Aggarwal

Chartered Wealth Manager (Associate Partner, BlueFort Financial) | Angel Investor & Investment Council Member (@Venture Catalysts VC Fund)| MBA, IIM Lucknow'2011
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People often are biased in their responses. They want to sound logical, objective and smart. However their actual purchase decisions are not necessarily all logical (ample research to prove this). This is one big barrier of this method.

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2 Experimental Method

The experimental method involves manipulating one or more variables that affect the demand for your product, such as price, quality, features, advertising, or distribution, and observing the changes in sales or market share. You can conduct experiments in controlled settings, such as laboratories or simulated markets, or in natural settings, such as stores or online platforms. The experimental method is useful for measuring the causal effects of different factors on demand, testing the elasticity of demand, and optimizing your product strategy. However, it also has some challenges, such as ethical issues, external validity, scalability, and complexity.

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Parag Aggarwal

Chartered Wealth Manager (Associate Partner, BlueFort Financial) | Angel Investor & Investment Council Member (@Venture Catalysts VC Fund)| MBA, IIM Lucknow'2011
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While a great way to identify a causal relationship, this method usually takes a long experimentation time, since multiple iterations need to be done.

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3 Regression Method

The regression method involves using statistical techniques to estimate the relationship between the demand for your product and various explanatory variables, such as price, income, population, competitors, seasonality, or trends. You can use historical data from your own sales records, market reports, or industry sources to build a regression model that predicts the demand for your product based on the values of the explanatory variables. The regression method is useful for identifying the key drivers of demand, forecasting future demand, and evaluating the impact of changes in the market environment. However, it also has some drawbacks, such as data availability, quality, and reliability, model specification, and assumption violations.

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4 Artificial Intelligence Method

The artificial intelligence method involves using machine learning algorithms to learn from large and complex data sets and generate demand estimates for your product. You can use various types of data, such as text, images, videos, audio, or social media, to train an artificial intelligence model that captures the patterns, preferences, and behaviors of your customers. The artificial intelligence method is useful for handling unstructured and dynamic data, discovering hidden insights, and adapting to changing market conditions. However, it also has some risks, such as data security, privacy, and ethics, model interpretability and explainability, and human oversight and intervention.

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5 How to Choose the Best Method

There is no single best method for demand estimation that works for every product. The choice of the method depends on several factors, such as the nature and characteristics of your product, the availability and quality of data, the objectives and scope of your analysis, the resources and time constraints, and the accuracy and reliability of the results. You should consider the advantages and disadvantages of each method, compare their costs and benefits, and evaluate their suitability and feasibility for your product. You may also use a combination of methods to complement and validate each other and improve your demand estimation.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What is the most effective demand estimation method for your product?

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3

4

5

6

1 Survey Method

2 Experimental Method

3 Regression Method

4 Artificial Intelligence Method

5 How to Choose the Best Method

6 Here’s what else to consider

Economics

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What is the most effective demand estimation method for your product?

1

2

3

4

5

6

1 Survey Method

2 Experimental Method

3 Regression Method

4 Artificial Intelligence Method

5 How to Choose the Best Method

6 Here’s what else to consider

Economics

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