Sensing demand is the practice of using data to anticipate customer needs and guide decisions related to product development, marketing and forecasting. Companies use sensing demand to gain insights into customer behavior, preferences, and trends, allowing them to respond quickly to changing market conditions and capitalize on emerging opportunities.
Inputs for Demand Sensing
It's critical for an organization to understand the following around customer behavior, preferences, and trends.
Market Research: Gather information about customer preferences and market trends.
Historical Data Analysis: Analyze past sales and marketing data to identify areas of opportunity.
Pricing Strategies: Evaluate pricing models and strategies to maximize profits
Promotional Activities: Develop and execute promotional plans to increase demand
Distribution Channels: Identify and leverage distribution channels to reach target markets.
Additional inputs include:
Historical Sales Data
Customer Reviews & Market Surveys
Price Elasticity Models/ Competitor Pricing Information
Consumer Sentiment Data, Social Media Posts, Geographical Data
Why is Demand Sensing Important?
Demand sensing is crucial because it helps organizations better understand and anticipate customer behavior and demand for their products and services. Using demand sensing analytics can help organizations identify and act on insights to improve customer service and optimize pricing, and promotions. Additionally, demand sensing can help organizations stay ahead of their competition by predicting market trends and adjusting their supply chain accordingly. Finally, demand sensing can help businesses lower costs by reducing inventory, avoiding stockouts, and minimizing costly markdowns.
Today’s demand management tools can capture quantitative and qualitative demand insights from online and offline data inputs, including the ability to annotate the data with notes that document changes and assumptions. In Demand Sensing, custom calculations help you spot trends, identify forecast variances, and respond to other demand stream changes quickly and efficiently.
As we continue this series, we will discuss demand predicting and shaping as critical parts of a customer-centric approach.
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