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AI: Virtual Customer Modelling

PriceBeam's virtual customer technology leverages Artificial Intelligence (AI) to transform market research data into detailed models that predict how different consumers might respond to various products and pricing. These virtual customers are then "consulted" in simulated scenarios to determine the choices they would likely make.

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AI: Virtual Customer Modelling

RGM Optimizer & Simulator enables users to create a "virtual customer" to simulate real-life market scenarios and determine potential choices their customer would make. RGM Optimizer & Simulator relies on a continuous feed of data, sourced from PriceBeam’s Predictive Research and/or RGM Data Lake. The Data Lake serves as a repository of revenue and pricing insights, offering best-practice analyses curated by pricing experts. 

Virtual Customers
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How it Works

Users can simulate various market scenarios—like price adjustments or competitive responses—to visualize potential outcomes. Based on these simulations, decisions can be refined, and strategies optimized in real-time, providing a continuous loop of feedback and improvement.

  • Data is collected from market research and historical sell-out data.

  • The Virtual Customer model is trained on the collected data.

  • The virtual customers are "consulted" as to how they would choose between products offered in the market simulation.

  • Analysts can create a variety of simulation scenarios, each applied to the virtual customer model, and the analyst can determine most favourable scenario.

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Predictive Analytics & AI Modelling

Tap into PriceBeam's Virtual Customer Modelling and simulate market scenarios. 
 
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Pricing & Revenue Growth Challenges Solved

Simulating Price Changes

RGM simulation can model different pricing strategies to understand their impact on sales and profitability. This includes simulating how changing prices over time can affect demand and revenue, measuring how sensitive customer demand is to price changes, and finding the optimal price points to maximize profit or market share.

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Simulating Assortment Scenarios

Assortment simulation helps in determining the best mix of products to offer. This involves Product Mix Analysis, i.e. evaluating which products should be included in the assortment based on sales data, profitability, and customer preferences. 

Similarly, it supports Category Management decisions by understanding how different product categories interact and affect overall sales.

 

Running What-If Scenarios on Competitors' Actions

Understanding and reacting to competitor actions is crucial for maintaining market position. RGM simulation can help with competitive pcricing such as analyzing how competitors' pricing strategies impact your market share and adjusting your prices accordingly.

Similarly, it can help simulating the impact of new competitors entering the market or existing ones exiting, or evaluating the potential impact of competitors launching new products and planning your response.

Competitive Analysis