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Price Optimization & Neural Networks

Smarter Pricing with Neural Networks

Revolutionize your pricing by harnessing the power of neural networks. Discover hidden opportunities and move beyond the constraints of traditional approaches.
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No Hype. Just Results.

Neural network-based AI increases pricing prediction accuracy and win-rate probability by more than 30% — expediently improving profit margins and revenue across the business. The neural network adapts to market dynamics in real-time, processing new data as it occurs, while recognizing the uniqueness of each negotiated sale. All delivered with confidence through explainable AI. 

Results

Businesses around the world are using our solutions to achieve exceptional results on their journey to digital transformation. 

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4.5%

Revenue Uplift

A global US-based Food Manufacturer boost revenue using pricing technology powered by neural networks.  

11%

Margin Uplift

A global EU-based Industrial Manufacturer maximized profit margins in negotiated deals across all sales channels.  

2x

Greater Adoption Rate

Based on the analysis of PROS customers, the neural network model achieves significantly higher adoption of price recommendations compared to other pricing models.

The solution provides us with so many details around each attribute and many ways to dig into the data. In the neural network, the price prediction is significantly better, enabling us to stay ahead of inflation. PROS Gen IV AI provides more strategic pricing recommendations that align with the market and our strategy.

Frank Moore
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Frank Moore

Division Pricing Manager

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FAQs

How do neural networks enhance price optimization?

Neural networks enhance price optimization by analyzing a wide range of structured and unstructured data—product details, competitive landscape, aggregate customer behavior insights, market indices, seasonality, location, revenue, inventory levels, and even consider data gaps to learn from. This allows them to uncover complex patterns across the entire business, navigate complexity with ease, adapt to market dynamics in real-time, and deliver highly accurate price predictions and win rate probabilities your sales teams can trust.

Neural network-powered technology drives revenue and margin profit growth in weeks by translating business complexity and market dynamics into precise, competitive prices, aligned in real-time with the latest conditions and demand. It can further maximize revenue with efficient capacity utilization. Unlike segmentation models, neural networks “thrive” in volatile and highly complex business environments, such as thousands of products and customers, constantly changing market conditions, and disruptive events.  

Neural networks consistently achieve over 90% price prediction accuracy, compared to traditional segmentation models, which typically reach around 60%. This higher accuracy stems from neural networks’ ability to mimic human reasoning, analyze diverse data sources, adapt swiftly to market changes, and interpret large volumes of data. These capabilities result in more reliable and effective pricing strategies and forecasting. 

Dynamic segmentation-based pricing solutions empower B2B businesses to optimize revenue and enhance the customer experience. This is done by tailoring prices to specific segments, while considering demand, price elasticity, aggregate customer behavior insights, and value. By leveraging real-time data, these solutions enable market-driven pricing that feels fair and relevant, while allowing companies to respond to market changes, competitive pressures, and seasonal trends. This agility ensures pricing strategies remain competitive and profitable, ultimately fostering customer trust and loyalty.
An AI model based on dynamic segmentation is an excellent choice for B2B organizations with well-structured, rich historical data—such as transactions, product details, customer profiles, channel performance, and competitive insights. This approach performs best in less disruptive markets and is ideal for businesses managing similar frequently encountered sales scenarios, whether spot buys or contractual deals. Additionally, this approach is highly suitable if a company has a data science team that is experienced and comfortable working with segmentation-based methodologies to ensure effective use of the model.

Neural network-based technology enables pricing leaders to handle extensive product and customer lists with ease. It delivers competitive, market-driven pricing across a vast array of products, allowing for swift and effective optimization strategies even in complex scenarios.

Neural network-powered pricing promotes pricing discipline and enhances customer loyalty. As sales teams begin to use these prices, their confidence in the system increases, appreciating the real-time optimization and successful outcomes driven by neural networks. This results in higher adoption rates and better sales performance.