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Writer's picturemamta Devi

Using AI and Gen AI to Revolutionize Customer-Level Pricing in B2B


Written By: Gargi Sarma 


In the past, pricing plans were usually based on market trends, category-level data, or wide consumer segmentation in both B2B and B2C industries. Today, however, companies can customize prices for each unique consumer with the use of AI and generative AI. A more accurate and astute strategy, customer-level pricing enables businesses to optimize their pricing strategies and maintain their competitiveness. AI has the ability to change pricing in both B2B and B2C contexts by shifting from a broad pricing approach to one that is targeted at specific clients.


How AI and Gen AI Enable Customer-Level Pricing:

Figure 1: AI-based Sentiment Analysis


Sentiment Analysis in Negotiations: Consider entering a business-to-business pricing discussion. Real-time recording and analysis of these chats by sophisticated AI algorithms can help you spot your consumers' emotional indications. For example, does your client seem concerned about price rises or react favorably to upscale features? AI can provide insights instantaneously, enabling you to modify your pricing approach in response to sentiment. Real-time price adjustments during discussions are made possible by this technology, which is currently in use for client interactions through chats, emails, and phone conversations.


Figure 2: What Customer Behavior Patterns Can Be Predicted with AI


Customer Behavior and Browsing Data: AI can examine each customer's unique browsing or buying habits. For example, a consumer may express a desire for luxury products in one product category (premium electronics, for example) while favoring more affordable options in another (office supplies, for example). AI may create tailored prices or provide targeted discounts based on the consumer's preferences thanks to this extensive behavioral data, which raises conversion rates and improves customer happiness.


AI-Powered Dynamic Price Adjustments: Depending on time, place, and even mood, customer preferences might change quickly. Real-time price adjustments can be made using AI-powered pricing systems using client data like:


  • History of purchases

  • Background in terms of socioeconomic status

  • Prices of competitors

  • Demand and supply in real-time, businesses can optimize their margins and set customized prices that provide the client with the most value by combining these elements.

Figure 3: Dynamic Pricing Adjustments with AI


AI in B2B Pricing Discussions: To help with intricate pricing discussions, B2B organizations have begun utilizing AI. Artificial intelligence (AI) algorithms evaluate consumer data to forecast the best pricing plan that will satisfy customers while maintaining vendor profitability. These technologies assist sales teams in creating the ideal offer during negotiations by examining previous transactions, consumer preferences, and moods. For example, based on each customer's digital footprint, AI can determine the best pricing point for them while they are debating a sale on Instagram or any other digital site.

Figure 4: A Simple Framework for Generative AI Pricing Strategy (Source: Ibbaka)


Possible Use Cases:


  • Instagram Vendor Pricing: Because Instagram sellers frequently interact directly with consumers, AI can suggest customized prices based on the platform's knowledge of the customer's tastes, past purchases, and financial situation. Consider a scenario in which a vendor requests a price, and AI instantaneously determines the best pricing based on client information.

  • B2B Services and Procurement: Depending on the quantity or regularity of orders, B2B clients frequently bargain for various pricing arrangements. Procurement teams can use AI to find the best prices for each customer based on their unique requirements, previous purchases, and negotiating mood.


Figure 5: Mapping Three Commom AI Monetization Strategies to Value Capture Tactics

Examples:


  • IBM used its Watson AI to examine the emotion and behavior of its customers during negotiations. Watson AI processed past customer data to deliver real-time pricing strategy recommendations, enabling sales teams to tailor offers according to past negotiations and client preferences. Customers felt they were receiving personalized offers, which increased customer satisfaction and resulted in a 5% boost in conversion rates.

  • Large enterprise clients' price packages are tailored by AWS using AI algorithms according to their service requirements, geographic location, and consumption trends. For instance, companies that need a lot of storage pay less for cloud storage services, while companies that require a lot of processing power receive special deals. Stronger client retention and improved profits are the results of an AI-driven strategy.

  • Based on each customer's digital footprint, previous purchases, and engagement data, XANT (previously InsideSales.com) uses artificial intelligence (AI) to forecast the best pricing tactics for them. In order to ensure that deals are finalized at prices that satisfy both the vendor's profitability goals and the objectives of the client, this allows B2B enterprises to dynamically alter pricing in real-time during negotiations.

  • Based on past purchases and supplier connections, SAP Ariba's AI-powered procurement solutions employ generative AI to forecast pricing trends and provide the best procurement offers for companies. A business that routinely purchases raw materials, for instance, can receive dynamic pricing modifications based on market conditions, which lowers procurement costs and improves supplier relationships.


Ethical Pricing and Personalization: 


While AI can tailor rates to maximize customer satisfaction and profitability, businesses must exercise caution regarding legality and fairness. Dynamic pricing shouldn't result in unfair business practices where clients with less knowledge or less negotiating power routinely get inferior offers. Even with AI-powered pricing methods, transparency is crucial to preserving confidence.


Conclusion:


Retail and B2B services are two businesses that are fast changing due to the move towards customer-level pricing driven by AI and Gen AI. With the use of these technologies, companies can now offer customized prices that take into account the unique demands, interests, and behavior of each individual client, going beyond broad-based pricing methods. AI's capacity to instantly determine the best rates will become a crucial difference for companies in a variety of industries as it develops.

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About RapidPricer


RapidPricer helps automate pricing and promotions for retailers. The company has capabilities in retail pricing, artificial intelligence, and deep learning to compute merchandising actions for real-time execution in a retail environment.


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