AI - Increasing the Effectiveness of B2B and B2C Sales Activities through Discount Policy Optimization

22 05 2024
News |
Business advice

The future of enterprises is now inextricably linked with the use of artificial intelligence, and companies see AI as the key to success.

AI as a Competitive Advantage

In the rapidly changing world of business, artificial intelligence (AI) is becoming an indispensable tool that can provide a competitive edge. For business owners looking to enhance operational efficiency and profitability, AI offers a wide array of possibilities.

In this article, we will discuss two key areas where AI can significantly impact business success: optimizing discount policies and assigning discount codes. These aspects can improve the effectiveness of existing sales platforms in B2B and B2C channels.

This article describes two projects undertaken for our clients, ultimately generating the following benefits:

• Revenue Optimization

• Increased Sales Conversion

• Enhanced Customer Loyalty

• Quick Adaptation to Market Changes

As part of these AI-driven projects, we defined two tasks.

Task 1: Optimal Discount Policy

Input Data

We collected data on customer behavior history - information on granted discounts, profiles, purchasing dynamics, and characteristics stored within the client's infrastructure. We also obtained data from Google BigQuery.


  1. Determining Customer Price Elasticity: We analyzed historical data using AI algorithms to understand how different discount levels affect individual customer purchases. This enabled precise adjustment of the discount policy.

  2. Customer Scoring at the Beginning of the Month: We developed a scoring model based on machine learning (ML) to evaluate customers based on their profiles and purchase histories, determining the optimal discount level.

  3. Combining Business Knowledge with AI Algorithms:

    • Decision Rules (JSON format): Expert knowledge was translated into decision rules guiding the discount policy.
    • ML Algorithms (Scoring): ML algorithms allow continuous assessment and classification of customers.
    • Reinforcement Learning (Multi-Armed Bandit): Learning algorithms that adjust discount levels in real-time based on changing customer behaviors, ensuring continuous improvement of the discount policy.

Benefits for Business Owners

Increased Customer Loyalty: Precisely tailored discounts boost customer satisfaction and loyalty.

Revenue Optimization: A flexible discount policy maximizes revenues through intelligent discount management.

Quick Adaptation to Market Changes: AI algorithms enable rapid adjustment of discount strategies to changing market conditions.

Task 2: Optimal Discount Code Assignment Policy

Input Data

In addition to the data collected for task 1, we gathered information on customer behavior on the website - current session and previous sessions within a specified time window.


  1. Identifying Customer Price Sensitivity: We analyzed customer behavior on the website using AI algorithms to identify their price sensitivity to specific products.

  2. Real-Time Event Stream Processing:

    • Complex Event Processing (Kafka Rest Proxy, Kafka, Apache Beam): We utilized stream processing technologies that allow real-time analysis of customer behavior.
  3. Contextual Bandit (ML Algorithms + Reinforcement Learning): Contextual algorithms adjust the assignment of discount codes to the user's current context, increasing the effectiveness of promotions. This ensures that the user receives a personalized discount that maximizes the likelihood of purchase.

Benefits for Business Owners

Increased Sales Conversion: Precise discount code assignment increases the likelihood of purchase.

Reduced Marketing Costs: More effective discount policies allow for more efficient use of the marketing budget.

Offer Personalization: Personalized discount codes enhance customer engagement and satisfaction.


Utilizing artificial intelligence in optimizing discount policies and assigning discount codes is key to gaining a competitive advantage. AI enables precise tailoring of offers to customer needs, translating into increased revenues and customer satisfaction. For business owners, implementing AI-based solutions is an investment in the future, ensuring greater operational efficiency and profitability. It ensures that their offer meets customer expectations and the competitive environment, while maintaining margin security.


Mariusz Kokoszkiewicz, CEO Omega Code

Arkadiusz Zięba

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Olga Jacek
Board member and co-founder

Olga is co-responsible for building and implementing Omega Code's strategy. In addition, she is an expert in insurance and financial intermediation.

Mariusz Kokoszkiewicz
CEO and co-founder

Mariusz, as CEO and co-founder of Omega Code, is responsible for the strategy and implementation of the development of the organisation, the teams and the technology area.

Mariola Pruchińska
Director of Implementation Teams

Manager with over 30 years of experience in the IT industry. For more than a dozen years, she has led teams involved in, among other things, the implementation of ERP, CRM and dedicated systems.

Tomasz Michałowski

IT specialist with 15 years of commercial experience in the IT industry.