Effective data management is a persistent challenge for businesses across industries. For our client, a leading petroleum and petrochemical company in Thailand, the issue was particularly pronounced due to the immense volume of data generated daily. In some instances, for example in our case with the sales team, data collection was relying on manual processes that limited efficiency and scalability.
Manual data entry was both labor-intensive and time-consuming, often leading to errors that resulted in inaccurate quotations. These inefficiencies not only increased operational costs but also posed risks to the client’s ability to manage the growing volume of data effectively. To address these challenges, the client needed a more streamlined and reliable approach to data handling.
We developed and deployed a comprehensive, AI-powered pricing and quotation engine that addressed the client’s key challenges and delivered significant business benefits:
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Higher Close Rate, Increased Customer Satisfaction Our quotation engine helped our client achieve higher closing rates and boost customer satisfaction |
Increased Workflow Efficiency We replaced manual operations with process automation to enhance workflow efficiency |
Eliminated Human Errors We removed human-made errors from quotations with system integration |
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AI-Powered Real-Time Quotation Engine: Leveraging live data sources and machine learning, the engine dynamically adjusted pricing recommendations tailored to each client and product. This allowed the client to optimize pricing strategies, improve bid success rates, and position themselves more competitively in the market. By enabling better data-driven decision-making, the solution also laid the foundation for improving profitability through smarter, more informed pricing adjustments.
Digital Transformation of the Quotation Process: We transformed the client’s entire quotation process, bringing it online and to the cloud. This digitization introduced multiple benefits:
Enhanced Data Integration: By implementing Azure Data Factory, we automated schema validation and cross-source integrity checks, ensuring high data quality. This robust and scalable data foundation not only supports the client’s current needs but also positions them to expand their analytics capabilities for future initiatives, such as predictive performance and market analysis.
Predictive Analytics for Pricing Optimization: We trained custom machine learning models to provide pricing recommendations that balance competitiveness and profitability. These models analyze historical and real-time data to apply discounts where they add the most value, while continuously learning to refine recommendations over time. This approach has empowered the client to strike an optimal balance between increasing win rates and maximizing profits.
The successful implementation of this advanced ML-based pricing platform marked a significant milestone in client’s digital transformation journey. By addressing inefficiencies and enabling data-driven decision-making, we empowered the client to achieve greater operational efficiency, improve profitability, and set the stage for continued innovation in their pricing strategies.
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