Case study

Simplifying Sales Cycles: SG Analytics' Comprehensive Solution to Streamline Deal Structuring and Automated Sales Contract Creation for Thomson Reuters

Gen AI Case Study_SG Analytics' Comprehensive Solution to Streamline Deal Structuring

BUSINESS SITUATION

In a highly competitive market, the client faced significant challenges in optimizing discount strategies and managing sales contracts efficiently. The existing manual processes were time-consuming and prone to errors, leading to suboptimal pricing decisions and frequent delays in contract finalization.

SGA STRATEGIC APPROACH
 

SGA developed a comprehensive solution utilizing traditional machine learning for discount prediction and LLMs for contract creation. The approach aimed to optimize pricing strategies and streamline the sales contract creation process. 

Data Integration and Analysis: 

  • Diverse Datasets: SGA integrated diverse datasets, including financials, customer interactions, product engagement, and market trends, to provide a holistic view of the factors influencing discount strategies and contract terms. 
  • Data Cleaning and Preprocessing: The data was cleaned and preprocessed to ensure accuracy and reliability, enabling more precise analysis and predictions. 

Predictive Analysis with Traditional Machine Learning: 

  • Historical Sales Data: Machine learning models analyzed historical sales data to identify patterns and trends that influence discount strategies. 
  • Optimal Discounting Strategies: Predictive analysis was employed to forecast optimal discount rates, ensuring data-driven pricing decisions that maximize profitability and competitiveness. 

Large Language Models for Contract Creation: 

  • Contextual Understanding: LLMs were used to generate and manage sales contracts by understanding the context and legal language. This ensured accuracy and compliance with legal standards. 
  • Human-like Explanations: The LLMs provided human-like explanations and justifications for each recommendation and clause, enhancing transparency and trustworthiness. 
  • Dynamic Adaptation: The system dynamically adjusted recommendations based on real-time market and behavioral changes, maintaining relevance and effectiveness. 

User-friendly Interface: 

  • Intuitive Interaction: The solution featured a user-friendly interface that allowed users to easily interact with the AI system, ensuring smooth and efficient operation. 
  • Customization Options: Users could customize contract templates and discount parameters, tailoring the system to meet specific business needs and preferences. 


ENGAGEMENT

The engagement process included: 

  • Integrating diverse datasets, including financials, customer interactions, and market trends, for data-driven decision-making. 
  • Utilizing LLMs to generate and manage sales contracts, ensuring accuracy and compliance. 
  • Implementing AI-driven predictive analysis to forecast optimal discounting strategies. 

BENEFITS & OUTCOME

  • Enhanced Decision Making: Empowers businesses with AI-driven insights for optimal discounting.

  • Increased Revenue: Optimizes pricing strategies for better profitability, enhancing revenue impact by 5% through optimized discounting.

  • Customer Satisfaction: Aligns pricing with customer expectations and market demands, a 10% uplift.

  • Operational Efficiency: Reduces the time and complexity involved in pricing decisions.


KEY TAKEAWAYS

  • AI-driven predictive analysis and LLMs significantly enhance discount strategies and contract management. 
  • Automation in contract creation improves accuracy, compliance, and operational efficiency. 
  • Integrating diverse datasets ensure more accurate and informed decision-making. 

We bring comprehensive data driven insights to everyone, everywhere

In depth-analysis with simple solutions