Solution

Quantiphi implemented a comprehensive predictive analytics solution with three key components:

Demand Forecasting and Price Optimization: A machine learning-driven demand forecasting model was developed using time series analysis to predict future demand for specific partners. This model was integrated with a price optimization system that leverages demand forecasts, historical booking data, and business logic, enabling more informed and strategic pricing decisions.
Sentiment Analysis: Quantiphi developed a sentiment analysis tool that leverages the Gemini 1.5 Pro model to categorize customer reviews and extract valuable insights into customer sentiment and preferences, enabling better service enhancements.
Data Visualization with Looker Studio: Interactive dashboards were created using Looker Studio to visualize insights, KPIs, and metrics from the demand forecasting, price optimization, and sentiment analysis models, enabling data-driven decision-making and provide actionable insights for the business.

Results

The predictive analytics solution delivered a substantial improvement over the existing system, achieving 92% accuracy in the sentiment analysis model and approximately 70% accuracy in the demand forecasting model, with performance peaking at 82% for select partners. These enhanced accuracy levels have directly contributed to more precise decision-making, enabling better alignment with customer sentiment and more effective demand planning.
A user-friendly dashboard, incorporating 20 key performance indicators (KPIs), empowered stakeholders with actionable and interpretable insights and established a strong data foundation for future growth.