Our goal: To help hotel companies and travel retailers optimize the travel experience

DataPrime leverages proven AI and Machine Learning to enhance consumer value, enrich the customer experience, and drive profitable growth for travel providers.  Our predictive ACMs (Analytical Components and Methods) provide immediate impact, while learning how to improve how hotels and travel retailers present the customer with a bundle of products and services tailored to their known preferences and the context of their trip, at the right time in the customer journey, and at a price that balances profitability with probability of purchase.

Who We Serve

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Hospitality CMO & CCO

  • Enhance customer experience and drive loyalty and repeat purchase
  • Maximize profitability with technology and analytics that enable incrementally-better commercial decisions
  • Identify and track ROI on marketing efforts to ensure marketing dollars are having desired reach and impact
  • Increase automation of pricing, inventory controls and marketing
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Hotel Revenue Manager

  • Effectively manage demand using pricing and inventory controls to maximize occupancy and profitability
  • Optimize pricing based on forecasted demand, customer price sensitivity, and competitive price position to drive customer purchase through incrementally-better revenue decisions
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Hotel Brand Manager

  • Identify customer segments with specific purchase behavior, market products, and services they desire
  • Ensure packaging and promotion efforts drive incremental demand and profitability
  • Leverage customer preference data to drive engagement, purchase, and follow-on business

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Demand Forecasting

DataPrime forecasting solutions provide improved visibility into expected demand, utilizing a suite of forecasting algorithms to accurately predict future demand and inform your commercial decision-making. Our predictive ACMs isolate the factors that drive behavior through data-driven customer segmentation and accurately predict final demand across each segment.

Forecasting is never easy, but our modular approach allows us to have models up and running and providing improved visibility (and up to 50% reduction in forecast error) in weeks, not months. 

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Transient Price Optimization

DataPrime's Price Optimization ACM brings together machine-learning enabled demand forecasting, price sensitivity measurement at the customer/segment level, and market rate intelligence to determine optimal pricing based on the current realities and forecasted state of the market, accounting for incremental costs and cross-elasticity between room products.

Implementation of this approach and implementation in the travel and transportation industry have driven revenue improvements of 3-4% and more than $100M annually in individual customer benefit.

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Context-Based Dynamic Offers

Within the travel and hospitality industry, hotel brands, owners, and travel retailers are looking for capabilities that optimize across the customer experience. Increasingly, they are focused on the benefits of a holistic approach across three areas:

  1. Offer Generation

  2. Ancillary Bundling

  3. Dynamic Pricing


Our Context-Based Dynamic Offers capability uses AI and Machine-Learning enabled analytics to present the traveler with a bundle of products and services, tailored to their known preferences and the context of their trip, at the right time in the customer journey, and at a price that balances profitability with probability of purchase.


Case Study:

Leading Industry Company

 

The Challenge

The Challenge

Hospitality company with 8 brands across the chain scale struggles to leverage legacy RM systems in the current market  

    • Legacy systems built around dated business assumptions and data, and don’t reflect current hospitality
    • Forecasting models are borrowed from old airline systems, incapable of adjusting to market changes
    • No science behind pricing, all automation is based on dated inventory control models

 

 

The Solution

The Solution

A new approach to hospitality transient pricing that explicitly measures sensitivity and incorporates competitive data.  

    • Demand forecasting based on the latest data-driven behavioral segmentation and machine learning
    • Explicitly measured price sensitivity at the segment level, accounting for price position vs. the competition
    • Real-time competitive pricing data to determine demand impacts of increases and decreases in price relative to defined comp set
The Outcome

The Outcome

Industry-first hospitality price optimization capability driving a measured uplift of 2.7% improvement in RevPAR

    • Pricing capability rolled out to more than 4,000 hotels worldwide
    • Seamlessly linking with the inventory management system, intuitive dashboards and reports drive adoption and rate acceptance >78%
    • Revenue generated in the first year of deployment equals more than $118M

 

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