AI Inventory Management More b2b profitability Lowers cost of sales Enhances sustainability
Profiter AI optimises the inventory management delivering more profit and more sustainability from online distribution.
Profiter AI optimises the inventory management delivering more profit and more sustainability from online distribution.
Think of margins, not only revenue
Profiter first applied its concept on travel, with an AI engine for the inventory management in multi-channel online distribution. It focused on improving online distribution by delivering more profitable revenue, consistently. With predictive intelligence, it improved profitability by optimising inventory allocation amongst intermediated distributors to reduce commissions and cancellations.
AI optimisation as a service
The end of first to come, first to serve. We allocate inventory intelligently.
Per-channel suggestions to increase results.
Think of margins, not only revenue
Profiter ML software integrates with your inventory management system (aka channel manager) and delivers the best channel mix with predictive and automatic inventory allocation. It produces more profit, awareness and distribution control.
Get more gain out of the same revenue thanks to the reduction of distribution costs and cancellations
Obtain a comprehensive overview of your CPS on the distribution mix of OTAs, metasearch and direct channels.
The end of free sale model “first in, first out”.
Real-time inventory allocation reduces the big reseller’s dependency.
Including forced discounts, price cuts, ranking and dimming issues.
Instant monitoring and optimisation of the critical KPIs of your online distribution are not scalable by humans. The AI software can predict and instantly optimise channel mix in real-time.
In the current situation of COVID emergency, we find interesting to adjust the project development to assess the Hotel Market needs
How the daily routine adapts in COVID lockdown times
Online distribution has grown by almost 50% over the past 5 years
Contact our Profiter Team