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Pace uses machine learning to optimally match supply and demand through price.

Pace uses machine learning to optimally match supply and demand through price.

95% of properties in the global hospitality industry take their pricing decisions manually, leaving 10-20% of their revenues to a combination of experience and chance. Pace solves this by giving the industry access to a revenue management solution that emphasises science, real-time and automation.

SCIENTIFIC
As revenue managers we trade in probabilities. Pace uses a scientific approach to evaluate the probabilities of different outcomes and proposes optimal actions. This gives you confidence you're always on the right track.

REAL-TIME
Traditionally revenue management has relied on historical data. Through proprietary technologies Pace is capable of adjusting it’s forecasts and models of the future based on bookings as they happen.

AUTOMATED
Even a mid-size hotel would need to, every year, change millions of prices accurately and quickly. Revenue strategy will always require human guidance but the only way to keep up with pricing frequency is automation.

Jason Pinto

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Jens Munch

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Founder @Pace • Previous Chief Strategy Officer at @iZettle & Strategic Partnerships @Google
Total raised

$3.3M

Funded over

1 round

Latest round

Seed (Dec 2017)

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