Unfold the Future
Unfold the Future
Unfold the Future
Put in place Your Car Park Dynamic Pricing Effortlessly
Put in place Your Car Park Dynamic Pricing Effortlessly
Boost your parking revenue by at least 10% with Kowee's innovative dynamic pricing solutions, powered by advanced demand forecasting and optimal length-of-stay modules.
Boost your parking revenue by at least 10% with Kowee's innovative dynamic pricing solutions, powered by advanced demand forecasting and optimal length-of-stay modules.
Discover the Kowee parking revenue optimization solutions
Kowee delivers smart, dynamic pricing solutions tailored for parking— from powerful business insights to optimized yield management, we make every space count.
Data Accuracy
Leverage analytics to make informed decisions with accurate data and enhance operational efficiency
Revenue optimization
Maximize your parking potential revenues with our cutting-edge dynamic pricing tools
Optimize Your Airport Parking Revenue Today
At Kowee, we provide innovative solutions tailored for airports to maximize their car parking pricing strategies. Our expertise ensures that you achieve optimal revenue while enhancing customer satisfaction.
Easy integration in your processes
Discover how easy it is to get the key benefits of using K-Analytics.
Integrate historic
Feed the data of your 3 last years into our system.
Ensure data accuracy
Controls and tests are performed to ensure 99,9% accuracy (orphan tickets, manual counting processes, etc.)
Setup your API real time connections
The Kowee solutions use the CPMS and the booking system data thanks to a real time connection.
The Kowee solutions use the CPMS and the booking system data thanks to a real time connection.
The Kowee solutions use the CPMS and the booking system data thanks to a real time connection.
Enjoy the easiness of Kowee solutions
Daily use the 80/90 dashboards available in K - Analytics
Regularly update your gate prices thanks to K-Pricing simulations
Thanks to K-Yield, constantly fine tune and control the yield strategies of your parking facilities
Let the numbers do the talking
3M+
Prices generated per day
450M
Imported tickets
30+
Airports using Kowee
Let the numbers do the talking
3M+
Prices generated per day
450M
Imported tickets
30+
Airports using Kowee
Let the numbers do the talking
3M+
Prices generated per day
450M
Imported tickets
30+
Airports using Kowee
Let the numbers do the talking
3M+
Prices generated per day
450M
Imported tickets
30+
Airports using Kowee
Kowee’s innovative solutions increase parking revenues by up to 20-25%. Our clients consistently report enhanced customer satisfaction and operational efficiency.
20-25%
Boosted revenue through optimized pricing strategies.
Pricing Agility
Pricing Agility
Booking services are more and more appreciated thanks to pricing agility leading to attractive on-line prices
Pricing agility made simple
Gone are the days when parking operators changed their pricing policy once a year.
What Our Clients Say About Us
What Our Clients Say About Us
Discover what our clients are saying about us—genuine testimonials that highlight our impact, service excellence, and the success we've helped them achieve.
Discover what our clients are saying about us—genuine testimonials that highlight our impact, service excellence, and the success we've helped them achieve.
"With Kowee’s tools and assistance, the airport now dynamically adapts the on-line rates of its various parkings. Doing so, it better meets both passenger expectations and park occupancy constraints."
Philippe RODIER
Head of Marketing and Digital Services
"With Kowee’s tools and assistance, the airport now dynamically adapts the on-line rates of its various parkings. Doing so, it better meets both passenger expectations and park occupancy constraints."
Philippe RODIER
Head of Marketing and Digital Services
"With Kowee’s tools and assistance, the airport now dynamically adapts the on-line rates of its various parkings. Doing so, it better meets both passenger expectations and park occupancy constraints."
Philippe RODIER
Head of Marketing and Digital Services
"With Kowee’s tools and assistance, the airport now dynamically adapts the on-line rates of its various parkings. Doing so, it better meets both passenger expectations and park occupancy constraints."
Philippe RODIER
Head of Marketing and Digital Services
"We particularly enjoy Kowee’s user-friendly solutions, which were implemented smoothly at Marseille Provence Airport only a few weeks ago. We can already see first benefits, both in terms of occupancy optimization and revenue growth."
Julien BOULLAY
Sales and Marketing Director
"We particularly enjoy Kowee’s user-friendly solutions, which were implemented smoothly at Marseille Provence Airport only a few weeks ago. We can already see first benefits, both in terms of occupancy optimization and revenue growth."
Julien BOULLAY
Sales and Marketing Director
"We particularly enjoy Kowee’s user-friendly solutions, which were implemented smoothly at Marseille Provence Airport only a few weeks ago. We can already see first benefits, both in terms of occupancy optimization and revenue growth."
Julien BOULLAY
Sales and Marketing Director
"We particularly enjoy Kowee’s user-friendly solutions, which were implemented smoothly at Marseille Provence Airport only a few weeks ago. We can already see first benefits, both in terms of occupancy optimization and revenue growth."
Julien BOULLAY
Sales and Marketing Director
"Thanks to K-Yield we were able to be price-agile towards new competitors around the Nantes Atlantique airport, diminishing our average discount rate from -30% to -12% for pre-bookings. We estimate the net gain to be around 800k € for the first year."
Isabelle DIX-NEUF
Parking and Mobility
"Thanks to K-Yield we were able to be price-agile towards new competitors around the Nantes Atlantique airport, diminishing our average discount rate from -30% to -12% for pre-bookings. We estimate the net gain to be around 800k € for the first year."
Isabelle DIX-NEUF
Parking and Mobility
"Thanks to K-Yield we were able to be price-agile towards new competitors around the Nantes Atlantique airport, diminishing our average discount rate from -30% to -12% for pre-bookings. We estimate the net gain to be around 800k € for the first year."
Isabelle DIX-NEUF
Parking and Mobility
"Thanks to K-Yield we were able to be price-agile towards new competitors around the Nantes Atlantique airport, diminishing our average discount rate from -30% to -12% for pre-bookings. We estimate the net gain to be around 800k € for the first year."
Isabelle DIX-NEUF
Parking and Mobility
"After the implementation of K-Yield, our expectations have been exceeded. It is worth to remark the outstanding competence in Pricing & RM we have found in the whole Kowee team who completed our complex implementation timely."
Antonio FRACCARI
CEO ADR Mobility
"After the implementation of K-Yield, our expectations have been exceeded. It is worth to remark the outstanding competence in Pricing & RM we have found in the whole Kowee team who completed our complex implementation timely."
Antonio FRACCARI
CEO ADR Mobility
"After the implementation of K-Yield, our expectations have been exceeded. It is worth to remark the outstanding competence in Pricing & RM we have found in the whole Kowee team who completed our complex implementation timely."
Antonio FRACCARI
CEO ADR Mobility
"After the implementation of K-Yield, our expectations have been exceeded. It is worth to remark the outstanding competence in Pricing & RM we have found in the whole Kowee team who completed our complex implementation timely."
Antonio FRACCARI
CEO ADR Mobility
We Are Always Ready To Answer Any Of Your Query
We’re always ready to answer any query you have, providing prompt and helpful support whenever you need it.
What manual intervention is required for the proper setting of the forecasts?
At the launch of the project, we usually work on 1-2 years of data to properly perform the parameter settings of K-Yield like the calendar mapping (define equivalent weeks between past and future periods of time) or the definition of the yield classes. Later, apart from regular updates (every 1 or 2 years) of these structural parameters, the manual interventions related to the forecasts are limited to the “special event” management
How are the demand forecasts done? What data is used to inform them and what algorithmic approach is used to drive the demand forecasts?
The variable that we forecast is a volume of entries per date and time of entry for a given yield class (a Yield class is a cluster of the demand, usually defined as a band of length of stay). We use three forecasting modules that are imbricated with each other: - The first one is addressing the long-term trend (capturing the seasonality aspects, differentiating week types, etc.) - The second one is focusing on the short-term trend, considering the very latest weeks of observation - The last one is based on the actual car park situation (the current number of cars that are present or that have just exited): this is the real-time “touch” that we think necessary to make sure pre-bookings that would be requested with a very small lead time would be properly answered
What action does the optimization engine drive in response to the updated forecasts?
The optimization engine performs different calculations aiming at answering the 2 following questions: - Whether a given booking request is likely to be competition with alternative bookings during its stay (considering its length of stay, but also the other forecasted demand, the already confirmed bookings, etc.) - Whether, when competing for capacity, the request in question is better contributing to the overall economy than other demands (i.e is it optimal?) These two types of calculation cannot be done by a human resource (only an engine can embrace the complexity of the number of possible combinations between the various lengths of stay potentially entering the parking at so many different entry times but competing for the same inventory).
How long does the implementation of Kowee solutions take?
The implementation of K-Yield, Kowee’s dynamic pricing solution for parking, takes approximately 2-3 months. Two parallel projects are conducted: one relates to the building of the APIs between Kowee and the 3rd party systems (the CPMS and booking systems) and the other one consists in defining the yield strategies together with the customer’s team and in general, in doing the parameter setting of K-Yield.
How do Kowee solutions differentiate from other providers solutions?
Kowee’s dynamic pricing solution is different from other market solutions as it is natively designed as a parking revenue optimization solution: - It does not optimize occupancy but rather revenues (occupancy rates are a consequence of revenue optimization, not a driver of it) - It is real-time connected to the parking system so as to ensure a true dynamic pricing response to upcoming booking requests (considering forecasts but also the latest parking status) - Is differentiates the prices upon the entry times (not only entry dates, car park and length of stay)
What manual intervention is required for the proper setting of the forecasts?
At the launch of the project, we usually work on 1-2 years of data to properly perform the parameter settings of K-Yield like the calendar mapping (define equivalent weeks between past and future periods of time) or the definition of the yield classes. Later, apart from regular updates (every 1 or 2 years) of these structural parameters, the manual interventions related to the forecasts are limited to the “special event” management
How are the demand forecasts done? What data is used to inform them and what algorithmic approach is used to drive the demand forecasts?
The variable that we forecast is a volume of entries per date and time of entry for a given yield class (a Yield class is a cluster of the demand, usually defined as a band of length of stay). We use three forecasting modules that are imbricated with each other: - The first one is addressing the long-term trend (capturing the seasonality aspects, differentiating week types, etc.) - The second one is focusing on the short-term trend, considering the very latest weeks of observation - The last one is based on the actual car park situation (the current number of cars that are present or that have just exited): this is the real-time “touch” that we think necessary to make sure pre-bookings that would be requested with a very small lead time would be properly answered
What action does the optimization engine drive in response to the updated forecasts?
The optimization engine performs different calculations aiming at answering the 2 following questions: - Whether a given booking request is likely to be competition with alternative bookings during its stay (considering its length of stay, but also the other forecasted demand, the already confirmed bookings, etc.) - Whether, when competing for capacity, the request in question is better contributing to the overall economy than other demands (i.e is it optimal?) These two types of calculation cannot be done by a human resource (only an engine can embrace the complexity of the number of possible combinations between the various lengths of stay potentially entering the parking at so many different entry times but competing for the same inventory).
How long does the implementation of Kowee solutions take?
The implementation of K-Yield, Kowee’s dynamic pricing solution for parking, takes approximately 2-3 months. Two parallel projects are conducted: one relates to the building of the APIs between Kowee and the 3rd party systems (the CPMS and booking systems) and the other one consists in defining the yield strategies together with the customer’s team and in general, in doing the parameter setting of K-Yield.
How do Kowee solutions differentiate from other providers solutions?
Kowee’s dynamic pricing solution is different from other market solutions as it is natively designed as a parking revenue optimization solution: - It does not optimize occupancy but rather revenues (occupancy rates are a consequence of revenue optimization, not a driver of it) - It is real-time connected to the parking system so as to ensure a true dynamic pricing response to upcoming booking requests (considering forecasts but also the latest parking status) - Is differentiates the prices upon the entry times (not only entry dates, car park and length of stay)
What manual intervention is required for the proper setting of the forecasts?
At the launch of the project, we usually work on 1-2 years of data to properly perform the parameter settings of K-Yield like the calendar mapping (define equivalent weeks between past and future periods of time) or the definition of the yield classes. Later, apart from regular updates (every 1 or 2 years) of these structural parameters, the manual interventions related to the forecasts are limited to the “special event” management
How are the demand forecasts done? What data is used to inform them and what algorithmic approach is used to drive the demand forecasts?
The variable that we forecast is a volume of entries per date and time of entry for a given yield class (a Yield class is a cluster of the demand, usually defined as a band of length of stay). We use three forecasting modules that are imbricated with each other: - The first one is addressing the long-term trend (capturing the seasonality aspects, differentiating week types, etc.) - The second one is focusing on the short-term trend, considering the very latest weeks of observation - The last one is based on the actual car park situation (the current number of cars that are present or that have just exited): this is the real-time “touch” that we think necessary to make sure pre-bookings that would be requested with a very small lead time would be properly answered
What action does the optimization engine drive in response to the updated forecasts?
The optimization engine performs different calculations aiming at answering the 2 following questions: - Whether a given booking request is likely to be competition with alternative bookings during its stay (considering its length of stay, but also the other forecasted demand, the already confirmed bookings, etc.) - Whether, when competing for capacity, the request in question is better contributing to the overall economy than other demands (i.e is it optimal?) These two types of calculation cannot be done by a human resource (only an engine can embrace the complexity of the number of possible combinations between the various lengths of stay potentially entering the parking at so many different entry times but competing for the same inventory).
How long does the implementation of Kowee solutions take?
The implementation of K-Yield, Kowee’s dynamic pricing solution for parking, takes approximately 2-3 months. Two parallel projects are conducted: one relates to the building of the APIs between Kowee and the 3rd party systems (the CPMS and booking systems) and the other one consists in defining the yield strategies together with the customer’s team and in general, in doing the parameter setting of K-Yield.
How do Kowee solutions differentiate from other providers solutions?
Kowee’s dynamic pricing solution is different from other market solutions as it is natively designed as a parking revenue optimization solution: - It does not optimize occupancy but rather revenues (occupancy rates are a consequence of revenue optimization, not a driver of it) - It is real-time connected to the parking system so as to ensure a true dynamic pricing response to upcoming booking requests (considering forecasts but also the latest parking status) - Is differentiates the prices upon the entry times (not only entry dates, car park and length of stay)
What manual intervention is required for the proper setting of the forecasts?
At the launch of the project, we usually work on 1-2 years of data to properly perform the parameter settings of K-Yield like the calendar mapping (define equivalent weeks between past and future periods of time) or the definition of the yield classes. Later, apart from regular updates (every 1 or 2 years) of these structural parameters, the manual interventions related to the forecasts are limited to the “special event” management
How are the demand forecasts done? What data is used to inform them and what algorithmic approach is used to drive the demand forecasts?
The variable that we forecast is a volume of entries per date and time of entry for a given yield class (a Yield class is a cluster of the demand, usually defined as a band of length of stay). We use three forecasting modules that are imbricated with each other: - The first one is addressing the long-term trend (capturing the seasonality aspects, differentiating week types, etc.) - The second one is focusing on the short-term trend, considering the very latest weeks of observation - The last one is based on the actual car park situation (the current number of cars that are present or that have just exited): this is the real-time “touch” that we think necessary to make sure pre-bookings that would be requested with a very small lead time would be properly answered
What action does the optimization engine drive in response to the updated forecasts?
The optimization engine performs different calculations aiming at answering the 2 following questions: - Whether a given booking request is likely to be competition with alternative bookings during its stay (considering its length of stay, but also the other forecasted demand, the already confirmed bookings, etc.) - Whether, when competing for capacity, the request in question is better contributing to the overall economy than other demands (i.e is it optimal?) These two types of calculation cannot be done by a human resource (only an engine can embrace the complexity of the number of possible combinations between the various lengths of stay potentially entering the parking at so many different entry times but competing for the same inventory).
How long does the implementation of Kowee solutions take?
The implementation of K-Yield, Kowee’s dynamic pricing solution for parking, takes approximately 2-3 months. Two parallel projects are conducted: one relates to the building of the APIs between Kowee and the 3rd party systems (the CPMS and booking systems) and the other one consists in defining the yield strategies together with the customer’s team and in general, in doing the parameter setting of K-Yield.
How do Kowee solutions differentiate from other providers solutions?
Kowee’s dynamic pricing solution is different from other market solutions as it is natively designed as a parking revenue optimization solution: - It does not optimize occupancy but rather revenues (occupancy rates are a consequence of revenue optimization, not a driver of it) - It is real-time connected to the parking system so as to ensure a true dynamic pricing response to upcoming booking requests (considering forecasts but also the latest parking status) - Is differentiates the prices upon the entry times (not only entry dates, car park and length of stay)
Increase Your Car Park Revenue
Take a test drive and see how Kowee’s software solutions will elevate your airport parking revenue. Don’t just park, optimize! Your bottom line will thank you.
Increase Your Car Park Revenue
Take a test drive and see how Kowee’s software solutions will elevate your airport parking revenue. Don’t just park, optimize! Your bottom line will thank you.
Increase Your Car Park Revenue
Take a test drive and see how Kowee’s software solutions will elevate your airport parking revenue. Don’t just park, optimize! Your bottom line will thank you.
Increase Your Car Park Revenue
Take a test drive and see how Kowee’s software solutions will elevate your airport parking revenue. Don’t just park, optimize! Your bottom line will thank you.