Car park revenue optimization
K-Pricing
Parking revenue optimization
From business Intelligence to dynamic pricing
One of the key levers to achieve car park revenue optimization is to optimize the so-called parking “price grid” (or “tariff tables”). Usually, due to a lack of tools, parking rates are set for a year or even more and rarely adapted to demand various levels.
Thanks to K-Pricing, our pricing simulation tool, parking revenue optimization is made easier. It is based on the real-time re-processing of hundreds of thousands of past tickets and includes many key business factors (eg. price elasticity), making the fine tuning of roll-up rates is an easy game. At stake are substantial additional revenues.
K-Pricing
K-Pricing is a pricing simulator software dedicated to the car park sector. This car park revenue optimization tool includes multi price grids management, seasonality management, tariff grid structure evolutions, price elasticity hypothesis, etc.
Benefits
Thanks to K-Pricing, one can see in a few seconds the potential revenue impact of any pricing policy change.
Based upon the real time re-processing of past tickets that are automatically made available, it gives you all the elements on the relevancy of pricing policy changes.
This solution is a complement to K-Yield as it primarily addresses the optimization of the drive-up pricing policies.
Benefits
Thanks to K-Pricing, one can see in a few seconds the potential revenue impact of any pricing policy change.
Based upon the real time re-processing of past tickets that are automatically made available, it gives you all the elements on the relevancy of pricing policy changes.
This solution is a complement to K-Yield as it primarily addresses the optimization of the drive-up pricing policies.
Needed data
The sources of data need for the implementation of the K-pricing car park revenue management tool are equivalent to those of K-Analytics.
Data from the equipment system (the “gate system”) as well as from the parking e-commerce platform (if it exists):
- Data are transfered daily, or are connected in real-time when K-Yield is put in place;
- In all cases, the content is limited to, per individual transaction: date and time of entry, payment amount, date and time of exit, customer type, etc;
- APIs with the most important equipment system providers are available.
One can easily retrieve a set of past data, ticket transactions as well as applicable price tables, and base its simulations on it.
Features
The real time simulation of pricing policy changes makes it a powerful decision-making tool for car park managers.
The following questions are most easily addressed:
- Should we change the prices after 1 hour of stay? Or 45 minutes? Between 4 and 8 hours of stay in the parking?
- Should we introduce seasonal rates? A weekend package?
- What are the threshold effects of any change in the pricing structure?
- How many vehicles are affected? Which customer segments will be proposed different tariffs than before?
- What are the consequences on revenue?
- What are the most likely hypothesis regarding client behavior?
- Will the demand volume decrease if the price is raised by x%? In what proportions and with what effect on the revenues? What is the best trade-off between price and volume?
K-Pricing is for parking managers who do not want to spend hours getting data sets and complicated excel sheets to simulate pricing changes.
Implementation
The implementation of K-Pricing is very similar to that of K-Analytics. It takes only a few days depending on data availability (from the gate system):
- The first phase consists in the integration of 2 or 3 years of past data
- In parallel, the daily API is put in place together with the third party team (gate system provider for ex.)
- Controls and tests are performed (vs turnover and volume of transactions) to ensure 99.9% accuracy in the data processing aspects (lost tickets, manual counting processes, etc.)
- Past pricing policies are entered in the system
- Knowledge transfer is ensured by Kowee teams