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, a pricing simulator, parking revenue optimization is made easier: based on the real-time re-processing of hundreds of thousands of past tickets and including many key business factors (eg. price elasticity), 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 including 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 are equivalent to that 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 daily transfered when K-Yield is not put in place, otherwise a real-time connection with the system is required
  • 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 in 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
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