• Smarking

The Impact of Dynamic Parking Rates: 17+ Months Across 10+ Markets

Updated: 5 days ago

Leading parking operators and asset owners have been leveraging dynamic pricing for over a year with great success, here are the results.


Dynamic Pricing: It’s here and now.


Leading parking operators have been using our dynamic pricing offering for over a year now. And we have over a year of results to prove that it’s here to stay and it’s where the market is going.


With several months under our belt, we can confidently say that dynamic pricing can help increase demand and revenue for operators. After deploying Automatic Yield Management (AYM) for over a year in 10+ markets, here are the results:

  • 163% average revenue increase across the US. This has ranged as high as 400% for locations with high volume. Since the machine-learning algorithm learns from transaction data, more transactions equals faster return.

  • The increase of annual net income has been up to hundreds of thousands of dollars, raising the asset value by millions.

  • Total number of transactions increased by 137%, i.e. 137% more cars parked in the same assets during last year, a huge increase of asset utilization.

  • 50% increase of occupancy during low demand times - evenings and weekends for commercial sites.


It created new demand:

  • 257% increase of multi-day (1+ days) transactions for urban locations with online sales channel and AYM. Previously, it was very rare for non-hotel sites to capture these types of transactions.

  • 210.5% increase of 4-6 hour transactions across board for urban locations. Before, most of the transactions were between 1-2 hours or a full day, now more new demand has been created and captured.


How does it work?


Smarking's AYM uses parking data to predict demand, so the more data that’s available, the faster the algorithm learns the unique demand fluctuation of the location. Factors that impact demand include: the day, time, duration, holidays, events and weather.


AYM responds to the demand by updating the rate multiple times a day, per location, and assigning the optimal price (400+ rate options).


The program is “set & forget”. Our operator partners provide high-level parameters at the beginning, and then commit to let the algorithm run and learn for at least 90 days. After that, the data usually stabilizes, showing us that it’s aligned with the market value. Resulting in not only a revenue increase for owners and operators, but higher satisfaction of the community, and a reliable amount of demand.


Parking professionals that are interested, can try it out risk free and uncover the value, quickly. No commitment or payment upfront with an easy implementation process. If you don’t like the results after 90 days, simply turn it off, no questions asked.


Demand-based pricing helps to close the gap between competition-based pricing and the true market value. Parking priced under the market value is bad for everyone involved. Especially in cities where the demand far exceeds the supply and causes major congestion.



The truth about cannibalization


One of the major hesitations operators have with online reservations apps is the perception that the online traffic is taking away, or converting, their transient visitors.


However, after a year and hundreds of thousands of transactions, the data consistently shows a neutral impact on transient demand. Most drivers have their preferred method of parking - either drive-up or pre-paid reservation.


Visitors that prefer to just drive-up continue to do so, and those who use reservation apps, consistently use the app when visiting new or repeated locations. It’s very rarely the case that drivers check both options and compare. By opening up spaces on an online sales channel, you’re simply allowing a new segment of visitors to find your garage.


How industry leaders and benefitting from dynamic pricing


LaSalle Investment Management - Peter Owusu-Opoku, Asset Manager: “One of our Chicago assets deployed Smarking AYM in March 2019, and we have observed continuously growing revenue increases since then for up to 136% (YOY), annualizing a very meaningful NOI and asset valuation uplift. Our partnership with Smarking helps us deliver competitive investment performance through economic and property market cycles, which is a driving principle here at LaSalle.”
Millenium Parking - Rick West, CEO: “Millennium is one of the largest garages in the world, serving downtown Chicago. Even if we hired a full-time person just to set fees, we couldn’t post hundreds of rates multiple times a day, let alone develop the number of products and analyze the results Smarking’s algorithm does.”
VPNE Parking Solutions - Nick Litton, COO: “As a parking operator, we are constantly looking for ways to differentiate our services to our customers in order to provide greater value. Smarking, has long provided us with that edge, and AYM takes it to a whole new level of revenue maximization.” By July 2019, AYM has increased digital revenues by 101% across 13 VPNE parking facilities, bringing in an additional $485,000/year in revenue. At a 5% cap rate, AYM’s revenue contribution represents $9.7 million in parking asset value uplift for VPNE’s clients.

For decades, the pricing of parking inventory has been largely based on competition and location. Property value is largely based on the location of the garage, and unless there are new developments in the area, it’s assumed that the property value will remain relatively consistent.


However, owners and operators across the US have increased the net operating income of their property through dynamic pricing technology. With a fixed, perishable amount of inventory, it’s difficult to control the parking rates to keep up with the daily fluctuating demand of the market.


But this has changed significantly in the last year as access to demand data has become available and can now enable a true demand-based pricing approach.


Schedule time with our team to get started for free and learn more about automating parking rates to drive demand and increase revenue.


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