It’s a simple fact, every business in the world can benefit from collecting and analyzing customer data. Nowhere can the effects of data utilization play a bigger role or have a more positive impact than in the parking industry. Time in, time out, rates, length of stay, events, weather conditions, etc. all play a role in the daily parking operations and consequently, in highlighting facility usage and parking patterns.
Although gathering data can be a bit of a challenge, the real work starts once you’ve collected it. Knowing that 86 vehicles passed through your gates between 8am-9am is great, but how can you monetize this kind of data? That’s where data analytics comes in to play; helping to turn raw data into money and improving the decision-making process. Here are my thoughts on the new trend of data analytics in the parking industry and how to ensure that your operator turns raw data into raw success.
“Data is the new oil”
The big buzz for companies nowadays is that “data is the new oil”. Sadly, there hasn’t been a “geyser” of information flowing from parking operators or the parking industry just yet. Almost every parking operator in the world touts to have some form of “Data Analytics” or “Business Intelligence” solution for their clients but the truth is most operators possess very primitive means of data collection and have dedicated very little capital to grow this new technological resource. Most operators have chosen to defer the future growth of data analytics to third-party providers like Smarking. Alternatively, parking equipment suppliers have finally started to put forth a much more sustained effort in cultivating data analytics as a product/service. Given that their equipment is usually collecting parker data anyways, why not integrate a data platform and analytics tools for clients as well? Makes sense, right?
But what can or should parking operators do with the data they do get? How can they use this information to improve parking revenues and operations for their clients?
Here are my top five (5) recommendations when considering a Data Analytics or Business Intelligence solution with your parking operator:
Operators must certify that the collection of raw data (e.g. for one month) from parking equipment can be verified against reported revenues to ensure there are no discrepancies or gaps in the base data (e.g. missing transactions, payments, gate events, etc.) before being used in any Business Intelligence platform or applications(s).
Operators need to clearly demonstrate the proven capabilities or resources of their proposed Business Intelligence solution(s). Showing a PowerPoint presentation with varying computer screenshots isn’t good enough. You should be able to see the product work in real time in an actual facility.
Operators must ensure that parking data will be accessible in multiple formats for each parking facility and that it corresponds with site-specific operational characteristics (e.g. outdoor surface lots vs. weather patterns, duration of stay when facilities are staffed vs. unstaffed, corresponding transaction volumes, broken down by rates; per day/month/year, etc.) The more detailed data you receive the better!
Operators need to demonstrate how they plan to use parking data to provide you with useful reports. For example, if 48% of parkers that enter an airport parking facility between 6am-10am park in the garage closest to the terminal entrance/exit and are responsible for generating 70% of the total parking facility revenue, what does that mean? Why is that significant? If in this example the parking operator is able to present the data to highlight a higher percentage of traveler drop offs/pickups or short term parkers in this facility (mainly due to the close proximity to the terminal) then the client could consider (or justify) possible rate increases or variable pricing structures (based on demand and by time of day). Ask your operator how they plan to capitalize on the data they gather.
Parking operators must be able to provide real case studies on how their Business Intelligence solutions have utilized historical parking data to forecast future occupancy demands in a parking facility or low occupancies at other times. Their Business Intelligence solutions must be able to analyze data and predict (with reasonable certainty) the patterns of parkers by day, week or month etc. This would be particularly important for anyone looking to implement a strategy for variable or “dynamic” pricing.
Parking data is only useful if it is utilized correctly and to its maximum potential. Gathering data is only the first step towards a successful execution and implementation of an analytics solution so look for a proven product and service provider. Only then will you be able to turn raw data into raw success in your parking facility.
About the author:
Ross Frangos is the President and Founder of AuditPark Services Inc., a parking consulting firm based in Toronto ON. He specializes in Requests for Proposal, parking documents and assisting his clients in the procurement of parking management services.