Parking Benchmarking (Free): Understanding the Metrics

Modified on Fri, 22 Sep, 2023 at 3:40 PM

This article will help you understand the details displayed on the Parking Benchmarking (Free) dashboard. Read this knowledge base article to learn how the premium version differs.

The following information applies to all metrics:

The week begins at 12:00am on Monday
Only Passport-initiated sessions will be reflected (i.e., no sessions from ParkMobile, meters, or other third-party vendors)
- However, the results will include sessions from facilitators that use Passport APIs to create parking sessions in our system (e.g., Google, http://Way.com , SP+, etc.)
Gross Revenue = (parking fee + convenience fee + tax)
Session Duration = (end time - start time)

TABLE OF CONTENTS

Filters Overview
Summary Tiles
Individual Metrics

Filters Overview

Operator Name. Select your operator.
Interval. Select the interval unit for displaying the date range.
- Note: The free report provides only a month interval.
Operators to Compare. Select one or more operators whose data you want to compare.
- Note: This drop-down menu displays only those operators who have opted in to data sharing and have the Parking product.

Summary Tiles

Note: In the Parking Benchmarking (Premium) report, when additional operators are filtered onto the dashboard, this tile would display a delta that would compare your operator’s data against the aggregated average of the operator(s)' data you selected to compare.

Unique Active Users by Date Range

Overview

This tile displays the total number of unique active users by date range in my environment.

Calculation

(a)

a = Active users in your environment who have parked at least once during the selected date range

Note: A person who has parked at least once and is counted only once in the selected date range.

Example

You are Operator A and there have been 20 sessions that occurred during the specified date range. Each session was created by a different user, so you had 20 Unique Active Users.

Note: If the same user had parked 20 times, you would have had only 1 Unique Active User.

Average Paid Session Duration

Overview

This tile displays the length of a typical parking session for the specified date range in my environment.

Calculation

(a / b)

a = Total session duration for all paid parking sessions
b = Total number of all paid parking sessions

Average Gross Revenue per Session

Overview

This tile displays the amount of money generated by a typical parking session for the specified date range in my environment.

Calculation

(a / b)

a = Total of parking fee + convenience fee + tax for each session
b = Total number of sessions

Note: The result will display as dollars and cents (rounded to the nearest cent).

Individual Metrics

When the dashboard displays only my operator’s data, the tile will display the specific metric for my operator. When additional operators are added to the dashboard, their data will be displayed with mine.

Unique Active Users by Interval

Overview

This metric displays the total number of Unique Active Users in my environment where the parker has parked at least once during the selected date range.

Unlike the summary tile, which counts a parker only once per date range, this metric will count the parker once per time interval.

Calculation

(a)

a = all unique users within each time interval for the given date range

Example

If John Doe parked five times each month during the period 1/1/23 - 3/31/23, he would be counted three times: once in January, once in February, and once in March.

Data Source(s)

session information
parker ID

Factors That Affect This Metric

time of year
is the location seasonal (e.g., tourist town, university, etc.)
number of parking locations (e.g., downtown only or dispersed among multiple areas)
number of paid spaces
interval duration

Metric Significance

This metric distinguishes the unique active users from the total number of sessions. This metric enables you to quantify growth rate, market penetration, user retention. In addition, the metric could indicate non-local users.

Average Sessions per Unique User by Interval

Overview

This metric displays the average number of parking sessions per unique parker within the selected time interval.

Calculation

(a / b)

a = total number of sessions created by a unique user
b = number of unique users

Example

Lot XYZ had 19 sessions between 1/1/23 and 3/31/23.

User A created 4 sessions each in January, February, and March (4 sessions x 3 months)
User B created 2 sessions in each month (2 sessions x 3 months)
User C created only 1 session in March (1 session x 1 month)
Monthly Metrics
- January: 3
  - (6 sessions) / (2 unique users for January)
- February: 3
  - (6 sessions) / (2 unique users for February)
- March: 2.33
  - (7 sessions) / (3 unique users for March)

Data Source(s)

session information
parker ID

Factors That Affect This Metric

time of year
is the location seasonal (e.g., tourist town, university, etc.)
number of parking locations (e.g., downtown only or dispersed among multiple areas)
number of paid spaces
interval duration
rules and regulations (e.g., are users allowed to create multiple sessions in a day, are users allowed to move the vehicle to a new location at no additional charge)

Metric Significance

This metric reveals user retention and could indicate whether non-local parkers are consistently returning to your environment. This metric indicates whether parkers use the app only a few times or if they are consistent parkers with frequent app usage. Higher average session metrics indicate that users are finding value in your service.

Percentage of Unique Users with Two Sessions or Fewer by Interval

Overview

This metric displays the proportion of users who parked two or fewer times during the specified interval for the selected date range.

Calculation

(a / b)

a = number of unique users with fewer than 2 sessions
b = total # of sessions

Example

10 parkers created 30 sessions (in total) for the specified date range

8 of these 10 parkers created exactly 3 sessions each
1 user created 2 sessions
1 user created 1 session

Count how many unique parkers exist for each interval and how many of those parkers had two or fewer sessions. Then, divide the number of parkers with two or fewer sessions by the total number of unique parkers (for each interval) and multiply by 100. Finally, round the number and express as a percentage. The result for the example above is 20% = 2 / 10 x 100.

Data Source(s)

session information
parker ID

Factors That Affect This Metric

time of year
is the location seasonal (e.g., tourist town, university, etc.)
number of parking locations (e.g., downtown only or dispersed among multiple areas)
number of paid spaces
interval duration

Metric Significance

This metric indicates who may not use this service on a recurring basis.

Average Number of Extensions per Session

Overview

This metric displays the average number of times a parker extended their session during the specified interval.

Note: This metric only applies to operators who allow extensions. If you do not allow extensions, your metrics will display as zero.

Calculation

(a / b)

a = total number of extensions for all parking sessions
b = total number of parking sessions

Data Source(s)

session information
extensions

Factors That Affect This Metric

rules and regulations (e.g., what time limits and configurations affect the spaces)
location (e.g., does location encourage you to linger)

Metric Significance

This metric reveals (on a per-session basis) the utilization or adoption of the extension feature and provides insight into demand. If you see many extensions, you could choose to change the parking duration, add a variable rate, or change the rate.

Note: This metric will indicate whether your peer city provides the option to extend a session.

Average Number of Extensions per Unique User by Interval

Overview

This metric displays the average number of times a unique user extended their session during the specified interval.

Note: This metric only applies to operators who allow extensions. If you do not allow extensions, your metrics will display as zero.

Calculation

(a / b)

a = total number of extensions by unique users for their parking sessions
b = total number of unique users

Example

Lot A experienced 19 extensions between 1/1/23 - 3/31/23

User A performed 4 extensions each in Jan, Feb, and March
User B performed 2 extensions in each month
User C performed only 1 session in March
User D performed 0 extensions but parked once in March

The graph would display these results:

Yearly: 6.3
- (19 extensions) / (4 unique users for the year)
Monthly
- January: 3 = (6 extensions) / (2 unique users in January)
- February: 3 = (6 extensions) / (2 unique users in February)
- March: 2.33 = (7 extensions) / (3 unique users who performed extensions in March)

Data Source(s)

session information
extensions

Factors That Affect This Metric

rules and regulations (e.g., what time limits and configurations affect the spaces)
location (e.g., does location encourage you to linger)
quantity of users

Metric Significance

This metric reveals (on a per-unique-user basis) the utilization or adoption of the extension feature and provides insight into demand. If you see many extensions, you could choose to change the parking duration, add a variable rate, or change the rate.

Note: This metric will indicate whether your peer city provides the option to extend a session.

Number of Sessions per Weekday (Monday - Friday)

Overview

This metric displays the number of parking sessions that occurred on a weekday.

Calculation

(a)

a = the total number of transactions that occurred on a weekday in the selected date range

Example

Lot A experienced 400 weekday transactions during 1/1/23 - 3/1/23

200 in January
100 in February
100 in March

The graph would display 200 for January, and 100 each for February and March.

Data Source(s)

session information

Factors That Affect This Metric

location
rules and regulations

Metric Significance

This metric reveals your operation’s weekday parking demand. For example, you will be able to determine how many sessions occurred on weekdays in January 2023 or how many sessions occurred on weekdays during 2022.

If you have low weekday demand, you could adjust your rates and/or review your parking policy.

Number of Sessions per Weekend (Saturday - Sunday)

Overview

This metric displays the number of parking sessions that occurred on a weekend.

Calculation

(a)

a = the total number of transactions that occurred on a weekend

Example

Lot A experienced 400 weekend transactions during 1/1/23 - 3/1/23

200 in January
100 in February
100 in March

The graph would display 200 for January, and 100 each for February and March.

Factors That Affect This Metric

location
rules and regulations

Metric Significance

This metric reveals your operation’s weekend parking demand. For example, you will be able to determine how many sessions occurred on weekends in January 2023 or how many sessions occurred on weekends during 2022.

If you have low weekend demand, you could adjust your rates and/or review your parking policy.

Average Session Duration

Overview

This metric displays the typical amount of time used for the interval in the selected date range.

Calculation

(a / b)

a = total amount of time purchased for all sessions
b = total number of sessions

Data Source(s)

session information

Factors That Affect This Metric

rules and regulations
location (e.g., what is the driving force that brings people to the area)
whether your operation allows extensions

Metric Significance

This metric reveals the demand for parking and turnover patterns. To encourage shorter average session duration, you could increase your rates.

Percentage of Sessions Occurring on Weekdays

Overview

This metric displays the percentage of parking sessions occurred on a weekday.

Note: The Day and Hour intervals are irrelevant for this metric, because they would indicate 100% on a weekday and 0% on a weekend.

Calculation

(a / b) * 100

a = the total number of weekday sessions
b = the total number of sessions

Data Source(s)

session information

Factors That Affect This Metric

rules and regulations
location
type of location (e.g., university, tourist town, etc.)
is the location seasonal

Average Gross Revenue per Session

Overview

This metric displays the average gross revenue for a parking session.

Calculation

(a / b)

a = total of the gross revenue for all sessions
b = total number of sessions

Data Source(s)

session information

Factors That Affect This Metric

rules and regulations
location
type of location (e.g., university, tourist town, etc.)
is the location seasonal

Metric Significance

You will be able to answer questions such as: How much did a typical session cost in 2023? How much did a typical session cost in January 2022? How much did a typical session cost in the week of 4/1/23?