California Trails & Greenways ConferenceMonterey, 2017
Harness Visitor Use Data to Empower Outdoor Experiences
Agenda• Benefits of using data• Data types• Tools to collect data• Analyzing data• Methodology
Benefits of Using Data• Focus efforts• Target relevant audiences• Effective resource management
DATA TYPES
Data Types• Numerical• Geographical • Demographical• Behavioral• Social
Data Types - Numerical• Example:
• A person enters your park• What can we learn
• How many visitors (hike/bike/equestrian) are in the park?• How many visitors came through the northern gate?• What are the preferred times to visit the park?
Data Types - Geographical • Example:
• A person enters your park and walks the Skyline Trail• What can we learn
• What are the most crowded areas in your park?• How long does it take to complete the Skyline Trail?• Did he use the designated trails? Did he go off trail?
Data Types - Demographical• Example:
• A 33 years old female enters your park, and walks the Skyline Trail• What can we learn
• What is the main audience of the park?• What are the interests of a specific demographic group?
Data Types - Behavioral• Example:
• This is the third time that the same 33 years old female enters your park
• What can we learn• What are the main characteristics of the
first/second/third visits?• What is the key reason for recurring visits?
Data Types - Social• Example:
• This is the third time that Alice enters your park
• What can we learn• Alice is also interested in Zumba• Alice’s friends
Aggregation Vs. Specification• Use aggregated data to
• Full park picture• Detect trends• Understand park audience• Identify visiting patterns
• Use specific visitor data to• Personalize visiting experience
TOOLS
Tools• Manual Counts• Automated Counters • Proximity Sensors• Surveys • Apps
Tools – Manual Counters• Data
• Number of visitors• Type (hike/bike/equestrian)
Data Types
Numerical
Geographical Demographical Behavioral Social
Tools – Manual Counters• Pros
• Simple• Complete measurement
• Cons• Minimal information• Measure only a specific time
window
Data Types
Numerical V
Geographical XDemographical XBehavioral XSocial X
Tools – Automated Counters• Data
• Number of visitors• Single Location• Time• Direction • Type (hike/bike/equestrian)
Data Types
Numerical
Geographical Demographical Behavioral Social
* Photos from Eco Counter website
Tools – Automated Counters• Pros
• Complete measurement• Continuous data gathering
• Cons• Require setup• Installation costs• Single location data
Data Types
Numerical V
Geographical VXDemographical XBehavioral XSocial X
* Photos from Eco Counter website
• Data• Number of visitors• Single Location• Time• Direction • Type (hike/bike/equestrian) • User Id
Tools – Proximity SensorsData Types
Numerical
Geographical Demographical Behavioral Social
Tools – Proximity Sensors • Pros
• Continuous data gathering• Partial measurement• Unique identification
• Cons• Require setup• Installation costs• Single location data• Require additional devices (app,
bracelet)
Data Types
Numerical VX
Geographical VXDemographical XBehavioral VXSocial X
Tools – Surveys • Data
• Gender• Age• Main characteristics (e.g. income,
dog owners)
Data Types
Numerical
Geographical Demographical Behavioral Social
Tools – Surveys • Pros
• Simple• Open questions• Flexible
• Cons• Public participation• Partial measurement• Measure only a specific time
window
Data Types
Numerical X
Geographical XDemographical VBehavioral VXSocial X
Tools – Apps• Data
• Number of visitors• Time• Direction• Gender • Age • Main characteristics• Friends
Data Types
Numerical
Geographical Demographical Behavioral Social
Tools – Apps• Pros
• Continuous data gathering• Low installation costs• Direct feedback
• Cons• Partial measurement • Require additional devices
(smartphone)
Data Types
Numerical VX
Geographical VDemographical VBehavioral VSocial V
Data Types and Tools
Data Types Manual Counts
Automated Counters
Proximity Sensors
Surveys Apps
Numerical V V VX X VXGeographical X VX VX X VDemographical X X X V VBehavioral X X VX VX VSocial X X X X V
ANALYZE
Correlation and Collaboration• Use Correlation to
• Combine data sources to gain new insights (i.e. steppers and surveys)
• Use Collaboration to• Enhance your data base with 3rd party data (weather data)• Get insights from other similar agencies
Analyze - Tools• Excel is your friend
• 3rd party dashboards (e.g. Survey Monkey, Google Analytics)
• External visualization tools (e.g. StatWing)
METHODOLOGY
Methodology• First Step: Create a base line
• Current status• Measure impact of changes• Quantity Vs. Speed• Rule of thumb – 3 months
Methodology
MethodologyThe test subject
Methodology
Everything we talked about: data types and tools
Methodology
Analyze the data to gain insights
Methodology• Example: We want to increase weekday traffic
Weekday experience – current status
Survey focusing on weekday visitors
What is important for this specific segment?
Methodology• Example: We want to increase weekday traffic
Weekday experience – current status
Survey focusing on weekday visitors
What is important for this specific segment?
New marketing campaign
Use counters to measure the new weekday traffic
Why did my campaign work (or not)?
Methodology• Example: We want to increase weekday traffic
Weekday experience – current status
Survey focusing on weekday visitors
What is important for this specific segment?
New marketing campaign
Use counters to measure the new weekday traffic
Why did my campaign work (or not)?
The Process• A continuous process • Short iterations• Any level of the organization can implement
SUMMARY
Summary• Data
• Use the right tools to get the data you need• Aggregation Vs. Specification• Correlation and Collaboration
• Methodology• Base line• Build – Measure - Learn
Empower Outdoor Adventures by Connecting Park Managers and Visitors
Easy2Hike PlatformVisitor’s App Managers Dashboard
NavigationEducation & Park Data
Visitors Behavior InsightsData Driven Decisions
Navigation
Easy2Hike – Visitor’s AppEducational Data Safety Corridor
Easy2Hike Park Dashboard• Park Insights• Data Driven
Decisions