Editor’s note: This is the second of three articles about defining and measuring visitors to your community. Read “Segmenting first step to measure impact.”
BOULDER, Colorado—Do you ever wonder how many people visit your town or city? More than just a point of curiosity, this type of information is critical to measuring the impact of tourism to your area. A hotel or bed and breakfast can relatively easily tally the number of room nights sold during a year. But how would a DMO or other tourism organization measure the total number of visitors to the community?
A couple ways exist to estimate this figure. One is a “top down” approach employed by research companies like Longwoods or DK Shifflet & Associates. These studies tend to use survey research of a national database of travelers and then drill down to people who visited your city. Those responses are detailed by the number of people in the party, the number of nights stayed (if overnight), the type of accommodations and answers to other survey questions. Using that information, estimates can be made as to the total number of visitor-days (total visitors times days spent), as well as other facts like visitor-nights (overnight visitors times night stayed), visitors (individual travelers), travel parties (total visitors divided by people in group) and other metrics. However, some communities are too small to be able to leverage these national or statewide studies. Others desire more community-specific types of information. Another option is to build a visitor model using a “bottom up” approach.
A “bottom up” approach would involve using some data you probably already have (or have access to) and supplementing it with a visitor survey. The combination of several data sources into a visitor model can effectively estimate overnight visitors and day visitors (and the various sub-sets thereof, as described in Part 1 of this series) to your area.
One obvious place to start would be occupancy data, multiplied by the number of total hotel rooms available and the number of nights in question (a weekend, a month, or a year). This result would give you the number of occupied hotel rooms during that time period. But how many people stayed in each room? And what about visitors who stay with friends, in a second home, in a condo or other accommodations? How about day visitors, either passing through to another location or returning to their own home that night?
That is where the results of your visitor survey come into play. Several questions from an accurate and representative visitor survey can help to determine the important factors that serve as inputs to the visitor model. (Note that a visitor survey can be targeted to a special event or general to all visitors over a longer period of time.)
Similar to the “top down” approach mentioned above, some of the key inputs would be day or overnight visitors, number of people in the travel party, number of nights stayed, type of accommodations, number of people per room and other responses to the visitor survey. One simple calculation using occupancy data and visitor survey data results in an estimate of total visitors:
(NUMBER OF OCCUPIED ROOMS x NUMBER OF PEOPLE PER ROOM) / PERCENTAGE OF VISITORS THAT ARE STAYING OVERNIGHT IN COMMERCIAL LODGING = TOTAL NUMBER OF VISITORS
Other information sources that can be integrated into the visitor model to make it even more robust include hotel tax data, data on air travelers and other third-party sources that can help triangulate estimates and assumptions, further refining the final estimate.
As discussed, several potential methods exist to determine the number of total visitors to your area. Tracking total visitors over time allows your community to understand if tourism levels are up or down and how tourism stands relative to prior seasons and years. Measuring the overall impact of tourism is an important function of DMOs and CVBs and can be undertaken in a variety of ways.