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Research
             It should be cautioned that a small number of large projects   (22 percent). Resorts in the Midwest are the most likely to
             can heavily impact the numbers, and that not all ski resort   issue a daily ticket to passholders (31 percent, vs. 0 to 9      DRIVING SMART DATA ...
             capital improvement projects are represented in the data   percent in other regions).
             (because of non-response to the survey overall, and to the   The proportion of resorts using RFID increases with
             capital improvements question in particular).           size, from 10 percent at the smallest resorts to 45 percent at
                                                                     the largest. Conversely, small resorts are much more likely to
             Season Pass Tracking & Visits                           issue daily tickets to passholders than large resorts, or to esti-
             per Passholder                                          mate pass visits or use “other” methods. Typically, the largest
             In a further effort to document ticket accounting patterns,   resorts have more capital to spend on ticket scanning equip-
             resorts were asked to identify how they track season pass   ment and software than do the smallest ski areas.                               Age: 40                                    Loyalty Points: 4040
             usage (figure 6). This season, 34 percent of responding resorts   Given the number of season passes sold (11,065 per
             scanned all passholders in line, 27 percent estimated pass   resort, up 3.9 percent) and the number of snowsports visits
             usage (typically by applying an assumed average days of use   generated by those passholders (104,514 per ski area, down
             factor), 26 percent used RFID, and 8 percent issued a daily   3 percent), it is estimated that the average season passholder
             ticket for passholders. Finally, 10 percent used other counting    skied/snowboarded 9.4 days in 2016–17, down from 10 days                                                                    Name: David Schneider
             methods or estimates (such as a daily or seasonal percentage   in 2016–17.
             factor relative to lift tickets sold, counts at the lifts, or periodic    The average number of visits by passholders at any indi-
             scanning of passholders).                               vidual ski area can vary depending on a number of factors,
                 By region, resorts in the Rocky Mountains are most likely   such as season pass price, size of the ski area, and other reasons.
             to scan season passes or use RFID (88 percent combined),    The accuracy of the count of visits by season passholders has                  Season Ticket
             closely followed by the Pacific Southwest (87 percent) and   improved dramatically, as ski areas have been investing in
             Pacific Northwest (70 percent), with lower usage in the   more sophisticated ticket scanning and tracking technology
             Northeast (52 percent), Southeast (31 percent), and Midwest   and software.


             Figure 4: Average Days Open by Region, 2014–15 to 2017–18; 27-season average

                                                                                                                PACIFIC
                  AVERAGE DAYS OPEN  AND OPERATING                                                142  148            146                                   Male
                                                                                   ROCKY
                                                                                                  PACIFIC
             160       OVERALL       NORTHEAST      SOUTHEAST      MIDWEST       MOUNTAIN       SOUTHWEST      NORTHWEST                                                                                 Hometown: Denver
                                                                                                                    152
             140                     133    131                                    132  128  129  128  133  132  133

                      119  122  125       125  118                               125                                     122
                        114                                       112     111
             120                115
                                       108         109                                          107
                                                           103
             100                                        97   95        96                                      95
                                                                     92     94


              80
                                                      73
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               0
                                          2015–16
                              2014–152014–15
                              2014–15     2015–16     2016–17     2017–18     27-SEASON AVERAGE (91–92 TO 17–18)SEASON AVERAGE (91–92 TO 17–18)SEASON AVERAGE (91–92 TO 17–18)
                                          2015–16
                                                                              27-
                                                                  2017–18
                                                                  2017–18
                                                                              27-
                                                      2016–17
                                                      2016–17
                                                                                                                                             www.skidata.com                        (303) 980 4441
             10  |  NSAA JOURNAL  |  FALL 2018
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