From Inside Radio-
Despite conversion to PPM, ratings “bounce” is alive and well. Last May, long-running smooth jazz bastion KKSF, San Francisco flipped to classic rock, giving Inner City’s urban AC “The Quiet Storm” KBLX a ratings lift. Among persons 25-54, KBLX grew from a 2.7 in April to a 3.7 in May, then a 4.1 in June and a 5.2 in July. Then something changed. KBLX fell precipitously to a 3.5 in August, followed by a 3.1 in September. The ratings roller coaster continued in the fall and winter: 3.7 (October), 4.6 (November), 4.5 (December), 4.7 (Holiday), 4.1 (January). From last May to January, the station ranked as high as second and as low as eleventh. Welcome to the world of PPM ratings bounce. One promise of electronic measurement was that it would greatly reduce or eliminate bounce caused by sample fluctuations. But in San Francisco and other markets, there are sometimes wide ratings swings that can’t be explained by changes in programming. “Even if KBLX picked up every single person [KKSF] lost, you still wouldn’t get to KBLX’s July number,” Inner City Broadcasting-New York VP/GM Deon Levingston says. Between February and July 2009, the station’s 25-54 AQH persons more than doubled, from 7,500 to 15,100. Ratings bounce isn’t confined to urban stations. In a big rock and sports market like Chicago, you wouldn’t expect hot AC to be #1 in men 25-54. But that was the case for Bonneville’s “101.9 The Mix” WTMX last summer. The station was tracking in the low-to-mid three-share range in the demo from October 2008-February 2009. Then it jumped into the low fours in March and April and the low fives in May, June and July, making it first or second in men 25-54. It’s since fallen off and ranked 14th in the demo with a 3.0 in January. “There’s always going to be sampling error around whatever sample you select,” Arbitron VP of research methods and quality Beth Webb says. “The PPM has more stability month to month and is better than the diary at providing real trends. But we still have sampling variation and panel turnover and that affects the estimates
Despite conversion to PPM, ratings “bounce” is alive and well. Last May, long-running smooth jazz bastion KKSF, San Francisco flipped to classic rock, giving Inner City’s urban AC “The Quiet Storm” KBLX a ratings lift. Among persons 25-54, KBLX grew from a 2.7 in April to a 3.7 in May, then a 4.1 in June and a 5.2 in July. Then something changed. KBLX fell precipitously to a 3.5 in August, followed by a 3.1 in September. The ratings roller coaster continued in the fall and winter: 3.7 (October), 4.6 (November), 4.5 (December), 4.7 (Holiday), 4.1 (January). From last May to January, the station ranked as high as second and as low as eleventh. Welcome to the world of PPM ratings bounce. One promise of electronic measurement was that it would greatly reduce or eliminate bounce caused by sample fluctuations. But in San Francisco and other markets, there are sometimes wide ratings swings that can’t be explained by changes in programming. “Even if KBLX picked up every single person [KKSF] lost, you still wouldn’t get to KBLX’s July number,” Inner City Broadcasting-New York VP/GM Deon Levingston says. Between February and July 2009, the station’s 25-54 AQH persons more than doubled, from 7,500 to 15,100. Ratings bounce isn’t confined to urban stations. In a big rock and sports market like Chicago, you wouldn’t expect hot AC to be #1 in men 25-54. But that was the case for Bonneville’s “101.9 The Mix” WTMX last summer. The station was tracking in the low-to-mid three-share range in the demo from October 2008-February 2009. Then it jumped into the low fours in March and April and the low fives in May, June and July, making it first or second in men 25-54. It’s since fallen off and ranked 14th in the demo with a 3.0 in January. “There’s always going to be sampling error around whatever sample you select,” Arbitron VP of research methods and quality Beth Webb says. “The PPM has more stability month to month and is better than the diary at providing real trends. But we still have sampling variation and panel turnover and that affects the estimates