Comments on: How to identify real trends in user behavior http://jebstone.com/2009/12/how-to-identify-real-trends-in-user-behavior/ Observation, commentary, and helpful hints at the intersection of web analytics and social science Fri, 06 Aug 2010 21:21:48 +0000 hourly 1 http://wordpress.org/?v=3.0 By: zyxo http://jebstone.com/2009/12/how-to-identify-real-trends-in-user-behavior/comment-page-1/#comment-25 zyxo Sun, 13 Dec 2009 19:39:46 +0000 http://jebstone.com/?p=75#comment-25 The biggest variation in the day-to-day chart are the differences between the weekdays and the weekends. So the first thing to do if you want to look at longer-term trends is making a week-to-week chart in order to gid rid of this oscillating pattern. If by then the trend still is not clear, only then you should move on to more sophisticated methods. Try explaining your EMA to a HiPPO ! The biggest variation in the day-to-day chart are the differences between the weekdays and the weekends.
So the first thing to do if you want to look at longer-term trends is making a week-to-week chart in order to gid rid of this oscillating pattern. If by then the trend still is not clear, only then you should move on to more sophisticated methods.
Try explaining your EMA to a HiPPO !

]]> By: jebstone http://jebstone.com/2009/12/how-to-identify-real-trends-in-user-behavior/comment-page-1/#comment-24 jebstone Thu, 10 Dec 2009 17:02:59 +0000 http://jebstone.com/?p=75#comment-24 Hey Steve, thanks for the great question! You're a step ahead of me: I use the EMA technique to visually indicate whether overall performance is really trending up or down. To that -- as you thoughtfully point out -- it's possible to add "guardrails" based on standard deviations. The guardrails then tell you whether any single day is inside or outside a typical range, while the EMA line identifies whether the movement is reliably a trend. I'll be writing about combining EMAs with standard deviations in a subsequent post, and post some SQL and SAS code for producing EMAs as well. Thanks for reading! Hey Steve, thanks for the great question! You’re a step ahead of me: I use the EMA technique to visually indicate whether overall performance is really trending up or down. To that — as you thoughtfully point out — it’s possible to add “guardrails” based on standard deviations. The guardrails then tell you whether any single day is inside or outside a typical range, while the EMA line identifies whether the movement is reliably a trend.

I’ll be writing about combining EMAs with standard deviations in a subsequent post, and post some SQL and SAS code for producing EMAs as well.

Thanks for reading!

]]> By: Casey Carey http://jebstone.com/2009/12/how-to-identify-real-trends-in-user-behavior/comment-page-1/#comment-23 Casey Carey Tue, 08 Dec 2009 21:59:32 +0000 http://jebstone.com/?p=75#comment-23 Great article, I look forward to the day when more of these capabilities are standard in web analytics products. It really crossing the chasm between data/reporting to understanding/insight. For sites with significant shifts in volume between weekdays and weekends, I either average the base data on 7 days intervals or use only the weekday data. The picture becomes much clearer and exceptions are evident. Great article, I look forward to the day when more of these capabilities are standard in web analytics products. It really crossing the chasm between data/reporting to understanding/insight.

For sites with significant shifts in volume between weekdays and weekends, I either average the base data on 7 days intervals or use only the weekday data. The picture becomes much clearer and exceptions are evident.

]]> By: Steve Jackson http://jebstone.com/2009/12/how-to-identify-real-trends-in-user-behavior/comment-page-1/#comment-21 Steve Jackson Tue, 08 Dec 2009 18:08:26 +0000 http://jebstone.com/?p=75#comment-21 What is the advantage of doing this over standard deviations? Tia steve. What is the advantage of doing this over standard deviations? Tia
steve.

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