Google Analytics Historical Trends & Date Ranges
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Google Analytics Historical Trends & Date Ranges

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Google Analytics users only concern themselves with current traffic trends and date ranges

Google Analytics users only concern themselves with current traffic trends and date ranges

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  • 1. Google Analytics Selecting Historical Trends & Date Ranges By: Errett Cord Email: ecord@ecord.us Twitter: @errettcord
  • 2. Historical Traffic Trends Google Analytics users only concern themselves with current traffic trends, but identifying patterns based on previous traffic can yield valuable insights into how traffic can change over time. One of the best ways to view historical data is by using the Compare to Previous Period tool in the date range dialog box.
  • 3. Historical Traffic Trends When you’ve selected the desired date range (and the previous period to compare it to), you can apply the filter to see how the traffic compares from one time period to another – in this case, from March 2 to April 30, and March 12 to April 11 (the previous period).
  • 4. Date Ranges Applying this filter to a weekly view, you might think that a Monday-Sunday week view would mirror the previous period exactly – but it doesn’t. Instead, Google Analytics defaults to the number of days in the specified period, not to the corresponding days of the previous week.
  • 5. Date Ranges The first date range is Monday, May 5 to Friday, May 9. This covers the a five-day business week for this period. When we select “Compare to Previous Period,” Google Analytics pulls data from the five-day period immediately preceding the first date range, not the previous five-day work week. This means the data included in the graph is actually comparing completely different days of the week, which displays bogus results.
  • 6. Date Ranges Make sure we specify a custom date range (in which the days of the week match perfectly), you will see that the two graphs are virtually identical. Note that to accomplish this, you’ll need to enter the desired date range manually in the relevant fields, rather than clicking on a start day and letting Analytics fill in the blanks.