Post by account_disabled on Dec 21, 2023 5:46:12 GMT
At the beginning of February, we added a new function to Google Analytics called Group Analysis, which can be found in the Target Audience section. Is it feedback generation, group sessions, or is it another metric? Let's take a look at her teeth and evaluate her benefits. image Figure 1 - Group analysis Group analysis brings us the segmentation of customers according to the given period and the type of action that the customers performed. For example, we can find out the percentage of returning customers over the last 12 weeks, broken down by week.
In this case, it could help C Level Executive List us discover the purchase cycle of a product or how long it pays to target remarketing campaigns , etc. As can be seen in picture no. 1, we have the possibility to work with the size of the defined group, where we can set days, weeks, months and in the period section we set a specific value. At this time, we are limited to displaying historical data up to 3 months, 12 weeks or 30 days. We can also work with any metric from visit duration, transactions to user retention. I am personally interested in the mentioned transactions . If we would like to delve into the data in even more detail, we can add additional segments and thus examine the behavior of individual users within specific advertising channels.
Enough theory, let's get into practice! I set the size of the defined group to weeks, specifically to the displayed maximum, i.e. 12 weeks. I choose transactions as the metric because I'm interested in completed orders and leave the segment set to "all visits". image Picture No. 2 - Practical demonstration Week 0 in the above figure marks for us the period during which the main wave of transactions occurred. The All Visits box can be a little confusing because it adds up transactions over the entire period for each week. Week 1 is 7 days from the measurement period, week 2 is 14 days from the measurement period, etc... As can be clearly seen in picture no. 2, during November it paid off to do remarketing for a longer period, i.e. for weeks 0-3, and currently it is advantageous for the given client to use remarketing for the period 0-1 weeks, which is a total of 14 days.
In this case, it could help C Level Executive List us discover the purchase cycle of a product or how long it pays to target remarketing campaigns , etc. As can be seen in picture no. 1, we have the possibility to work with the size of the defined group, where we can set days, weeks, months and in the period section we set a specific value. At this time, we are limited to displaying historical data up to 3 months, 12 weeks or 30 days. We can also work with any metric from visit duration, transactions to user retention. I am personally interested in the mentioned transactions . If we would like to delve into the data in even more detail, we can add additional segments and thus examine the behavior of individual users within specific advertising channels.
Enough theory, let's get into practice! I set the size of the defined group to weeks, specifically to the displayed maximum, i.e. 12 weeks. I choose transactions as the metric because I'm interested in completed orders and leave the segment set to "all visits". image Picture No. 2 - Practical demonstration Week 0 in the above figure marks for us the period during which the main wave of transactions occurred. The All Visits box can be a little confusing because it adds up transactions over the entire period for each week. Week 1 is 7 days from the measurement period, week 2 is 14 days from the measurement period, etc... As can be clearly seen in picture no. 2, during November it paid off to do remarketing for a longer period, i.e. for weeks 0-3, and currently it is advantageous for the given client to use remarketing for the period 0-1 weeks, which is a total of 14 days.