Keeping Track of my Panel

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You have built up a comprehensive panel over time, but don't know how to get an overview of its structure and general operation in a simple and efficient way? Then you've come to the right place!

In this step-by-step guide, we will show you how to create detailed panel statistics with just a few clicks in the Statistics menu of the People module – with exactly the data that is relevant to you. Also, we provide you with the means to track the structure of your panel population using quotas.

Panel Statistics

How many of the panelists who have joined your panel in the last three months are male or female? What is their educational background and how did they actually join your panel? How many panelists have received more than two surveys in the last 4 weeks and what age group do they belong to? These are all questions you can answer via the Panel statistics menu in the People module – provided, of course, that you have saved the relevant master data for your panelists. Your panel statistics can contain information on various general criteria such as category and group membership, entry period, panel status, individual master data and performance data. The performance data also includes tracking variables, which are particularly interesting for analysis and evaluation purposes. These variables record how panelists interact with your panel (e.g. number of survey starts, number of sample memberships, number of bonus points received). More information on the topic of tracking variables can be found here: https://qbdocs.atlassian.net/wiki/pages/createpage.action?spaceKey=~7120208cccb5ff3706465482544efb0b37fd09&title=Tracking%20Variables. In the following, will show you all the steps to configure and create detailed panel statistics using two different examples.

Create Panel Statistics

We will now show you the individual steps and configuration settings for creating panel statistics using two different examples. You can find the Panel statistics menu under People > Statistics > Panel statistics. As soon as you open the menu item, you will be taken to a page where you can configure your individual panel statistics in detail.

Example 1 – Configuration

In our first example, we want to generate statistics on how many invitations the panelists in a particular group have received and how many surveys they have completed. We also want to break down the results by gender. This could then indicate, for example, whether your surveys are more interesting for men or women. To do this, follow the steps below:

In the Base area, select the corresponding panel group category for Panel group category. In our case, this is "default".
Then, under Panel group, select the desired panel group to which you would like to restrict the results. In our case, this is the "Statistics test" panel group.
Under Split variables, select the variable u_gender: Gender.
Retain the default setting Active in the Panel status area.

Under Performance data, select the variable track_num_completed. This stands for the number of completed surveys.
Then select the variable track_num_invited. This stands for the number of invitations.
Click on Create statistics at the bottom right of the page.

Example 1 – Results

After clicking on Create statistics, your statistics will be displayed immediately. At the top you will find a summary of the base:

Then, the number of completed surveys is displayed, broken down by gender:

1 panelist (male) from the Statistics test group has not completed any survey.
1 panelist (male) from the Statistics test group has completed 2 surveys.
2 panelists (female) from the Statistics test group have completed 3 surveys.

Then, you can see the number of invitations broken down by gender:

Two male and two female panelists have each received 3 invitations.

Example 2 – Configuration

In our second example, we want to create statistics on how many panelists entered the panel via a specific way of entry. The results should be broken down by age and filtered according to a specific entry period. To do this, proceed as follows:

In the Base area, select the variable md_age: Age for Split variables. The age of panelists is recorded in this master data variable. Information on creating and managing master data can be found here.
Under Entered panel from and Entered panel until, select the start and end time for the period you want to filter by.
We would like to create statistics for all panelists – regardless of their status. Therefore, activate the checkbox for Select all in the Panel status area.

In the Performance data area, select the variable pinput, which records the mode of entry of panelists.
In the Performance data area, select the variable reg_code, which records the way of entry of panelists.
Click on Create statistics at the bottom right of the page.

Example 2 – Results

Your statistics are created and you will find a summary of the base in the upper area:

Further down, the statistics on the mode of entry of panelists are displayed:

You can see, for example, how many panelists have been imported, entered by the admin or invited to the panel, and you have a direct overview of the distribution of panelists' ages. In our example, the majority of panelists were imported.

The statistics on the way of entry of panelists are displayed below:

In our example, you can see that the majority of panelists entered the panel via the standard way of entry "Default". No information on the age of these panelists is available. If the age or other panelist characteristics are of interest to you, it is advisable to ask about them as part of a master data survey.
A small proportion also registered via Portals. Here you can also see the age distribution of panelists.

Quotas

To ensure that your panel population meets your requirements, you can create quotas in the Statistics section of the People module. This allows you to compare target values for any combination of master data variables – e.g. age, gender, region, etc. – with the actual values from your panel. For example, you need 100 females and 100 males between the ages of 20 and 30 in your panel. Using a special quota that contains the variables for the corresponding age and gender, you can compare these target values with your actual panel population and then recruit more panelists if necessary.

Preparations

We will take up the above example and create a quota with the variables "age" and "gender" in the next step. Our target values: 150 females and 150 males between 20-30, 150 females and 150 males between 30-40 and 150 females and 150 males between 40-50.

In the first step, we need to create a grouping filter that will determine the actuals of our panel. To do this, proceed as follows:

In the People module, select the Groups menu item on the left-hand side.
Then select the Grouping filters menu item on the left-hand side.
Click on Create filter condition.

Enter a name for the filter. In our case: "Age_gender".
Enter a filter description if required. For the age of panelists, we have the master data variable "md_age" with the response categories "1 (20-30 years)", "2 (30-40 years)" and "3 (40-50 years)". Our filter should include all panelists in these age ranges. Proceed as follows to configure the filter criteria:
Under Variable, select the master data variable md_age, under Condition the option equal and under Value the number 1.
Click on Save.
In the next line, select OR as the conjunction, the master data variable md_age under Variable, the option equal under Condition and the number 2 under Value.
Click on Save.
In the next line, select OR as the conjunction, the master data variable md_age under Variable, the option equal under Condition and the number 3 under Value.
Click on Save.

=> Your filter now includes all panelists between the ages of 20 and 50.

Create Quota

We can now create the quota. To do this, follow the steps below:

In the People module, select the Statistics menu item on the left-hand side.
Then select the menu item Panel quotas on the left-hand side.

Click on Create quota.
Enter the name for your quota under Quota name. In our case "Age_Gender".
Under Grouping filter to use when calculating actuals, select the filter you created in the previous step.
Select the variable md_age: Age under Quota variable 1.
Under Quota variable 2, select the variable u_gender: Gender.
Click on Save.

Upload Target Values

The last step is to upload the target values for the quota. To do this, proceed as follows:

Click on the upload symbol in the line with your newly created quota.

Click on the Download import template button, fill in the template and save it. The template already contains the variables that you selected when creating the quota. We want 150 participants as the target value for all three age ranges – "1 (20-30 years)", "2 (30-40 years)" and "3 (40-50 years)". Our import file therefore contains the following data:

Click on Choose file and select your saved import template.
Click on Import.

Show Cell Values

You can now display the quota allocation for the quota you have created and compare the target values with the actual values.

In the line with the quota you have created, click on the symbol Show cell values.

The quota allocation is displayed immediately. Cells for which the quota has been met are displayed in green. If the quota has not been met, the corresponding cell is displayed in red. In the example below, you can see at a glance that you need to recruit both female and male participants for the age range 30-40, male participants for the age range 40-50 and female participants for the age range 20-30. The other segments are sufficiently staffed.

Please note that the actuals are not updated in real time. The last update time is displayed; if necessary, you can update the values manually.