Let’s figure out what reports consist of, and explain what each section means:

We will start with the simplest option of Full statistics for popunder during the last 7 days with grouping by date:

First, you can see the report in the form of graphs showing the day-by-day changes of basic indicators:

Requests – the gray graph indicates the number of popunder displaying attempts 

Impressions – гed graph that shows the number of real popunder displays

CTR - Impressions/Requests*100 ratio. The higher it is, the better popunders perform on the website. If this indicator keeps below 50%, you’re likely to have problems with behavioral settings, or visitors do not click the ads. Anyway, if this is your weak side, you should work on raising the CTR. 70% and higher level is considered to be normal. 

CPM – cost per 1000 ad impressions (according to ad networks). 

Income – the daily income from all popunder creatives shown.

On the above-featured graph, we notice a pronounced growth of traffic and income since October 13. The growth was triggered by the installation of AdSpyglass popunder solution and customization of our Anti Adblock script.

Below, you can see the statistics in the form of a table:

Aside from the basic indicators, the table also shows: 

Returned – the amount of traffic returned by ad networks and redirected by Adspyglass to other ad networks.

Ad Network impressions – traffic counted by ad networks.

Discrepancy – loss of traffic, traffic that was not approved by ad networks. Calculated by the formula: (Ad Network impressions + Returned)/Impression*100. The level up to 20% is acceptable. If this level exceeds 20%, you should perform a deep analysis and define the ad network causing it. In most cases, it happens because of the so-called shave.

rCPM - Real CPM = income/impressions. This is your real CPM with the traffic loss taken into account. 

Let’s take a look at another grouping approach for analysis – group by creative:

Using the same publisher’s example we will generate popunder statistics in 1 day grouped by creatives. In this case, we use only table (no graphs are used). 

We can see on which creatives and from which ad networks the traffic was sent, how it was counted by ad networks, and what was income. 

As a rule, such a way of grouping is used to evaluate creatives’ Discrepancy, check which creatives attracted more traffic, and what CPM rate was.
In our example, the Discrepancy is normal (20% and lower is a good level). We can see that the creatives of Gay_pu_mob campaign have a low CTR (50% and lower). It means that websites showing those creatives have problems with the mobile version – the issues should be fixed.  

We can also see that creatives of TrafficForce do not buy out a huge amount of traffic (see Returned column). Most likely, the ad network does not like your traffic and can be switched off. It is likely to reduce the loss of redirected traffic and increase your income. To get a closer look at the situation with TrafficForce, you can check the report for one creative with grouping by country. 

We sorted countries by the request number and see that India is the first, but out of 21,072 popunder impressions, only 445 were bought by TrafficForce, and 17,194 were returned.

If you take a look at Italia and Sri Lanka, you will see that TrafficForce did not buy traffic: 585 and 797 hits were returned, and the rest was lost during redirects. Thus, we can see TrafficForce does not buy your traffic well, and it would make sense to switch the ad network off. 

This example explained to us how to figure out the weak spots in your ad campaigns using filters and grouping in Full statistic reports. 

We added Compare to option for you to easily analyze your activity and understand in detail the reasons for its growth or decrease for any breakdown you need: domains, ad type, ad network, creatives, etc. For that, just:

Update the report and check out for the Δ (Change relative to the compared period) column value (1):

As an example, please note that you see the Income value for the date chosen in the Period tab (25/04/2021) that is compared to be greater by 5% to the date chosen in Compare to tab (24/04/2021).

Using SSP statistic reports you can analyze the traffic coming to DSP connected with AdSpyglass.

I selected the same time span, group by date, and ticked detailed reports. You can also filter by DSP, Stream, creatives and Ad type.

More detailed information can be obtained by grouping the report by creatives or Ad network (DSP). Then you can understand which network buys more traffic, and which one buys it poorly or runs a server at points remote from your traffic making most of the requests go to timeouts. 

This is a highly useful report that allows for analyzing recent ad display changes or website design alterations. 

We can see the same filters as used in other reports.

The graph shows the ad activity yesterday (gray) and today (blue). Requests are shown on the graph by default, but you can switch them to Impressions or CTR in the right upper corner of the graph. This switch would be of much help if you want to analyze the popunder behavior after response settings change. 

The graph is updated every 2 minutes and displays 2 days of activity. Aside from ad performance, you can also check the server-related issues. In our example, the activity is smooth, but if you see the spike-like graphs or sudden falls, there must be something wrong with your servers – you should report it to your administrator and contact your hosting company. 

If the indicators on today’s graph are far below the indicators of yesterday, you’re likely to have some problems with your website. 

This is a convenient report that helps to understand recent changes on the website and add new ad networks. However, the report is not precise – it simply allows making better/worse evaluations. We recommend checking instant income alterations in 4-5 hours after changes. 

In this report, you can see the income from each particular ad network within a certain time span. 

The real-time activity of traffic returned by ad networks. The graph gives you insight into how well your traffic is being bought. If the activity has risen suddenly, probably, the quality of your traffic has fallen and ad networks ceased to buy it, or you added an ad network that does not buy much of your traffic.