3 Reasons Why Ad Revenue Reporting Alone Makes You Lose Money

Posted by Asmaa Bentahar on

Over the last few years, publishers’ ad stacks have become much more elaborate than they were before. Nowadays, to drive maximal revenue, publishers have to work with several advertising partners and different technologies: 

  • several SSPs,
  • one or more ad servers,
  • different wrappers (Prebid, Open Bidding, TAM, INDEX),
  • one or more DMPs,
  • several Ad Networks or Content Recommendation partners,
  • a Consent Management Platform,
  • and more.

This multiplicity of partners creates a fragmented technological stack, where data is scattered across different platforms and is thus difficult to consolidate. 

To solve this problem, publishers usually build internal reporting tools or use commercial solutions to centralize all their revenue data in the same place and meet the needs of their Sales and Finance teams. Reporting is essential indeed for this part of your team, but it has several limitations, which make it utterly insufficient for the Ad Ops team. These limitations can make you lose a considerable amount of time and money.

Throughout this article, we will explore the 3 reasons why this kind of tool does not cover all your needs and how you can fix this, thanks to ad revenue monitoring.


Reason 1:  Access to data is a nightmare 

As mentioned above, multiple partners mean scattered data. If you are creating your own reporting tool, you will either have to get this data manually from each corresponding platform (often a CSV file) or connect each of your partners’ APIs to your in-house solution. All this can quickly become a very time-consuming and cumbersome process.

Let alone the fact that these APIs often break down, and you end up downloading your report manually anyway.

When it comes to data punctuality, data is available at Day+1, and for the majority of partners, this data is available with several days of latency. While some days of delay can be acceptable for the Sales and Finance teams, it is far from being true for Operations people who need to get answers as fast as they can ask the questions.


Reason 2: Data quality is weak and inconsistent

The data provided by SSP reports and APIs lacks crucial information and is uneven from a partner’s report to another, there is absolutely no standardization effort made. You can find metrics that have the same naming but which mean totally different things from a report to another, for example:

  • for SSP 1, “Revenue” may refer to the daily revenue earned before invalid traffic adjustment; 
  • for SSP 2, “Revenue” may refer to the net amount to be paid to the publisher.

Inconsistencies like these are prevalent, making the data consolidation process very tedious and cumbersome.

Moreover, the number of metrics provided by partners is not the same. If you’re lucky enough to find a specific metric in five of your partners’ reports, there are chances that this same metric will be missing in two others, the quality of your global reporting will suffer, as you will be forced to level your reporting down to the worst quality report.

Let’s say that you need to answer a fundamental question: “What are my revenues per website and per day?”   You should be able to find this information in “at least” all your partners’ reports. If this information is missing in even one partner report, your reconciliation is doomed! 


Reason 3: Data heavily lacks granularity

The question I gave above is very basic. So, let alone situations where you need more granularity, say you need to understand the structure of your revenue by country, by browser, by ad slot, and by device. In the majority of cases, it is just impossible to have an answer. Your partners do not provide these dimensions because they are challenging to map and require endless projects.

Of course, you cannot blame your SSPs for this, because it is not their core business to provide you with excellent reporting. Bringing you more money is!

And even if after a lot of effort, you’ve managed to overcome all these limitations and build your in-house reporting tool or got an out-of-the-box reporting solution. You still don’t meet the needs of a crucial part of your team. While Finance and Management can accept these loopholes, Ad Operations teams cannot. Ad Ops teams need granularity and punctuality; they even need real-time!


But why do Operations teams need granularity and punctuality?

When talking about Operation teams, I am referring to revenue analysts, developers, and Ad Ops, of course. These people need to be able to pinpoint the source of an issue when it happens, very precisely. 

With no granularity, you end up attributing unexplained revenue drops to seasonality!

For example, if you have a 50% revenue drop for Teads between today and yesterday, this drop can have different reasons:

  • Is it because Teads bids less?
  • Is it because Teads always loses the bid to the ad server?
  • Is it because Teads loses the bid to another SSP?
  • Did a developer break Teads placement on the website?
  • Did Teads stop receiving the CMP user consent?
  • Is this loss limited to a specific geo? Or a particular website? Or device? Or format?

Almost as many questions as reports that you need to check to be able to get an answer. And then again, the information still needs to be available in the said reports.

Likewise, if, on the one hand, you want to optimize a specific ad unit, but on the other hand, you are not able to precisely isolate the impact of the changes you made, you won’t be able to optimize it.

If you are testing a new setup, a new placement, or a new CMP, you have to wait days (in the best case scenario) or even weeks to get the results. You cannot afford to wait this long, because sometimes one day of latency can mean thousands of euros lost.


Reporting tools are hard to build and maintain, but once created, they can be very precise and will meet some crucial needs on the Finance and Sales Management side. On the other hand, these tools lack granularity and punctuality, which makes them poorly suited for Ops and Developers who require much granular and real-time data. Hence the need for monitoring solutions that provide very granular, independent, and real-time data.

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