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Answers to Common Discrepancy Reporting Questions

Despite best efforts, discrepancies in ad operations are still an industry-wide problem. We know the sheer volume of data involved in discrepancy reporting can be overwhelming and often get questions from businesses about reporting best practices. Here we’ve answered a few of the top questions to help you get the most out of your discrepancy reporting, regardless of your method.

What exactly should I be looking at?

Something that is digestible. Pulling everything possible means a lot of unnecessary information that you probably don’t need—more data doesn’t mean more useful. Reporting systems can quickly confuse new users, many of whom select a vast array of columns and end up with something so massive it’s not analyzable. Use filters and sorting to your advantage in order to break down your reports into manageable chunks. Understand what dimensions are critical, (such as order, line item, or placement) and keep an eye out for additional metrics that are important for your business (such as viewability). Pacing, OSI (on-schedule indicator), and third-party discrepancies are also important as is having a good understanding of the application of those KPIs.

When should I be looking?

The best practice for discrepancy reporting is daily. This is especially important early on in the campaign, but you’ll want to make sure you’re not making adjustments too early as campaigns can take a few days to level out. Pacing reports should be run at least weekly to keep track of the campaigns that are about to end, making sure they will deliver and invoice in full. This is also where you want to check that the data from your OMS is passing through and linking up to your ad server data flawlessly. As long as those reports are constantly monitored, it should make things much easier for your finance team when they need to process monthly reports.

Who should be looking at this data?

Three important players that should be regularly looking at reports include operations teams, account managers or sales (depending on your organizational structure), and finance teams. Many times, departments outside of ad ops don't have access to ad server data. Why should other departments keep an eye on operational data? We've found that publishers that include more members of their team in campaign reporting experience a smoother process. When more people are involved, we often see different types of reports going to each team in different intervals.

Ad operations needs to keep an eye on their inventory in order to reduce waste from overbooked impressions. Account managers should try to stay on top of the agencies they're working with in order to make sure deals go smoothly. Finally, finance teams need these reports for accurate billing. The quicker they get the reports, the quicker they can bill, and the quicker the organization gets paid.

What makes good reports?

To understand how to make good reports, it's important to understand how to tie all your data sources together. Your ad server data is part of a delivery chain along with any ad-quality vendors that you might be implementing. The ability to combine these data sources together originates from your publisher ad server, so you need a way to tie this data to each other.

So how do I piece this data together?

What's the best way to piece together all the data scattered across different platforms, ad servers, and order management systems? We've seen many attempting to manually tie data from different ad servers together by manipulating naming conventions in the publisher ad server. It's a very common way to solve this problem; people still do this today. But this can involve a lot of manual work, time-intensive processes, and result in errors due to oversight or unpredictable names.

Ultimately, utilizing tag data is the best way to gain visibility into what occurs during ad delivery. Ad-Juster D-FIT (data- fusion, interpretation, translation) leverages the tag data set up in your ad servers. It uses tag data, along with any mapping strategies that can be derived from names in line items or placements, to tie the first and third-party ad server data together. Regardless of the method you choose, it's important to understand how to tie this data together, whether by a traditional method of naming conventions or advanced mapping.

If you have other reporting questions you’d like to see answered, don’t hesitate to contact us!