Accurate Multiple-Vendor Programmatic Reporting: Fantasy or Reality?

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The biggest challenge to true programmatic reporting has been normalizing data from multiple vendors, because there is tremendous disparity from vendor to vendor in what they support and what dimensions they provide.

In trying to get all the data aggregated in one place, you’re not even talking the same language sometimes. Beyond the initial column challenges, the aggregated data itself also needs to be normalized: unified, transformed, and standardized, there’s just so much of it. For now and the foreseeable future, publishers are in a severe struggle to do it on their own. And any achievements in this area will only serve them.

Pressuring Partners to Produce Data You Need

If you normalize all data, it becomes clear what can and can’t be obtained from each partner and empowers publishers to ask for more compatible data. If you look at something like what advertisers are buying across all of the platforms by day you might find that it isn’t available from some partners, so you mark which partners don’t have that information.

With this significant leverage, publishers could then say, “You know, I’d really like to see this data. I can see it from five of my six partners. You’re the only platform that doesn’t have it. Can you provide it?” That could even become a criteria for partner vetting – if they give you data you’re interested in or not. Insisting on compatible data sets will push the industry forward.

Making Data Applicable to Action

Normalized data allows you to easily and quickly identify trends and patterns amongst your partners. These things are really hard to do when you’re just staring at a spreadsheet. Spreadsheets can help quickly analyze data.

The real problem is building those spreadsheets, gathering the information in a meaningful way, and then transforming it into something you can take action on.

The goal is not to replace the spreadsheet, which is a very well-known language. The goal is to cut all the wasted time trying to massage and mold the data into the formats you need to take action on.

The right tool set helps get you there faster…much faster. For example, you put the numbers into a graph, and all of a sudden you can see the trends such as if a particular partners’ eCPM numbers are slowing down faster than others, if their fill rates are dropping, or how revenue is tracking against other partners. That’s how you start to see where you need to focus, and which partners you need to troubleshoot or even dump.

When programmatic really started to get into the stacks of many of our publishers, you could see the difference in ad request patterns before programmatic and afterwards. These were just passbacks and the waterfall method of doing programmatic.

Header Bidding Arrives…

Now, with header bidding the number of ad requests to deliver a single ad has gone up by an order of magnitude. All of this is measurable and can tell you how much lag has been introduced before you can finally deliver a tag. Publishers can measure a baseline for latency across their different partners and then set it up to monitor on a regular frequency to measure performance throughout time. Keeping an eye on the performance of each partner in their header-bidding stack can be useful in determining the real value of that partner in their ad delivery chain.

Looking at publisher data over the past 10 years, you can see where header bidding started taking off, because the reports also have grown by an order of magnitude. That data all needs to be processed and analyzed. It’s that much more important to have the right tools to help identify when and where you need to take action.

For programmatic reporting, integrations in OMS are only as good as the data fed back into them. Being able to push something like advertiser buying trends back into those systems can probably give you additional insights, but the problem is still data normalization. The same advertiser might be named uniquely in different programmatic platforms—so you’d have to align Coca Cola with Coca-dash-Cola, and so forth.

New Approach: Analyzing Bid Rates

Smartly evaluating demand partners requires analyzing bid rates as well as amounts. At Ad-Juster we can bring it all together in one place and normalize it. With that, publishers will be able to identify unique demand and determine its value, specifically with partners that have demand overlap. Different SSPs might be talking to the same demand partners.

We know direct reporting very well, and by adding the programmatic data set, we can provide a true picture of the value publishers are getting. Publishers can start to look at where the spend is coming from on an advertiser-to-advertiser basis. If they want to upsell an advertiser to a more premium product, they now would have the data to back up the ROI they’re getting.

Founded in 2007, Ad-Juster simplifies the manually intensive processes associated with digital ad operations. As the complexity of the digital landscape has exploded from standard display 3rd party ad delivery to include new systems and metrics for mobile, video, programmatic, viewability and many other growing ad quality measurements, Ad-Juster advancements have provided clients with state-of-the-art streamlined daily reporting as well as dashboard visualizations. Over 120 brand name digital publishing companies use Ad-Juster, including over half of the comScore Top 50 publishers by impression volume. The company was acquired by Innotech Capitals, an international private equity consortium group and the investment arm of Innotech International Group in January 2017.

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