Is true programmatic reporting a pipe dream, or is it within reach? Tough question–we can lay out a road map to a programmatic reporting ideal, but it’s easy to see how there might be a lot of twists and turns along that road. For a publisher, getting all the data from all your demand sources is a challenge in itself. Once the data is through the door, you’re still facing the process of normalizing it so you can take meaningful action.
No reason to fear, though–Peter Yang, COO of Ad-Juster, is willing to offer some driving tips to publishers winding down the road to programmatic reporting. He and AdMonsters’ Gavin Dunaway spoke recently about how publishers can manage the data disparity they see–and about the need for transparency on all sides, the role of technological toolsets in collecting and normalizing data, and the importance of knowing your own goals well enough to take action on those data insights.
GAVIN DUNAWAY: True programmatic reporting seems like a bit of a pipe dream. What are some of the biggest challenges on your front?
PETER YANG: The biggest challenge has been getting all the data from vendors and trying to normalize it. We’ve been seeing a lot of disparity from vendor to vendor as far as what they support and what dimensions they provide. And that’s just at the column level.
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. But if we do it once, then all of the publishers can benefit through our economies of scale.
GAVIN: How would you get around the data disparity?
PETER: We’ve normalized everything available, which makes it clearer what can and can’t be obtained from each partner. For example, you might want to look at something simple such as what advertisers are buying across all of the platforms by day. If the data just isn’t available from some partners, we would mark which partners don’t have that information.
That would really empower the publishers. With this significant leverage, publishers could say to their partners, “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?”
GAVIN: Right, ammunition, and a lot of transparency.
PETER: That’s one of the things publishers have been asking for. There’s not a clear dictionary out there of who supports what and what you can get from each partner. That could even be in the valuation chain for partner vetting—if they give you data you’re interested in or not. Giving them that feedback could push the industry forward.
GAVIN: Do ops professionals analyzing programmatic reporting need a more enhanced skill set?
PETER: It’s a combination of having the right tools and being familiar enough with the data to spot where you need to take action. Today, I would say people in programmatic probably spends 80 percent of their time aggregating the data and 20 percent of their time analyzing it. If you can flip those numbers around, you’ll get used to looking at the data in a consistent way, and you’ll start to see more insights.
GAVIN: What integrations are crucial for optimal programmatic reporting—the OMS in particular?
PETER: 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.
GAVIN: How have header integrations affected reporting, beyond adding complexity?
PETER: Looking at publisher data over the past 10 years, you can see where header bidding started taking off, because the reports 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.
GAVIN: Smartly evaluating demand partners requires analyzing bid rates as well as amounts. Can Ad-Juster assist in this?
PETER: Ad-Juster 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.
GAVIN: Do you think your reporting suite paves the path to true holistic yield management, particularly through the enabling of comparison of direct and indirect sales?
PETER: This is the direction we’ve been going. 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.
GAVIN: Ad-Juster has been typically associated with a single product, but you guys offer much more than that. What do you think publishers don’t understand about you?
PETER: I think a big part of it is that when we first came out with our discrepancy reconciliation solution back in 2009, there was such a desperate need for the product that we’ve really made our name on the success of that particular product. And the association of our brand has been to that. We hope that as we continue to build new products and expand our solution suite that they will have as much success as our initial product that the ecosystem begins to recognize Ad-Juster as a solutions provider with a suite of products that can help publisher operations and organizations.
GAVIN: How have you seen visualization technology improve publisher yield efforts?
PETER: The key is being able 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. You put the numbers into a graph, and all of a sudden you can see the trends—if 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 switching out.
GAVIN: So spreadsheets aren’t like The Matrix, where you can see everything in the code?
PETER: If you stare long enough, you might be able to bend a spoon.
But I don’t think spreadsheets are actually the problem. 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—it’s 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.
GAVIN: How else is Ad-Juster addressing publisher difficulties in working with finance and the whole reconciliation process?
PETER: For reconciliation, we have some OMS integrations with CRMs to push third-party billable numbers into. Beyond that, we have an entire support staff to assist operations with the data they’re seeing, and can provide insights and best practices to get through end-of-month billing.
GAVIN: What problem with viewability does Ad-Juster aim to relieve?
PETER: Viewability seems to have the same problems it had back in 2014. There are non-standardized and inconsistent ways for billing for it, from agency to agency. Ad-Juster is able to associate viewability numbers back to the original local creatives, show daily viewability thresholds and snapshots across campaigns, and provide Excel templates where we can embed the billing rules from different agencies.
GAVIN: Your Tag Scan product is pretty well known. Tags are being fingered as a culprit in latency issues and other ad hangups. How is Tag Scan keeping up with these challenges?
PETER: When we first launched Tag Scan, it was right before programmatic really started to get into the stacks of many of our publishers. You could already see the difference in ad request patterns before programmatic and afterwards. These were just passbacks and the waterfall method of doing programmatic.
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. Using TagScan, 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 of the partners in their header-bidding stack can be useful in determining the real value of that partner in their ad delivery chain.