Over the last several years, publisher monetization has grown increasingly complex — with more moving parts interacting in different ways and at a faster rate than ever before.
To get the most out of their revenue streams, publishers need to be able to continuously scan their datascapes — from top-to-bottom and end-to-end — comparing real time figures to expected values; going beyond simplistic rules and arbitrary inferences to quickly surface meaningful problems and opportunities.
For Publishers, Actionable Analytics Is an Uphill Battle
Given the enormous scale, speed, and complexity of the transactions that underpin publisher monetization, maintaining the type of oversight and insight needed is a constant struggle.
And it's made all the more difficult by a number of complicating factors:
- Monetization teams are already undermanned
- The skills required are changing quickly — leading to a shortage of available players
- The game itself has gotten bigger, faster, and more complex
- Surrounding technologies are evolving at a rapid pace, while supporting technologies have stagnated
The pandemic has only exacerbated the situation — at once shifting consumer preferences and advertiser expectations. If publishers were already dealing with a hard-to-hit target, now that same target is on the move.
So where does that leave publishers? Not in a great place, to be honest.
Of the publishers wielding devoted BI and reporting tools, almost all (97%) are using mass-market technologies. Since those systems are built for other industries, data environments, and use cases, they cannot deliver a full-service experience or actionable analytics.
This is the result of 6 key technological limitations that combine to dramatically undercut the value of standard BI reporting and anomaly detection. To wit, such solutions cannot...
- Contextualize data relationships.
- Tell when a change is trivial or significant.
- Translate mathematic insights into business imperatives.
- Complement highly specialized workflows.
- Trace data anomalies to their root cause(s).
- Help guide smart interventions.
At best, mass-market BI tools will flag issues that they cannot explain. And that's on the far end of the spectrum — the 7.4% that make use of such tools.
For the majority of the industry, data monitoring is still a matter of manual reviews. When help is inevitably needed, most publishers look to level up with the incorporation of automated, rule-based reviews.
Unfortunately, these solution don’t really monitor anything so much as they set up a framework of tripwire alarms. These alarms sound when triggered, but based on predefined interactions rather than situational observation or environmental awareness. Just like tripwires, they can easily be circumvented and, just like a tripwires, they tend to produce more false alarms than useful warnings.
In fact, AdOps teams using rule-based alerting systems actually spend 40% more time on their data than teams relying on purely manual reviews!
Case in point: 11% admit to spending more than 6 hours working their data every day!
But that's not even the main problem.
The main problem is that even with so much time and energy poured into managing and mining the data, issues still aren't being found and fixed quickly enough. That's why 20% of publishers say they have no reliable process in place to find and fix issues.
Those issues translate to revenue losses. Based on an anonymized review of oolo system data from 16 different publishers, we estimate that, on average, 7% of total ad revenue potential is forfeited to slow-to-detect setup, delivery, and performance issues.
Smarter Tooling Begets Better Monitoring
To survive and thrive through this period of sustained disruption, publishers need to be able to get eyes on and insights from their data in near real-time — without sacrificing any of the depth, accuracy, or actionability of their analytics.
That's a far cry from today when it can take hours just to review top-line figures and KPIs for all relevant metrics and dimensions. Which is why 81% of publishers acknowledge that data monitoring will not improve without new and more actionable analytics technologies.
Of course, technology for technology's sake will get you nowhere.
Publishers should be discriminating with their technology investments and seek out solutions made specifically to meet their unique complexities. Regardless of the strength of the technology, a system's value will always be limited by its understanding of your business dependencies, data relationships, and operational controls.
Even when all the pieces seem to fit into place — the technology is strong and it's been purpose-made for the right department and use cases — publishers should establish proof of value before getting too deep into any augmented analytics project.
Rapid value demonstration is the standard we hold ourselves to at oolo and it's that high watermark that makes our solution stand out from the crowd. At oolo, our approach to monetization is rooted in data enablement — helping publishers restore confidence, remove hassle, and raise revenue.