When you look back at the last 10 years, due to the lack of standardized metric advertisers (not ad agencies) as well as quality content publishers end up losing out. Yes, it might be shocking – the parties most interested in the process and at the same time should be most influential and cooperating. But for some reason, it has never happen. Advertisers spent billions into campaigns which has rarely been seen by human viewers or only part of the ad has been seen. In the race for more page impressions quality content publishers were punished by falling prices and in consequence – falling content quality to satisfy growing page views (PV) measured audience.
Only now, the process related to ad viewability and engagement has started. It should never happen, as ability to measure user attention, engagement and any other metric are much better and precise at digital content than the standards used by TV’s - which still run on Gross Rating Point build on statistical audience sample with people meters.
The world we knew was set on PV, unique users (UU) or sessions. Despite of the fact that we all knew that those metrics were giving us completely false and misleading picture:
- Page Views – all mistaken clicks, all impressions that were bounced even before the page content was loaded (due to crazy overload of trackers, ads etc.), all bots - that was significant part of that metric.
- Unique Users – someone was really brave or blind to call it unique. If you have 3 devices, you will be recognized as 3 unique. If you are cleaning your devices from cookies, you might be recognized even as 6 or 9 unique. So, how many real unique users we have? Yes, we have more advanced tools like …but with ad blockers, still it is very problematic.
New approach to measure content performance
Nowadays with much better analytic tools that are able to collect and process huge streams of data in real time for extremely rational cost fraction, publishers and advertisers should fight for much better standards and constantly adjust them with changing environment. That would really give strong arguments to justify the higher CPM for well performed content or ad.
But the most important thing is that there's no single universal metric.
Different measures are important for advertisers, different for editorial, product or sales teams. Let's dig even deeper in the following sections.
What is the right metric for advertiser?
It depends on many things like campaign goals, channels, form of ad. For instance, a simple display ad we can measure by visibility and time viewed. A sponsored article that aims to spread brand we should measure by percent of consumption, user interactions, time spent. But similar article that should drive sales has to measure by conversions.
What is the right metric for newsroom?
Many current solutions measures in fact not content but our website or mobile app performance showing how many people an URL has attracted.
What's is extremely important is to distinguish content and platform performance, and measure real consumption of each piece of content we produce, let it be text articles, article leads, video, audio podcasts, or even creatives we put on our platforms. We should have in mind that many kinds of content is put often on the same page so we need to build metrics that measures it in the right way.
But there's also the other way of looking at content: we should measure what's maximizes our gain. And the ultimate goal is to reach and keep the most loyal audience, because it has the highest LTV (lifetime value).
So, what's the measure? Again - it depends! We suggest to create kind of engagement metrics that combines important factors for our goal. For an entertainment content we should focus more on social sharing, virality, total reach. For deep reporting piece way important is to measure if readers fully consume it and how often they return.
You might feel concerned after reading this article, because we did not suggest any specific, simple solution. And we will not do it. Our strong believe is that publishers must collect their first party data (it means big data), rethink and define their own metrics combined from user interactions. The common baseline for this task is definitions of goals for each part of operations and a capable platform that would allow to track these metrics.