The single most important aspect of digital marketing in today’s world is analytics. As a marketer, having data that shows how your campaign performed is a critical requirement that will inform decisions around your advertising for the foreseeable future.
But what if the data is in itself ineffective? Many campaigns generate lots of data, but little insight; they concentrate on “delivery” data. But whilst knowing how many impressions a campaign received is important, brands are not running campaigns just so lots of people see them, they are looking for the knock-on effect – are people then considering or intending to buy their product as a result of seeing the ad?
Some publishers do go further, providing a measurement of the brand lift generated by some campaigns on their sites, thereby moving closer to knowing their true effectiveness. But here again, we can run into challenges.
Each publisher who chooses to measure a campaign this way is doing so for noble reasons, seeking to understand and optimize effectiveness. They also get to present themselves in the most positive way, focusing on the best numbers that champion what they do. But whilst that may seem a good short-term strategy for that particular campaign and publisher, in reality they are not helping anyone, least of all themselves.
This ad hoc approach is expensive and time-consuming and often is not transparent, especially if the measurement is carried out via an in-house solution. Put simply, that is akin to marking their own homework.
Meanwhile, the marketer is potentially receiving a number of different reports and spreadsheets from the different publishers on their schedule and has to somehow piece them together to formulate a holistic picture of how the “premium publishers” part of their campaign have delivered campaign effect.
It is easy to understand why publishers might fall back on such tried and tested methods – they are simply using data that is readily available to them and operating the same measurement process they have always relied on. But that does little to benefit the marketer.
Different methods of monitoring ad effectiveness means marketers may be seeing a whole host of very impressive looking statistics from different sources, but they are not seeing any like-for-like measurement and so, cannot draw truly effective conclusions that will inform the next stage of their advertising.
Which is why we need to move away from one-dimensional ‘data’ and start talking about ‘metrics’. Metrics offer a universal language of performance; a consistent approach across publishers and markets that enable the comparability that is essential for a real understanding of how an ad campaign has performed.
But to avoid this disconnect there needs to be a common set of metrics that become universal – across publishers and markets – so everyone, from single market brands and publishers, to international businesses, can gain a consistent, holistic view of their campaign performance.
In order to do this, we must first define a “metric”. To me a metric is something that is uniform (i.e. the same language is used consistently by everyone); is simple (i.e. it cannot be too complicated to understand or deploy); and is widespread (i.e. it is used across different publishers and different marketplaces).
Many companies operate globally, so in an ideal world they will be talking the same language around metrics, regardless of where they’re physically based. That’s when you start to generate data that is invaluable, enabling the buy side to draw comparisons with other publishers in the same space, and enabling publishers to explore how they’re performing in different areas of the world, but all via the same simple, easily understood set of numbers.
A further advantage of using a consistent approach to metrics is that measurement companies, such as ours, can add each piece of data captured to an ever-growing set of benchmarks. This enables us to share anonymised data showing individual publishers how their individual campaigns performed against a global set of benchmarks, highlighting areas of over- and under-performance. But you can’t build such benchmarks if you don’t have a consistent way of measurement.
To me, the really exciting bit about using global metrics is the ability to operate with more effectiveness at scale and plan more effectively for the future. A big publisher running across various different markets might discover their campaigns are working much stronger in Country A than Country B, and with that knowledge they can start to explore what might be contributing to that success and how they can export some of that learning into their other markets.
And in turn, they can pass on their collective understanding to help their advertisers generate a more positive return on their future campaigns. By building a bank of knowledge around what works and what doesn’t, they can help their customers tweak their activity and also go on to attract new customers with the promise of this accessible, uniform data and insight.
Running comparable metrics at scale, tapping into benchmarks and beginning to build something more than a one-off campaign-based spreadsheet is advantageous on every level, to every party, publishers, agencies, and marketers alike. Perhaps it’s time to stop talking about data and to start talking about metrics.
[To share your insights with us, please write to sghosh@martechseries.com]
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