Alex Steer

Advertising effectiveness, analytics and strategy / about

Lift Points: A currency for effective impressions

504 words

This is a quick follow-up to an equally quick Twitter conversation with Faris Yakob about his interesting piece in the Guardian on the currency of online impressions. The piece's main argument is that the assumption that the impression is the currency of attention is faulty:

In order to buy and sell something, we needed a currency. We settled on the impression: one person being exposed to something once. Attention is a complex and analogue aspect of consciousness – its most directed form – which makes it a small part of the most complex system in the known universe. The complex, fundamentally analogue, nature of attention, which has many different facets, is converted into the simple, inherently binary, impression.

The piece is both mostly fair and a bit unfair. There are better ways of measuring attention; they are granular and specific to specific ad exposures; but they're not yet a properly tradable currency for online media.

So what are they? And what should the currency for attention be?

They don't really have a name yet, but they do exist, we're working with them, and my shorthand for them would be Lift Points.

Here's how it works. Using log-level ad-server or site analytics data (the same thing that gives us impressions), it's possible to identify the number, order and nature of exposures an individual has had to online advertising during a time period. This is particularly true if you can deduplicate across devices, tie cookies/device IDs back to real people, and so on. So far, so obvious.

Using sufficiently large behavioural tracking + attitudinal research panels (e.g. Millward Brown's Ignite network), it's possible to tie these granular impressions to well-controlled brand tracking surveys.

Briefly, this means you can effectively regress the test-vs-control uplift in brand awareness/equity/whatever to specific patterns of exposure - creative, site, placement, order, recency, frequency, and so on. By treating this like an attribution model you can assign percentage points of brand uplift to specific factors in the advertising mix. This can be done at a very large scale, and very quickly - and you can use it to isolate the contribution of any factor and give its typical contribution to uplift. And those are Lift Points.

The most obvious - and most easily tradable - would be Awareness Lift Points - the average incremental points of brand awareness delivered by an ad / placement / etc per single exposure. Because ads that are unseen have no impact on awareness, like any good attribution it controls for viewability automatically.

Is it immediately tradable the way impressions are? No, but if used it would quickly build up a tradable market value the way that media owner ratecards or viewability scores do - based on the typical delivery of uplift per exposure. It's also challenging to the economics of the research industry as it means a vast number of very small and fast-turnaround post-exposure test-and-control surveys, but some providers are already moving in this direction.

# Alex Steer (11/08/2015)


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