In the current digital media measurement paradigm a premium continues to be placed on the ability of a provider to get credit for an online conversion rather than the contribution an advertising impression makes to business success. We will never grow the size of the proverbial digital advertising “pie” until we learn to value media and move above and beyond last-action attribution.
Consider that perhaps the largest objection to moving sizeable budgets into the online advertising arena from television is the ability to reach large audiences at scale. The argument is that television effectively reaches everyone in a targeted demographic group with effective frequency. The proponents of this argument would claim that the web does not, and those who it does reach are harder to find with an optimal balance of reach and frequency. Although TV is not foolproof in this regard, it’s considered “easier” than digital given fragmentation of publishers and lack of standardized and agreed-upon measurement.
The argument of lack of reach and frequency rings hollow to digital practitioners because we know that the reach of the digital realm (even pre-mobile) allows us to target millions of ad impressions per second. And while it is unquestionably true that not all those impressions are of equal advertising value, that is a subject of willingness to pay or valuation and not reach. We also know that the addressable vehicles of the digital ecosystem actually provide for much more accountable frequency metrics than television. (Please note that I am ignoring the creative differences between the channels for the simplicity of the argument.)
Thus my thesis; the flawed attribution models and rhetoric of ROI espoused by the digerati of the world to prove our worth have promoted an unwinnable agenda. The rhetoric of advertising ROI in the digital landscape is contrary to the definition applied to the “analog” channels: the very definition of ROI may mean something that is inconsistent between marketer and financial analyst. This example from Investopedia on the matter is enlightening: “…For example, a marketer may compare two different products by dividing the gross profit that each product has generated by its respective marketing expenses. A financial analyst, however, may compare the same two products using an entirely different ROI calculation, perhaps by dividing the net income of an investment by the total value of all resources that have been employed to make and sell the product…” And in my experience I have yet to see advertising ROI ever calculated by the incremental and ongoing contribution to a business’ cash flow or profitability that would not otherwise have occurred for a given incremental amount of spending on advertising.
Large advertisers tend to use television typically because they require mass reach to achieve their corporate goals, which gravitate toward massive sales volumes dependent on high awareness, preference, loyalty, and ultimately conversion. And thus far, only television has accepted mass reach metrics – consider the $80-plus billion in sales that P&G and Unilever did last year (individually). Imagine attempting to gain acceptance as a digital inventory provider – defined loosely as any entity that is attempting to make a profit by providing impressions to an advertiser (e.g., publisher, ad network, DSP) – if you only allowed yourself to be measured by reach and frequency against an agreed-upon segment or demographic. How much share-of-wallet would you win?
When studying the impact of a digital advertising impression for atomic structure (those items that make up an advertising impression such as domain, time, OS, inclusion in an identified audience segment, etc.) across multiple online attribution models such as click, last action, equal weight, and decay, we can determine that the relative worth of the individual sub-atomic element varies wildly.
By way of example, an impression promoting a CPG product measured in a click attribution model places a disproportionate value on a set of particular domains, while that same impression measured in an equal weight model places the value emphasis on a broad contextual category that differs from the category of the click domains. That same CPG product measured in a “decay to exposure” model places value in a particular audience segment that is only loosely associated with the broad contextual category of the equal weight model.
It’s important to note that all of these models measure the same digital end goal of getting credit for some sort of digital conversion measured by the holy digital grail of a pixel fire. This suggests that the only thing of importance in the digital advertising ecosystem is understanding how the score is kept and not how you play or value the game. If we want digital marketing to succeed in capturing a larger piece of the “pie,” we need to rethink the ability to take credit and instead focus on the ability to create value.
Image on home page via Shutterstock.
Advertisers are more concerned than ever about brand safety, and one of the primary ways they're trying to keep their ads from appearing in unfriendly places is through whitelisting. But as more and more brands turn to whitelisting, some are talking about the impact this will have.
We all know that Facebook is a viable source of huge amounts of mobile traffic with relatively cheap CPCs). It’s too good an opportunity to ignore in today’s digital landscape - even if your mobile landing-page experience isn’t up to snuff.
For years, advertisers have tolerated a big elephant in the room: the fact that their digital ads aren't always appearing where they would want them to.
Deep learning tools are the next major area of AI-based research, and it will spark a wave of future innovation in every industry – bringing a new era of marketing which both advertisers and end-users will benefit from.