Hari Shankar
Apr 27, 2016

Digital advertising efficiency: A reality check

How good are today's ad-tech systems, really, at tracking individuals across multiple devices and exchanges? At capping frequency? At excluding the already converted or the uninterested? Hari Shankar ponders the reality of efficiency.

Hari Shankar
Hari Shankar

In an earlier article for Campaign India, I touched upon the imperfections of today’s digital advertising and marketing measurement from an organizational ecosystem perspective. Having dwelt upon the legacy systems that mar the landscape of tracking, monitoring and measurement of digital initiatives across paid, owned and earned in today’s companies, it is time to brood a little upon another million-dollar question: How much of the tonnes of dollars launched into digital advertising are landing anywhere within the ramparts of efficiency?

Making paid digital media the fulcrum of our discussion today, let us ponder whether today’s measurement stacks, employed by the demand or supply-side, have the brawn in them to religiously track actual individuals (unduplicated) across multiple targeting environments (or at least across Facebook and Google properties)?

In the unnerving scenario where this is a distant reality, how does one avoid the debacle of ultra-spamming through uncontrolled, repeated delivery of display ads to converted audiences or departed audiences—those who aren’t interested in your product? And if we can't stop such spamming, don't the laws of diminishing returns and advertising 'blindspot' set in much earlier than they would otherwise?

Put in simpler terms, are today’s systems capable of following people around the web and across multiple screens while delivering controlled quantities of advertising to individuals, incident upon certain business rules, such as cutting off advertising to individuals who have already been exposed to the blindspot zone?

To arrive at some semblance of an answer to these questions begs for closer examination of the much-debated life of the ubiquitous, misunderstood, tiny piece of Javascript popularly known as the cookie. If you are wondering why the cookie made an appearance here, it might be pertinent to remember that all systems—first-party, second-party, third party, demand-side or supply-side—are designed to be able to identify, interpret and target audiences through the proverbial cookie.

Is there a true global frequency-capping solution?

Individual platforms like Facebook or individual DSPs like Google DBM have relevant controls that allow one to have reins on the number of exposures per individual. But when it comes to tracking that one individual across multiple ad exchanges, platforms or sites, there are nary any foolproof methods of achieving this lofty objective. Hardly any, due to the challenges involved in tagging an individual across the large number of touchpoints that he or she will traverse, utilizing multiple screens from multiple places during multiple times of the day, week or month.

Let’s pause for a moment to delve into this a bit further. Third-party ad-serving platforms use the cookie-deposition method to identify individuals who are exposed to a particular advertiser’s display ad or click on the advertiser’s display ad. But without the aid of a robust first-party DMP (data-management platform) that can store, classify, tag, interconnect and identify a designated individual in order to curtail the number of exposures served (or, for that matter, without the ability to add exclusion lists to a DSP in order to exclude a ‘converted’ group), there exists no other solution to control the wads of green that get wasted right under the nose of the oblivious advertiser. And building a first-party DMP is easier said than done in a world where leading brands are struggling with getting the basic digital measurement itself right.

The challenge posed by the third screen

Hardly any digital huddle transpires without copious discussion of mobile, the poster-child of digital marketing of the present era. But hardly anyone recognizes that today’s users have multiple cookies associated with them, in proportion to the screens owned and the vigorous transitions they make between screens. Even among those who recognised this challenge, the road to controlling frequency is dotted with many who have failed miserably in their attempts to stitch multiple cookies to one individual in order to be able to control the exposure.

Then there is a different dimension altogether that tends to escape the marketer’s consideration: the colossal cookie-inoculated iOS user base, owing to the default setting in their iPhones. This is a gaping chasm in the cross-channel attribution and measurement movement.

And then there is an entire gamut of other challenges—viewability, ad blockers, cookie expirations, mobile-device upgrade cycles and dark browsing (like Tor)—that pose intimidating challenges toward the creation of a state of paid advertising that comes anywhere close to providing robust measurement and ensuring maximum bang for the advertiser’s buck.

Is there a light at the end of the tunnel?

There are many parallels between a cookie and a bug. When the bug is detected, it is busted. A bug cannot exist in a bug-inoculated space, or it can expire within a hostile environment. And this indeed is the chink in the cookie’s armour, which needs to be eradicated.

This issue has become the Achilles’ heel of the industry when it comes to maximizing digital marketing impact and solving the attribution question. The only respite is that there are some technologies, in their infancy at present, that hold strong promise toward alleviating this perpetual affliction. But I will save that for another time.

Hari Shankar is managing director, Ecselis Asia, and head of paid digital strategy with Havas Media Group


Campaign Asia

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