March 30, 2017
A major fallacy publishers still have is the notion of “quality supply” or “premium inventory”. I’ll explain the idea behind the argument.
Introduction. The fallacy of quality supply lies in publishers assuming the quality of certain placement (say, a certain website) is constant, whereas in reality it varies according to the response which, in turn, is a function of the customer and the ad. Both the customer and the ad are running indices, meaning that they constantly change. The job of a programmatic platform is to match the right ads with right customers in the right placements. This is a dynamic problem, where “quality” of a given placement can be defined at the time of match, not prior to it.
Re-defining quality. The term “quality” should in fact be re-defined as relevance — a high-quality quality ad is relevant to customers at a given time (of match), and vice versa. In this equation, the ad placement does not hold any inherent value but its value is always determined in a unique match between the customer, ad and placement. It follows that the ad itself needs to be relevant to the customer, irrespective to the placement. It is not known which interaction effect is stronger, ad + customer, or placement + customer, but it is commonly assumed that the placement has a moderating effect on the quality of the ad as perceived by the customer.
The value of ad space is dynamic. The idea of publishers defining quality distribution a priori is old-fashioned. It stems from the idea that publishers should rank and define the value of their advertising space. That is not compatible with platform logic, in which any particular placement can be of high or low quality (or anywhere between the extremes). In fact, the same placement can simultaneously be both high- and low quality, because its value depends on the advertiser and the customer which, as stated, fluctuate.
Customers care about ad content. To understand this point, quality should be understood from the point of the customer. It can be plausibly argue that customers are interested in ads (if at all) due to their content, not their context. If an ad says I get a promotion on item x which I like, I’m interested. This interest takes place whether the ad was placed on website A or website B. Thus, it is not logical to assume that the placement itself would have a substantial impact on ad performance.
Conclusion. To sum up, there is no value in an ad placement per se, but the value realizes if (and only if) relevance is met. Under this argument, the notion of “premium ad space” is inaccurate and in fact detrimental by its implications to the development of the programmatic ad industry. If ad space is priced according to inaccurate notions, it is not likely to match its market value and, given that the advertisers have choice, they will not continue buying such ad inventory. Higher relevance leads to higher performance which leads to advertiser satisfaction and a higher probability of repurchase of that media. Any predetermined notion of “quality supply” is not relevant in this chain.
Recommendations. Instead of maintaining the false dichotomy of “premium” and “remnant” inventory, publishers should strive to maximize relevance in match-making auctions at any means necessary. For this purpose, they should demand higher quality and variety of ads from the advertiser. Successful match-making depends on quality and variety at both sides of the two-sided market. Generally, when prices are set according to supply and demand, more economic activity takes place – there is no reason to expect otherwise in the advertising market. Publishers should therefore stop labeling their inventory as “quality” or “premium” and instead let markets decide whether it is so. Indeed, in programmatic advertising the so-called remnant inventory can outperform what publishers initially would perceive as superior placements.
March 30, 2017
Currently, there is very strong hype involved with programmatic buying. Corporations are increasing their investments on programmatic advertising and publishers are developing their own technologies to provide better targeting information for demand-side platforms.
But all is not well in the kingdom. Display advertising still faces fundamental problems which are, in my opinion, more critical to advertising performance than more granular targeting.
Problems of display advertising
In particular, there are four major problems:
Banner blindness is a classical problem, stating that banner ads are not cognitively processed but left either consciously or unconsciously unprocessed by people exposed to them (Benway & Lane, 1998). This is a form of automatic behavior ignoring ads and focusing on primary task, i.e. processing website content. Various solutions have been proposed in the industry, including native advertising which “blends in” with the content, and moving to calculating only viewable impressions which would guarantee people actually see the banner ads they are exposed to. The problem with the former is confounding sponsored and organic content, while the problem with the latter is that seeing is not equivalent to processing (hence banner blindness).
Ad blocking has been in tremendous rise lately (Priori Data, 2016). Consumers across the world are rejecting ads, both in desktop and mobile. Partly, this is related to ad clutter referring to high ads-to-content ratio in the websites. The proliferation of ad blocking should be interpreted as an alarming signal by the media houses. Instead, many of them seem to take no notice, keeping their website layout and ads-to-content ratio high. If there are no major improvements in user satisfaction, visible in reducing ads-to-content ratio, demanding higher quality ads from advertisers and making changes to website layouts, ad blocking is likely to continue despite pleas of publishers. Less advertising, of better quality, is needed to trigger a positive sentiment towards online advertising.
Finally, post-click behavior of traffic originating from display ads tends to be unsatisfactory. Bounce rates are exceptionally high (80-90% in some cases), direct ROI is orders of magnitude lower than search, and alarmingly enough display often seems weak also when examining the entire conversion path. Consequently, using direct ROI as a measure for success in display advertising yields sub-par results. Unfortunately, direct ROI is used more and more by performance-oriented advertisers.
Brand advertisers, who seek no direct returns in their online ad spend (think Coca-Cola), may continue using reach metrics. Thus, focusing on these advertisers, which still make a large share of the advertising market, would seem like a good strategy for publishers. Moreover, combating click-fraud and other invalid click forms is essential. If shortsightedly optimizing for revenue at all means – including allowing bots to participate in RTB auctions – media houses and DSPs are shooting themselves in the foot.
But let’s talk about why these problems have not been addressed, at least not fundamentally by the majority of media companies. There are a few reasons for that.
First, the organizational incentives are geared towards sales. The companies follow a media business model which principally means: the more ads you sell, the better. This equation does not consider user satisfaction or quality of ads you’re showing, only their number and the revenue originating from them.
At a more abstract level, the media houses face an optimization conundrum:
Maximizing number of ads (shown on the website) and price of ads also maximizes ad revenue. However, it is not maximizing user satisfaction. User satisfaction and performance are in parentheses because they are not considered in the media company’s optimization function, although they should be because there is a feedback mechanism from user satisfaction to ad performance and from ad performance to price of ads.
Seemingly, many media companies are maximizing revenue in the short-term through power-selling strategy. However, they should be maximizing revenue in the long-term and that cannot take place without considering user satisfaction from consumer perspective and ad performance from advertiser’s perspective. Power selling actually hurts their interests in the long-term through the feedback mechanism.
How to dismantle this conundrum? First, the media companies should obviously consider both user satisfaction and ad performance. The former is done by actively studying the satisfaction of their users in terms of ad exposure. The latter is done by actively asking or otherwise acquiring data from advertisers on campaign performance. I, as a marketing manager, rarely found media sales people interested in my campaign performance – they just wanted a quick sell. Even better than asking would be to find a way to directly dip into campaign performance, e.g. by gaining access to advertiser’s analytics.
Second, media companies should consider the dynamics between the variables they are working with. For example,
It can be hypothesized, for example, that a higher ad performance leads to a higher price of ads as ads become more valuable to advertisers. If in addition ad performance increases as the number of ads decreases, there is a clear signal to decrease the number of ads on the website. Some of these hypotheses can be tested through controlled experiments.
Third, media companies should re-align incentives from power-selling to value-based selling. They should not want to “fill the slots” at any means, but only fill the slots with good advertising that performs well for the advertiser. Achieving such a goal may require a stronger collaboration with advertisers, including sharing data with them and intervening in their production processes to deliver such advertising which does not annoy end users and based on prior data is likely to perform well.
In conclusion, there is a bottleneck at advertising-customer interface. Red herring effect takes place when we are focusing on a secondary issue – in the context of digital marketing we have to acknowledge that there is no intrinsic value in impressions or programmatic advertising technology, if the baseline results remain low. Ultimately, advertisers face a choice of abundance with channels both online and offline. And although they are momentarily pushing for large programmatic investments, if the results don’t follow they are likely to shift budget allocations into a different sort of equilibrium in the long-run, once again under-weighing display advertising.
Personally, I believe the media industry is too slow to react and display advertising will lose budget share in the coming years especially against social media advertising and search advertising, but also against some traditional channels such as television.
March 29, 2017
This is a short post taking a stance on programmatic ad platforms. It’s based on one single premise:
Digital convergence will lead into a situation where all ad spend, not only digital, will be managed through self-service, open ad platforms that operate based on auction principles
There are several reasons as to why this is not yet a reality; some of them relate to lack of technological competence by traditional media houses, some to their willingness to “protect” premium pricing (this protection has led to shrinking business and keeps doing so until they open up to the free market pricing), and a host of other factors (I’m actually currently engaged in a research project studying this phenomenon).
Anyway, digital convergence means we’ll end up running campaigns through one or possibly a few ad platforms that all operate according to the same basic principles. They will resemble a lot like AdWords, because AdWords has been and still is the best advertising platform ever created. Why self-service is critical is due to the necessity of eliminating transaction costs in the selling process – we don’t in most cases need media sales people to operate these platforms. Because we don’t need them, we won’t need to pay their wages and this efficiency gain can be shifted to the prices.
The platforms will be open, meaning that there are no minimum media buys – just like in Google and Facebook, you can start with 5 $ if you want (try doing that now with your local TV media sales person). Regarding the pricing, it’s determined via ad auction, just like in Google and Facebook nowadays. The price levels will drop, but lowered barrier of access will increase liquidity and therefore fill seats more efficiently than in human-based bargaining. At least initially I expect some flux in these determinants — media houses will want to incorporate minimum pricing, but I predict it will go away in time as they realize the value of free market.
If Google was smart, it would develop programmatic ad platform for TV networks, or even integrate that with AdWords. The same applies actually to all media verticals: radio, print… Their potential demise will be this Alphabet business. All new ideas they’ve had have failed commercially, and to focus on producing more failed ideas leads unsurprisingly to more failure. Their luck, or skill however you want to take it, has been in understanding the platform business.
Just like Microsoft, Google must have people who understand about the platform business.
They’ve done a really good job with vertical integration, mainly with Android and Chrome. These support the core business model. Page’s fantasy land ideas really don’t. Well, from this point of view separating the Alphabet from the core actually makes sense, as long as the focus is kept on search and advertising.
So, programmatic ad platforms have the potential to disrupt Google, since search still dwarfs in comparison to TV + other offline media spend. And in the light of Google’s supposed understanding of platform dynamics, it’s surprising they’re not taking a stronger stance in bringing programmatic to the masses – and by masses, I mean offline media where the real money is. Google might be satisficing, and that’s a road to doom.
Dr. Joni Salminen holds a PhD in marketing from the Turku School of Economics. His research interests relate to startups, platforms, and digital marketing.
Contact email: [email protected]