March 30, 2017
Answer: It kinda is.
“Premium publishers” and “premium ad space” — these are often heard terms in programmatic advertising. But they are also dangerously fallacious ideas.
I’ll give three reasons why:
First, publishers define what is “premium” a priori (before results) which is not the right sequence to do it (a priori problem). The value of ad space — or the status, premium or not — should be determined a posteriori, or after the fact. Anything will risk biases due to guess-work.
Second, what is “premium” (i.e., works well) for advertiser A might be different for advertiser B, but the same ad space is always “premium” or not (uniformity problem). The value of ad space should be determined based on its value to the advertiser, which is not a uniform distribution.
Third, fixing a higher price for “premium” inventory skews the market – rational advertisers won’t pay irrational premiums and the publisher ends up losing revenue instead of gaining “premium” price (equilibrium problem). This is the exact opposite outcome the publisher hoped for, and arises from imbalance of supply and demand.
I defined premium as ad space that works well in regards to the advertiser’s objectives. Other definitions also exist, e.g. Münstermann and Würtenberg (2015) who argue the distinctive trait between premium and non-premium media is the degree of its editorial professionalism, so that amateur websites would be less valuable. In many cases, this is an incorrect classifier from the advertiser’s perspective — e.g., placing an ad on a blogger’s website (influencer marketing) can fairly easily produce higher rents than placing it alongside “professional” content. The degree of professionalism of the content is not a major cue for the consumers, and therefore one should define “premium” from the advertiser’s point of view — as a placement that works.
The only reason, I suspect, premium inventory is still alive is due to the practice of private deals where advertisers are more interested in volume than performance – these advertisers are more informed by assumptions than data. Most likely as the buyers’ level of sophistication increases, they become more inclined to market-based pricing which has a much closer association with performance than private deals.
March 30, 2017
Two brands colliding.
Hm, I’m thinking (therefore, I am a digital marketer). The classical advertising question has been:
How to measure the impact of advertising on a brand?
And then the answer has been “oh, you can’t”, or “it’s difficult”, or something along those lines. But, they say, it is there! The marketers’ argument for poor direct performance has traditionally been that there is a lift in brand awareness or attitude which are sometimes measured by conducting cumbersome surveys.
But actually, aren’t the aforementioned attributes just predictors of purchase? I mean, they should result in higher probability of purchase, right? Given that people know the brand and like the brand, they are more likely to purchase it.
If so, the impact metric *is* indeed always sales — it’s only a question of choosing the period of examination. If all advertising impacts lead to sales, then sales is the metric even when we talk of brand advertising.
According to the previous logic, it would seem measuring advertising impact by sales is always correct, but because of carryover effects (latent effects) the problem can be reformulated into:
What time period should we use to measure advertising impact?
And forget about measurement of brand impact. It’s not a question of impact on “soft” issues but impact on revenue. The influence mechanism itself might be soft, but it always needs to materialize as hard, cold cash. The more tricky questions are determining the correct examination period for campaigns which requires fitting it to the length of purchase process, and keeping the analytics trail alive for at least that time period.
Conclusions and discussion
If carryover effects occur, how can we determine the correct time frame for drawing conclusions on advertising impact?
…I have to say, though, that measuring brand sentiment can’t be wrong. It can help understand why people like/dislike the brand, and therefore provide improvement ideas and a description of perceived brand attributes, information which is helpful for both product development and marketing.
But the ultimate metric for assessing advertising impact should always be sales.
March 30, 2017
From its high point, the sheep can see far.
In Finland, and maybe elsewhere in the world as well, media agencies used to reside inside advertising agencies, back in the 1970-80s. Then they were separated from one another in the 1990s, so that advertising agencies do creative planning and media companies buy ad space in the media. Along with this process, heavy international integration took place and currently both the media and advertising agency markets are dominated by a handful of global players, such as Ogilvy, Dentsu, Havas, WPP, etc.
This article discusses that change and argues for re-convergence of media and advertising agencies. I call this the new paradigm (paradigm = a dominant mindset and way of doing things).
The old paradigm
The current advertising paradigm consists of two features:
1) Advertising = creative + media
2) Creative planning –> media buying –> campaigning
In this paradigm, advertising is seen as rigid, inflexible, and one-off game where you create one advertising concept and run it, regardless of customer response. You are making a one sizable bet, and that’s it. To reduce the risk of failure, creative agencies use tons of time to “make sure they get it right”. Sometimes they use advertising pre-testing, but the process is predominantly driven by intuition, or black-box creativity.
Overall, that is an old-fashioned paradigm, for which reason I believe we need a new paradigm.
Towards the new paradigm
The new advertising paradigm looks like this:
1) Advertising = creative + media + optimization
2) Creative planning –> media trials –> creative planning –> …
In that, advertising in seen as fluid, flexible, and consecutive game where you have many trials to succeed. The creative process feeds from consumer response, and in turn media buying is adjusted based on the results of each unique creative concept.
So what is the difference?
In the old paradigm, we would spend three months planning and create one “killer concept” which according to our intuition/experience is what people want to see. In the new paradigm, we spend five minutes to create a dozen concepts and let customers (data) tell us what people want to see. Essentially, we relinquish the idea that it is possible to produce a “perfect ad”, in particular without customer feedback, and instead rely on a method that gets us closer to perfection, albeit never reaching it.
The new paradigm is manifested in a continuous, iterative cycle. Campaigns never end, but are infinite — as we learn more about customers, budget spend may increase in function of time, but essentially optimization is never done. The campaign has no end, unlike in the old paradigm where people would stop marketing a product even if the demand for that product would not disappear.
You might notice that the paradigm may not be compatible of old-fashioned “shark fin” marketing, but views marketing as continuous optimization. In fact, the concept of campaign is replaced by the concept of optimization.
Let me elaborate this thought. Look at the picture (source: Jesper Åström) – it illustrates the problem of campaign-based (shark-fin) marketing. You put in money, but as soon you stop investing, your popularity drops.
Now consider an alternative, where you constantly invest in marketing and not in heavy spikes (campaigns) but gradually by altering your message and targeting (optimization). You get results more like this:
Although seasonality, which is a natural consequence of the business cycle, does not fade away, the baseline results increase in time.
Instead of being fixed, budget allocations live according to the seasonal business cycles — perhaps anticipating the demand fluctuations. The timing should also consider the carryover effect.
I suspect media agencies and advertising will converge once again, or at least the media-buying and creative planning functions will reside in the same organization. This is already the way many young digital marketing agencies are operating since their birth. Designers and optimizers (ad buyers) work side-by-side, the former giving instructions to the latter on what type of design concepts work, not based on intuition as old-paradigm Art Directors (AD) would do, but based on real-time customer response.
Most importantly, tearing down silos will benefit the clients. Doing creative work and optimization in tandem is a natural way of working — the creative concept should no longer be detached from reality, and we should not think of advertising work as a factory line where ads move from one production line to another, but instead as some sort of co-creation through which we are able to mitigate advertising waste and produce better results for advertising clients.
March 30, 2017
I’ve long been skeptical of display advertising. At least my students know this, since ever year I start the digital marketing course by giving a lecture on why display sucks (and why inbound / search-engine marketing performs much better).
But this post is not about the many pitfalls of display. Rather, it’s outlining three arguments as to why I nowadays prefer social advertising, epitomized by Facebook Ads, over display advertising. Without further ado, here are the reasons why social rocks at the moment.
It’s commonly known Facebook advertising is cheap in comparison to many advertising channels, when measured by CPM or cost per individual reached. Display can be even cheaper, so isn’t that better? No, absolutely not. Reach or impressions are completely fallacious metrics — their business value approaches zero. Orders of magnitude more important is the quality of contacts.
The quality of Facebook traffic, when looking at post-click behavior, tends to be better than the quality of display traffic. Even when media companies speak of “premium inventory”, the results are weak. People just don’t like banner ads. The people who click them, if they are people and not bots to begin with, often exit the site instantly without clicking further.
People actually interact with social ads. They pose questions, like them and even share them to their friends. Share advertisements? OMG, but they really do. That represents an overkill opportunity for a brand to interact with its customer base, and systematically gather feedback and customer insight. This is simply not possible with any other form of advertising, display including.
Display ads, albeit using rich media executions, are completely static and dead when it comes to social interaction. Whereas social advertising creates an opportunity to gather social proof and actual word-of-mouth, even viral diffusion, in the one and same advertising platform, display advertising is completely lacking the social dimension.
Social advertising, specifically Facebook gives a great flexibility in combining text, images and video. Typically, a banner ad can only fit a brief slogan (“Just do it.”), whereas a social advertisement can include many sentences of text, a compelling picture and even link description that together give the advertisers the ability to communicate the whole story of the company or its offering in one advertisement.
But isn’t that boring? No, you can craft it in a compelling way – the huge advantage is that people don’t even need to click to learn the most essential. If the goal of advertising is to inform about offerings, social advertising is among the most efficient ways to actually do it.
That’s it. I don’t see a way for display advertising to overcome these advantages of social advertising. Notice that I didn’t mention the superior targeting criteria — this is because display is quickly catching up to Facebook in that respect. It just won’t be enough.
March 30, 2017
I’ve dedicated plenty of time for studying and coaching startups. But why do I care? Not only care, but be passionate about them, enough to say I love startups.
I got to think about that, and here are the results of that quick reflection.
1. Startups are about technology
Novelty, innovation, progress… call it what you want, but there is something endlessly exciting about startups. It’s to see them take something which exists and turn it into something completely new. This sounds melodramatic but at its core it’s close to creation, close to being a god. Not meaning to blaspheme, but honor the impact startups have on people’s lives. Of course there is a lot of hype and failure associated with this progress because the process of creation is not linear, but nevertheless the renewal of daily lives is to a great extent driven by startup innovations. We can see them all around us, never stopping to be amazed of what we humans can accomplish.
2. Startups have rebel spirit
They are the anti-thesis of corporations. As much as I love startups, as much I hate (bureaucratic) corporations. Startups are about freedom, creativity and independence — and about power to execute. Some other small organizations share these traits, which is why working with small tends to be easier than working with the big. Even big companies create innovative stuff from time to time, but I’ve seen plenty of cases where new ideas are strangled to death by internal politics. Many large organizations don’t want to change — truly — but they just pay lip service to change and new management fads. They also don’t need to change, because in the short-term the world actually remains quite stable. The change in any given industry does not come over-night which gives corporations plenty of time to adapt (i.e., they can hire and fire many CEOs until they have gradually shifted their focus to something that works).
The rebel spirit of startups can be seen in their desire to take on the world, solve big challenges (not only create vanity apps), and relentless execution and elimination of waste. Indeed, there’s a small optimization maniac inside me who loves startups because they aim for optimal use of resources – that’s the economic ideal. And they have to operate under strict scarcity which fosters innovation – much more exciting of a challenge to solve a major problem when facing resource constraints. You wouldn’t believe they are able to do it, but history shows otherwise.
3. The people and culture are amazing
Anyone who have been bitten by the startup bug know what I’m talking about. It’s energetic, young people that want to change the world for the better. Who wouldn’t get excited about that? On a side-note, it’s actually not to do with age; I’ve seen many mature people get excited about startups as well — so it’s more about mentality than age, gender or any demographic factor. The love for startups is universal – you can see that e.g. in the rapid diffusion of student-run entrepreneurship societies around the world. Startup people care about their surroundings, want to make a change, and are super helpful to one another. Again, this is the anti-thesis of “normal business” where dominant paradigms are rivalry and secrecy.
Startups openly share their ideas, invite new people to join them and are geared more towards collaboration than strategic thinking and self-interest. Even sometimes, coming from a business background, I think they are too nice (!) and neglect profit-seeking to their own demise (this shows e.g. in the monetization dilemma which I examined in my dissertation). However, it’s part of the startup magic at least in the early-stage: purely commercial motives would undoubtedly destroy some of the appeal. Ultimately, it’s the people of diverse backgrounds — IT, engineering, art, business, marketing, corporations — that make the startup scene such an interesting place to be.
4. Startups are never done
This relates to the first point of innovation. Joseph Schumpeter, a famous economist, had the idea of creative destruction which startups almost perfectly embody. When interacting with startups, you can see the world is never ready. The turnover of new companies coming and going, making small, medium and large impacts to their surroundings, is baffling. It’s analogous to research community, where scholars stand on the shoulders of those who came before them, and strive to make contributions, even small ones to the body of knowledge in their disciplines. Startups aim to make a contribution to the society, and are never finished at that.
In conclusion, startups are a fascinating topic to study and interact with. Startups are endlessly inspiring and embody the spirit of progress in daily lives of people. Startup people are a special group of people that willingly share their ideas and experiences to elevate one another.
March 30, 2017
This post is based on Dr. Elina Jaakkola’s presentation “What is co-creation?” on 19th August, 2014. I will elaborate on some of the points she made in that presentation.
Customer research, a sub-form of market research, serves the purpose of acquiring customer insight. Often, when pursuing information from consumers
companies use surveys. Surveys, and usage of customers as a source of information, have some particular problems discussed in the following.
1. Hidden needs
Customers have latent or hidden needs that they do not express, perhaps due to social reasons (awkwardness) or due to the fact of them not knowing what is technically possible (unawareness). If one is not specifically asking about a need, it is easily left unmentioned, even if it has great importance for the customer. This problem is not easily solved, since even the company may not be aware of all the possibilities in the technological space. However, if the purpose is to learn about the customers, a capability of immersion and sympathy is needed.
2. Reporting bias
What customers report they would do is not equivalent to their true behavior. They might say one thing, and do something entirely different. In research, this is commonly known as reporting bias. It is a major problem when carrying out surveys. The general solution is to ask about past, not future behavior, although even this approach is subject to recall bias.
3. Interpretation problem
Consumers answers to surveys can misinterpret the questions, and analysts can also misinterpret their answers. It is difficult to vividly present choices of hypothetical products and scenarios to consumers, and therefore the answers one receives may not be accurate. A general solution is to avoid ambiguity in the framing of questions, so that everything is commonly known and clear to both the respondent and the analyst (shared meanings).
4. Loud minority
This is a case where a minority, for being more vocal, creates a false impression of needs of the whole population. For example, in social media this effect may easily take place. A general rule of thumb is that only 1% of members of a community actively participates in a given discussion while other 99% merely observe. It is easy to see consumers who are the loudest get their opinions out, but this may not represent the needs of the silent majority. The solution would be stratification, where one distinguishes different groups from one another so as to form a more balanced view of the population. This works when there is an adequate participation among strata. Another alternatively would be actively seek out non-vocal customers.
Generally, the mentioned problems relate to stated preferences. When we are using customers as a source of information, all kinds of biases emerge. That is why behavioral data, not dependent on what customers say, is a more reliable source of information. Thankfully, in digital environments it is possible to obtain behavioral data with much more ease than in analogue environments. The problems of it emerge from representativeness and on the other hand fitting it to other forms of data so as to gain a more granular understanding of the customer base.
March 30, 2017
Technology is not a long-lasting competitive advantage in SEM or other digital marketing – creativity is.
This brief post is inspired by an article I read about different bid management platforms:
“We combine data science to SEM, so you can target based on device, hour of day and NASDAQ development.”
Yeah… but why would you do that? Spend your time thinking of creative concepts that generally work, not only when NASDAQ is down by 10%. Just because something is technically possible, doesn’t make it useful. Many technocratic and inexperienced marketing executives still get lured by the “silver bullet” effect of ad technology. Even when you consider outside events such as NASDAQ development or what not, newsjacking is a far superior marketing solution instead of automation.
Commoditization of ad technology
In the end, platforms give all contestants a level playing field. For example, the Google’s system considers CTR in determining cost and reach. Many advertisers obsess about their settings, bid and other technical parameters, and ignore the most important part: the message. Perhaps it is because the message is the hardest part: increasing or decreasing one’s bid is a simple decision given the data, but how to create a stellar creative? That is a more complex, yet more important, problem.
Seeing people as numbers, not as people
The root cause might be that the world view of some digital marketers is twisted. Consumers are seen as some kind of cattle — aggregate numbers that only need to be fed ad impressions, and positive results magically emerge. This world view is false. People are not stupid – they will not click whatever ads (or even look at them), especially in this day and age of ad clutter. The notion that you could be successful just by adopting a “bidding management platform” is foolish. Nowadays, every impressions that counts needs to be earned. And while a bid management platform may help you get a 1% boost to your ROI, focusing on the message is likely to bring a much higher increase. Because ad performance is about people, not about technology.
The more solid the industry becomes and the more basic technological know-how becomes mastered by advertisers, the less of a role technology plays. At that point of saturation, marketing technology investments begin to decline and companies shift back to basics: competing with creativity.
March 30, 2017
Planning makes happy people.
Media planning, or campaign planning in general, requires you to set goal metrics, so that you are able to communicate the expected results to a client. In digital marketing, these are metrics like clicks, impressions, costs, etc. The actual planning process usually involves using estimates — that is, sophisticated guesses of some sorts. These estimates may be based on your previous experience, planned goal targets (when for example given a specific business goal, like sales increase), or industry averages (if those are known).
By knowing or estimating some goal metrics, you are able to calculate others. But sometimes it’s hard to remember the formulas. This is a handy list to remind you of the key formulas.
In general, metrics relating to impressions are used as proxies for awareness and brand related goals. Metrics relating to clicks reflect engagement, while conversions indicate behavior. Oftentimes, I estimate CTR, CVR and CPC because 1) it’s good to set a starting goal for these metrics, and 2) they exhibit some regularity (e.g., ecommerce conversion rate tends to fall between 1-2%).
You don’t have to know everything to devise a sound digital media plan. A few goal metrics are enough to calculate all the necessary metrics. The more realistic your estimates are, the better. Worry not, accuracy will get better in time. In the beginning, it is best to start with moderate estimates you feel comfortable in achieving, or even outperforming. It’s always better to under-promise than under-perform. Finally, the achieved metric values differ by channel — sometimes a lot — so take that into consideration when crafting your media plan.