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“Please explain Support Vector Machines (SVM) like I am a 5 year old.”

“Please explain Support Vector Machines (SVM) like I am a 5 year old.” #analytics #machinelearning #modeling

Courtesy of @copperking at Reddit:

Direct quotation from Reddit:

  1. “We have 2 colors of balls on the table that we want to separate.
  2. We get a stick and put it on the table, this works pretty well right?
  3. Some villain comes and places more balls on the table, it kind of works but one of the balls is on the wrong side and there is probably a better place to put the stick now.
  4. SVMs try to put the stick in the best possible place by having as big a gap on either side of the stick as possible.
  5. Now when the villain returns the stick is still in a pretty good spot.
  6. There is another trick in the SVM toolbox that is even more important. Say the villain has seen how good you are with a stick so he gives you a new challenge.
  7. There’s no stick in the world that will let you split those balls well, so what do you do? You flip the table of course! Throwing the balls into the air. Then, with your pro ninja skills, you grab a sheet of paper and slip it between the balls.
  8. Now, looking at the balls from where the villain is standing, they balls will look split by some curvy line.

Boring adults the call balls data, the stick a classifier, the biggest gap trick optimization, call flipping the table kernelling and the piece of paper a hyperplane.”

Some reflections:

Well, for a practice-oriented guy the first question obviously is: so what? What can you do with it in practice?

I think it boils down to the nature of classification algorithms. They are quite widely used, e.g. in image or text recognition. So, machine can better learn how to differentiate between an orange and an apple, for example. This of course leads into multiple efficiency advantages, when we are able to replace human classifiers in many jobs.

In conclusion, in my quest to understand machine learning it has become obvious that support vector machine is not the easiest concept to start from. However, since classification is an essential area in machine learning, one cannot avoid it for too long.

Ad-Hoc Networks and Solution-Based Selling

For digital products, the salesman’s briefcase is unlimited.


In KIBS (‘knowledge intensive business services’ which used to be called “professional services”), newcomers are more and more often building ad-hoc networks with complementing service providers, may they be established companies or freelancers.

These ad-hoc networks remain dormant most of the time, but the links (“nodes”) are activated upon need. They enable the coverage of a large selection of complex customer needs, and therefore are a form of organization that competes with large enterprises bidding on the same projects.

Theory basis

The idea of ad-hoc networks is compatible with the theoretical constructs of resource integration (wiz. service-dominant logic) and solution-based selling. The professional agent taking the role of a resource integrator can increase his chances of providing a solution for a wide range of needs by widening his network. By so doing he acts as a type of entrepreneur: he takes external resources (know-how) and combines them in a novel way to “create value” (or, as economists would say, utility). As such, the idea is very much compatible with the notion of value creation in marketing theory.

These type of resource-integrating agents can also be seen as match-makers and indeed they are critical in mitigating transaction costs (searching, vetting, and contracting service providers) between market actors — as such, they in fact realize the classic match-making purpose of marketing which is to connect supply and demand as efficiently as possible. Whereas in the theory of the firm, it is classically seen that an enterprise can expand via horizontal or vertical integration, the formation of ad-hoc networks is an alternative approach.

The idea is also compatible with the theory of network effects: the more (potentially) useful connections you have, the more valuable professional you are — indeed, given that the contacts can be activated in due course when needed to realize that potential of value creation. In a similar vein, complementarity of the network in terms of skills is a requisite – say, Skill A and Skill B need to complement one another so that more such combinations can be built that correspond to modular customer needs in solution selling. If there are gaps in the resource integrator’s network, it is more likely that another provider that can provide the complete solution wins the case.

Many of the ventures compatible with what I’m talking about here focus on building a network of “tough names” whose expertise they can sell (for example, esteemed university professors, skilled freelancers, reputed marketing agencies). Tough names bring credibility and legitimacy to the offering (so as to avoid the liability of newness) and enable the provision of such services that otherwise would either be impossible or unfeasible for the resource integration to provide. The flexible nature of this arrangement is fundamentally important, as the resource integrator cannot perfectly anticipate or predict to complex customer needs – all he can do is to prepare the necessary “ingredients” for covering many types of complex needs. As a side note, the importance of productization may be negligible in such a case, as the product offering defined by the resource integrator cannot match the complex need of the client.

An additional benefit of flexibility is cost-efficiency. As the links are dormant most of the time, they do not incur a fixed cost and are thus a financially flexible and smart way of “acquiring” expertise, especially compared to recruiting. Economically, therefore, ad-hoc networks are a more efficient way of organizing labor resources than “idle” workforce: assuming that a portion of each worker’s time also in the professional job markets is at idle use. This may not always be the case.

By giving their pledge to provide a service when needed, the professionals are also not losing anything – typically in these arrangements if they are not interested or are busy elsewhere they can refuse to take a particular case. So joining the network includes only an upside for them — in a way, the agent provides a distribution channel for the professional’s expertise, or acts as a voluntary “sales force”.

Managing multi-layered networks

For the resource integrator’s part, he needs to first of all ensure that incentives are set at an adequate level for the professionals to participate in service provision come need, and secondly ensure a plan B in case they won’t (e.g., Professional A –> Professional B). This is an example of building a multi-layered professional network with “backups”.

The resource integrators may also build multiple layers for different type of clients and service scenarios, say separate the partners possessing the same skills into different customer segments or “buckets“; this strategy keeps the professionals with the same skill-set separate and enables the integrator to build flexible solutions for different customer profiles, say small and large companies.

For example,

  • Enterprise client – Needed skill: Website development –> use Service provider A
  • Small client – Needed skill: Website development –> use Service provider B

The interesting questions relate to exclusivity and management of such multi-layer network arrangements.

First of all, it needs to be clearly communicated to the network participants that they are given a certain limited exclusivity for them not to compete against one another and therefore eradicate the benefits of joining (a phenomenon that took place related to the first wave of e-marketplaces in the early 2000s) — but this can be done as explained above. Bucketing the network into multiple service level layers prevents intra-network competition and maximizes the utility of individual members.

Second, the separation tactic must only take place between potential rivals; complementing parties need to cooperate for the network to be able to provide the offered solution.

Network as a competitive advantage in fast-paced markets

The more complex the customer need landscape is, the better equipped a network is in responding to it in comparison to individual actors. Thus, in theory even a large corporation may lose against an agile resource integrator because he has the scope and scale of the network behind him.

Traditionally, companies are seeking for horizontal and/or vertical integration to produce scope and scale benefits in professional services, but there are downsides to this approach — it is expensive, slow and rigid. Even if the corporation would seek for “dynamic competence” (as per Teece) by hiring or acquiring know-how, the updating needs creates a pertaining conundrum: the company must constantly either grow or become outdated and irrelevant.

In practice, the existent skills and workforce are protected by organizational inertia which prohibits strategic renewal (as described by Christensen), and so the large corporation cannot renew itself as fast as a network. The speedier the shift in customer demands, the larger the competitive advantage for an ad-hoc network in this respect.

Practical tips for network builders

So what are the skills needed for this type of professionals?

  • First, the ability to spot opportunities.
  • Second, inter-personal skills, or “emotional intelligence”.
  • Third, intellect to understand complex technologies at an adequate level so that he is able to see their core value and apply them in practical business cases.
  • Fourth, he of course needs to be customer-driven and understand customer needs as per the logic of solution selling.

Finally, tenacity and persistence are needed to deal with multiple vendors throughout complex projects; in other words, real skills in project management.

I like to refer to the “virtual suitcase” of modern salespeople. Do you recall seeing the real suitcases (ones like the one in the cover of this post) of door-to-door salesmen? They always had a scarce offering of merchandise because it was limited by how much was possible to fit into the suitcase. In a virtual world, no such constraints exist – in professional business services, scaling the ad-hoc network is only limited by your ability to network and comprehend the business value of new technologies, service providers and phenomena.

These are not minor restrictions though, and the modern salesmen cannot expect to win with the same logic as their predecessors. The sales process is more holistic nowadays – but it is also more flexible – for the talented ones the rewards are bigger, too.


Complex needs whose fulfillment needs modular solutions are not feasibly provided by one vendor, but rather by a network. The most effective form of network is the ad-hoc network.

In a way, this argument is not purely novel since in we have always done business by asking “Hey, I have this thing I need to be taken care of – do you know anyone for the job?“. Now shift this logic to complex professionals services — it is not enough to name one person or company, but you have to name three, four, ten, or even fifteen. The novelty comes from the coordination of a network. Shipping, construction, digital transformation, nuclear power plants… It is a collage of providers that participate in the service provision, and a network is the ideal solution for service provision.

Therefore, the multi-layered ad-hoc network strategy is a flexible way to compete with larger players. It has the potential to overcome legitimacy issues relating to new and small organizations by making newness and smallness irrelevant. It is also in line with the momentum-gaining idea of “freelancer economy” as the economy moves into the direction of short-term episodic interactions.

However, episodic does not make relationship marketing any less relevant – quite the opposite, in that era relationships are more valuable than ever, as they enable the quick discovery and activation of particular specialized skills that would otherwise be difficult and time-consuming to obtain.

The author currently works as a researcher at the Turku School of Economics. His interests include startup companies and digital marketing.

Platform strategy: How can media companies co-align their operations with incentives of social platforms


Platform integration is a major issue for publishers. The question, as interpreted by some of them, takes the form: friend or foe? Although it would be naïve to answer “friend”, platforms such as Facebook and Twitter are not foes either. At minimum, they are necessary evil to cope with, at maximum they are strategic leverage. But somewhere along this axis the strategic response of media companies has to be, as readers and content consumers are spending the most of their online time in social platforms. Hence the need for a platform strategy – an issue this post touches upon.

“Remora’s curse” in action

Some time ago, Upworthy and a few other “new media companies” that base their business logic on identifying viral hits and recycling (or “curating”) content of not their own doing, experienced a noticeable decrease of traffic from the social media giant Facebook. In my dissertation, I’ve labelled this as Remora’s curse, a condition whereby a startup builds its house on “rented land”, essentially becoming dependent on the host platform in the attempt to solve the chicken-and-egg problem associated with user acquisition.

Countering Remora’s curse

However, Buzzfeed, although at surface a similar business than the other new media companies, was left intact in terms of traffic and visibility in Facebook. How come?

Here’s a perfect explanation by Jonah Peretti, the founder of Buzzfeed:

“BuzzFeed is very aligned with the interests of all the major social networks: 1) we are in this for the long term, 2) we continually invest in our content to make it better, 3) we do R&D on new formats and areas (lists, quizzes, explainers, mobile, video, breaking news, long form), and 4) we never game platforms with deceptive headlines, we never trick our readers, we put the reader first in all our decisions. The end result is that we are focused on making content that *readers* love and share and traffic growth on social platforms is only a secondary effect.”

Herein lies the answer: Buzzfeed was more compatible with the incentives of Facebook – especially in terms of providing “authentic” content as oppose to recycled “clickbaits”.

How should media companies approach social platforms?

I think Peretti’s answer encapsulates the perfect approach for any publisher devising their platform strategy.

First, you want to invest in the relationship with the platform. You do this by developing capabilities that are “native” in that platform, learning about that platform’s logic and rules as much as you can, and tailoring content (length, type, format) to it.

Second, you of course want to create engaging content because engaging content is what interests the platform as well (due to positive network effects). You don’t want to try and drive people from the platform to your site, but keep them within the platform enjoying your content (which you will monetize in other ways, such as in-stream ads or instant article integration). You learn through platform analytics (e.g., Facebook Insights) what content works and why.

Third, you want to experiment on the new features as soon as they roll out. This goes back to the first point — continuous investment on the platform. Only by so doing can you become a major player in that platform. You need to have journalists who are Facebook specialists at the same time, or at least willing to develop into such. With greater understanding comes the ability to quickly take advantage of new platform opportunities and enjoy the short but strong pioneer advantages associated with early movers.

Fourth, you don’t want to optimize for the platform but ultimately for the people. This means no “clickbaits” or recycling of others’ content. Instead, you want to create genuinely interesting (and useful) pieces of content which are your own original editorial content. Again, this requires investments in competence and capabilities in order for it to work. Your organizational structure and processes need to reflect online content production, so that you are able to create platform-specific content rapidly and run your production activities as a holy tandem of data-driven creativity.


Essentially, Peretti compares Facebook to a broadcaster that is interested in favoring content that keeps the “viewers” engaged. As a publisher, you want the same. The thing is, the platform won’t give you much “airtime” if you want to lure people away. Therefore, you need to share your best bits of content in the platform.

The author currently works as a researcher at the Turku School of Economics. His interests include digital marketing, startups, and platforms.

Broken Window Fallacy — Still Relevant?

Do we need more broken windows?

There is a fallacy within broken window fallacy.

I will now explain this argument.

Essentially, the fallacy (by the classic French economist Frederick Bastiat) argues that “breaking windows”, although brings work for window repairers and thus adds to economic activity, is sub-optimal because of the opportunity cost of using the work to build (or buy) something new.

But, this means there indeed is alternative job for the window repairer, or that the labor COULD be used more efficiently elsewhere (e.g., producing innovations). In the early days, where productivity was the bottle-neck for economic growth, this might have been the case.

But nowadays, I think the modern job market dynamics do not categorically support the broken window fallacy — it’s getting increasingly difficult to create products that add genuine value and not only rely on exploiting market inefficiencies (which, arguably, could be a form of value) or persuading consumers to buy for the sake of owning the new shiny thing (which is often misunderstood as marketing’s core value added).

As of now, we’d need some more broken windows to stimulate the economy and get the money circulating.

Productivity is no longer the bottleneck for growth — there is over-supply in both material produce and human labor — generating demand is now the primary economic problem. Marketers would recognize this as the shift from production orientation to sales-orientation and finally to customer orientation. We need a similar shift in the scale of the economy.

But how to accomplish that?

A good start, from policy perspective, are infrastructure projects that produce not only jobs but enable the platform effect, i.e. possibility to “innovate on top of” as per the classic definition of platforms. Any investments that enable the creation of economic activity, either by moving or connecting people, or by removing barriers such as Uber-prohibitive taxi cartels, or by making licenses and software tools and equipment accessible and affordable for all (also in terms of skills, viz. education), or by supporting incubators and access to early-stage funding, are positive ways to enable the creation of innovations.

Consider Finland — I live in Turku which is about two hours train ride from Helsinki. Turku is a big city (in Finnish standards) but in terms of job opportunities it pales in comparison to Helsinki (which is the capital). So, lately there has been talks of a “one hour train” between Turku and Helsinki. As stated previously, building this would not only increase employment but also provide a platform externality since more people would be able to live in Turku and work in Helsinki. Instead of investing the money which Finland is borrowing at an increasing rate to unemployment benefits, it should go to employing people on e.g. infrastructure projects like this.

Now consider Europe; following the same logic, we should focus on large-scale infrastructure projects like improving railroad connections between Asia and Europe, roads, hospitals, telecommunications, etc. Instead, much time is spent arguing on either minor details or managing whatever “threats” (refugees, euro-crisis) the continent is facing. Dealing with threats is important sure, but the policies cannot only be reactive — without a foresight and building concrete things, there will be no better tomorrow.

Anyway, transportation, communications technology, better housing and health-care — I’m counting those as infrastructure services that benefit the economy both short- and long-term. And repairing any of them does not fall under broken window fallacy — quite the opposite.

The author works as a researcher at the Turku School of Economics.

Negative tipping and Facebook: Warning signs

This Inc article states a very big danger for Facebook:

It is widely established in platform theory that reaching a negative tipping point can destroy a platform. Negative tipping is essentially the reverse of positive tipping — instead of gaining momentum, the platforms starts quickly losing it.

There are two dimensions I want to look at in this post.

First, what I call “the curse of likes“. Essentially, Facebook has made it too easy to like pages and befriend people; as a result, they are unable to manage people’s newsfeeds in the best way in terms of engagement. There is too much clutter, leaving important social information out, and the “friend” network is too wide for the intimacy required to share personal things. The former reduces engagement rate, the latter results in unwillingness to share personal information.

Second, if people are sharing less about themselves, the platform has it more difficult to show them relevant ads. The success of Facebook as a business relies on its revenue model which is advertising. Both of the aforementioned risks are negative for advertising outcomes. If relevance decreases, a) user experience (negative effects of ads) and b) ad performance decrease as well, resulting in advertisers reducing their ad spend or, in worst-case scenario, them moving on to other platforms.

To counter these effects, Facebook can resort to a few strategies:

  1. Discourage people from “over-liking” things – this is for their own benefit, not to clutter the newsfeed
  2. Easy options to unsubscribe from people and pages — e.g., asking “Do you want to see this?” in relation to posts
  3. Favoring social content over news and company posts in the newsfeed algorithms – seeing personal social content is likely to incite more social content
  4. Sentiment control of newsfeed algorithm – to many, Facebook seems like a “negative place” with arguing on politics and such. This is in stark contrast to more intimate platforms such as Instagram. Thus, Facebook could incorporate sentiment adjustment in its newsfeed algorithm to emphasize positive content.
  5. Continued efforts to improve ad relevance – especially by giving incentives for high-CTR advertisers to participate by lowering their click prices, thereby encouraging engagement and match-seeking behavior.

Overall, Facebook as a platform will not be eternal. But I think the company is well aware of this, since their strategy is to constantly buy out rivals. The platform idea persists although individual platforms may perish.

People vs. business models: Warren Buffet’s dilemma

In Quora, somebody asked why Warren Buffet prefers not to invest in startups [1]. One of the answers that resonated with me was this one:

“In an interview several years back, Warren Buffet said that he does not like to invest in companies whose success is based on the smartness of its people.

His reasoning was that all companies hire from the same pool of talent, so smart people by themselves do not provide long-term competitive advantage or “moat” (because a competitor can hire the same or similar talent). He thought of a company’s processes (not just operating processes, but also processes for new product creation, developing new business models etc) as the place where its value resides.”

So, I got to think of this question:

Which is more important for business success, people or business model?

At critical extremes, the answer splits like this:

People are critical, so talented people can make any business model work.


Business model is critical, so even non-talented people can make a good business model work.

The question is quintessential for startup entrepreneurship — should we be
chasing the best people or the best combination of business model parameters?

In other words, can we find business models combinations that even an idiot could use to succeed? Or, is it like most lean startup advocates argue, that any business model parameters are just guesses and the success rests only on the team’s ability to execute them?

There are examples of smart people turning around business that would have otherwise failed. There are equally examples of poorly managed companies that still thrive because they have a killer business model at place.

However, facing the market dynamics often involves shaping the business model parameters that therefore cannot be seen static but dynamic in nature. But who are the ones shaping them? It’s the people — ultimately everything in companies can be abstracted to human actions. But, without the right “recipe” of business model components at place, the actions of even the smartest people can become futile. As such, we may not be able to examine the team and business model separately – business model and people are not isolated but interacting factors.

The truth, therefore, lies somewhere in between and in the mix of both. Oftentimes in dichotomous questions like this end up in a structurally similar conclusion that was made here. Almost every time, an extreme argument can be shot down. The fallacy of believing in extremes can therefore save you time, but lead astray.

As for Warren Buffet, the explanation given in the Quora post sounds plausible — for an investor, it may be an efficient strategy to focus on business model parameters and macro-competitive factors (and finding opportunities against logical basis) instead of betting on startups with risky ideas and people.

[1] Here’s the Quora discussion:

Ohjelmallisen ostamisen alusta: ideaaliominaisuuksia

Full-metal digitalist.

Maailma muuttuu, markkinoijani

Tällä hetkellä digitaalinen media on siirtymässä ohjelmallisen ostamisen malliin, ts. mainokset ostetaan ja myydään mainosalustan (esim. Google AdWords, Facebook) kautta. Myös perinteinen offline-media (TV, printti, radio) tulee ajan myötä siirtymään ohjelmallisen ostamisen järjestelmiin, joskin tässä menee arvioni mukaan vielä 5-10 vuotta.

Miksi ohjelmallinen ostaminen voittaa?

Syy on selkeä:

Ohjelmallinen ostaminen on lähtökohtaisesti aina tehokkaampaa kuin vaihdanta ihmisten välityksellä.

Taloustieteen näkökulmasta tarkasteltuna mainosvaihdantaan, kuten kaikkeen vaihdantaan, liittyy transaktiokustannuksia: hinnan neuvottelu, paketointi, yhteydenpito, kysymykset, mainosten lähettäminen, raportointi jne. Tämä on ihmistyötä joka maksaa aikaa ja vaivaa, eikä johda optimiratkaisuun hinnan tai mainonnan tehokkuuden kannalta.

Ihminen häviää aina algoritmille tehokkuudessa, ja mainonta on tehokkuuspeliä.

Edellä mainitut transaktiokustannukset voidaan minimoida ohjelmallisen ostamisen kautta. Mediamyyjiä ei yksinkertaisesti tarvita enää tässä prosessissa; samalla mainonnasta tulee halvempaa ja demokraattisempaa. Toki siirtymävaiheessa tulee olemaan siirtymäkipuja, etenkin liittyen organisaatiorakenteen muutokseen ja kompetenssin päivittämiseen. Bisneslogiikassa on myös siirryttävä “premium”-ajattelusta vapaaseen markkina-ajatteluun: mainostila on vain sen arvoinen kuin siitä saatavat tulokset ovat mainostajalle — nämä tulevat olemaan pienempiä kuin mediatalojen nykyinen hinnoittelu, mikä onkin negatiivinen kannustin siirtymän hyväksymiseen.

Mitkä ovat menestyksekkään ohjelmallisen ostamisen alustan ominaisuuksia?

Näkemykseni mukaan niitä ovat ainakin nämä:

  • matala aloituskustannus: tarvitaan vain 5 euron budjetti aloittamiseen (näin saadaan likviditeettiä alustalle, koska myös pienmainostajien on kannattavaa lähteä kokeilemaan)
  • budjettivapaus: mainostaja voi vapaasti määrittää budjetin, ei minimispendiä (ks. edellä)
  • markkinapohjainen hinnoittelu: tyypillisesti algoritminen huutokauppamalli, joka kannustaa totuudenmukaiseen huutamiseen (vrt. Googlen GSP ja Facebookin VCG-malli)
  • suorituspohjaisuus: hinnoittelukomponentti, jolla “palkitaan” parempia mainostajia ja näin kompensoidaan mainonnan haittoja loppukäyttäjälle
  • vapaa kohdennus: mainostaja voi itse määrittää kohdennuksen (tämän EI tule olla mediatalon “salattua tietoa”)

Nämä ominaisuudet ovat tärkeitä, koska kansainväliset kilpailijat jo tarjoavat ne, ja lisäksi ne on osoitettu toimiviksi niin teoreettisessa kuin käytännöllisessä tarkastelussa.

Tärkeitä näkökulmia mainostajan näkökulmasta ovat:

  • demokraattisuus: kuka vain voi päästä alustalle ja käyttää sitä itsepalveluna
  • tulospohjaisuus: maksetaan toteutuneista klikeistä/myynneistä, ei ainoastaan näytöistä
  • kohdennettavuus: mainostaja voi itse säätää kohdennuksen, mikä nostaa relevanssin mahdollisuutta ja näin vähentää mainonnan negatiivista verkostovaikutusta (ts. asiakkaiden ärsyyntymistä)

Kohdennusvaihtoehtoja voivat olla esim.

  • kontekstuaalinen kohdennus (sisällön ja mainostajan valitsemien avainsanojen yhteensopivuus)
  • demograafinen kohdennus (ikä, sukupuoli, kieli)
  • maantieteellinen kohdennus
  • kävijän kiinnostuksen kohteet

Osa näistä voi olla mediataloille hankalia selvitettäviä, ainakaan hankalampaa kuin Facebookille – kohdennus on kuitenkin mainonnan onnistumisen kannalta kriittinen seikka, joten tietojen saamiseksi on tehtävä työtä.


Ohjelmallisen ostamisen alustat ovat mediatalon ydinkompetenssia, eivät ostopalvelu. Siksi uskonkin, että alan toimijat lähtevät aggressiivisesti kehittämään kompetenssiaan alustojen kehittämisessä. Tai muuten ne jatkavat mainoskakun häviämistä Googlen ja Facebookin kaltaisille toimijoille, jotka tarjoavat edellä mainitut hyödyt.

Kirjoitin muuten mainosvaihdannasta pro gradun otsikolla “Power of Google: A study on online advertising exchange” vuonna 2009 — jo siinä sivuttiin näitä aiheita.

Joni Salminen
KTT, markkinointi
[email protected]

Kirjoittaja opettaa digitaalista markkinointia Turun kauppakorkeakoulussa.

Facebook Ads: too high performance might turn on you (theoretically)


Now, earlier I wrote a post arguing that Facebook has an incentive to lower the CPC of well-targeting advertisers because better targeting improves user experience (in two-sided market terms, relevance through more precise targeting reduces the negative indirect network effects perceived by ad targets). You can read that post here.

However, consider the point from another perspective: the well-targeting advertiser is making rents (excessive profits) from their advertising which Facebook wants and as the platform owner is able to capture.

In this scenario, Facebook has an incentive to actually increase the CPC of a well-targeting advertiser until the advertiser’s marginal profit is aligned with marginal cost. In such a case, it would still make sense for the advertiser to continue investing (so the user experience remains satisfactory), but Facebook’s profit would be increased by the magnitude of the advertiser’s rent.

Problem of private information

This would require that Facebook be aware of the profit function of its advertisers which as for now might be private information to the advertisers. But had Facebook this information, it could consider it in the click-price calculation. Now, obviously that would violate the “objective” nature of Facebook’s VCG ad auction — it’s currently set to consider maximum CPC and ad performance (negative feedback, CTR, but not profit as far as I know). However, advertisers would not be able to monitor the use of their profit function because the precise ad auctions are carried out in a black box (i.e., asymmetric information). Thus, the scenario represents a type of moral hazard for Facebook – a potential risk the advertisers may not be aware of.

Origin of the idea

This idea I actually got from one of my students who said that “oh, I don’t think micro-targeting is useful“. Then I asked why and he said “because Facebook is probably charging too much from it”. I said to him that’s not the case, but also that it could be and the idea is interesting. Here I just elaborated it a bit further.

Also read this article about micro-targeting.

Micro-targeting is super interesting for B2B and personal branding (e.g., job seeking).

Another related point, that might interest you Jim (in case you’re reading this :), is the action of distributing profitable keywords by the platform owner between advertisers in search advertising. For example, Google could control impression share so that each advertiser would receive a satisfactory (given their profit function) portion of traffic WHILE optimizing its own return.


This idea is not well-developed though; it rests on the notion that there is heterogeneity in advertisers’ willingness to pay (arising e.g., from different in margins, average order values, operational efficiency or such) that would benefit the platform owner; I suspect it could be the case that the second-price auction anyway considers this as long as advertisers are bidding truthfully, in which case there’s no need for such “manipulation” by Google as the prices are always set to maximum anyway. So, just a random idea at this point.

Why human services are needed for world peace

The bot can be boss, as long as we have jobs.

Why are human services the future of our economy? (And, therefore, an absolute requirement for world peace [1].)

For three reasons:

  1. They do not pollute or waste material resources (or tend to do so with significantly less degree than material consumption)
  2. Exponential growth of population absolutely requires more human labor (supply and demand of labor)
  3. There’s no limit to service creation, but by type and nature they are infinite (because people’s needs are infinite and ever-changing)

Consequently, critical, absolutely critical measures are needed in the Western economies to enable true service economy.

Here are some ideas:

  • Taxation of human labor (VAT of services) must be drastically cut.
  • Side-costs of employing people (instead of machines) must be drastically cut.
  • Any technological solutions (e.g., platforms) increasing the match between supply and demand of human labor must be endorsed, and respectively all barriers such as cartels, removed.

Human services are the key to sustainable and socially balanced consumption – I look at Finland back in the 1950s; we were a real service economy. Today, every job possible has been replaced either by automation or by self-service (which companies call “customer participation”). We’re a digital self-service economy, not a service economy anymore.

I long for the days when we had bellboys, cleaning ladies, office clerks, research assistants and other support staff — they are important jobs which nowadays are no more. Self-service and efficiency are in fact the enemies of employment. We must consider if we want a society optimized for efficiency or one optimized for well-being (I’m starting to sound like, Bernie Sanders; which might not be a bad thing as such, but the argument has a deeper rationale in it).

Maximum efficiency is not maximum employment, far from it.

Regarding Silicon Valley and startups, there should be a counter-movement against efficiency. So far, software has been eating the world, and the world — at least in terms of job market — is becoming increasingly less. Granted, many new job types have been created to compensate for the loss, but much more is needed to fill the gap software is leaving. I think there needs to be a call for new type of startups, ones that empower human work. If you think about it, there already exists some good examples – Uber, Taskrabbit, Fiverr, Upwork are some of them. But all too often the core value proposition of a startup is based on its ability to reduce “waste” – that is, human labor.

I do not think there is any limit to creation of human services. People are never completely satisfied, and their new needs spawn new services, which in turn require new services, and so on and on. In fact, the only limit to consumption of services is one’s time and cognitive abilities! This is good and well, even hopeful if we think of the big picture. But I do think an environment needs to be created where incentives for providing human services match those of machine services, or at least approach that much more than what it currently does.

This is an issue that definitely needs to be addressed with real structural reforms in the society; as of yet, I haven’t seen ANY of that — not even discussion — in Finland. It’s as if the world was moving but the politicians were asleep, stuck in some old glory days. But in the end we all want the same thing – we want those old days BACK, when everyone had a job. It’s just that we cannot do it without adjusting the policies — radically — to the radical change of productivity which has taken place in the past decades.

It’s like another candidate — not Sanders — says: We gotta start winning again.

End notes

[1] The premise here is that the well-being of a middle class is required for a balanced and peaceful society. In contrast, the crumbling middle class will cause social unrest and wide dissatisfaction which will channel out in political radicalism, scapegoat seeking, and even wars between nations. Jobs are not just jobs, they are vehicle for peace.

The author has taught services marketing at the Turku School of Economics.

Facebook ad testing: is more ads better?

Yellow ad, red ad… Does it matter in the end?


I used to think differently about creating ad variations, but having tested both methods I’ve changed my mind. Read the explanation below.

There are two alternative approaches to ad testing:

  1. “Qwaya” method* — you create some base elements (headlines, copy texts, pictures), out of which a tool will create up to hundreds of ad variations
  2. “Careful advertiser” method — you create hand-crafted creatives, maybe three (version A, B, C) which you test against one another.

In both cases, you are able to calculate performance differences between ad versions and choose the winning design. The rationale in the first method is that it “covers more ground”, i.e. comes up with such variations that we wouldn’t have tried otherwise (due to lack of time or other reasons).

Failure of large search space

I used to advocate the first method, but it has three major downsides:

  1. it requires a lot more data to come up with statistical significance
  2. false positives may emerge in the process, and
  3. lack of internal coherence is likely to arise, due to inconsistency among creative elements (e.g., mismatch between copy text and image which may result in awkward messages).

Clearly though, the human must generate enough variation in his ad versions if he seeks a globally optimal solution. This can be done by a) making drastically different (e.g., humor vs. informativeness) as oppose to incrementally different ad versions, and b) covering extremes on different creative dimensions (e.g., humor: subtle/radical  informativeness: all benefits/main benefit).


Overall, this argument is an example of how marketing automation may not always be the best way to go! And as a corollary, the creative work done by humans is hard to replace by machines when seeking optimal creative solutions.

*Named after the Swedish Facebook advertising tool Qwaya which uses this feature as one of their selling points.