Archive for the strategy tag

Joni

Startup dilemmas: Feature priority problem

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Introduction

It is a common issue for startups applying customer development to discover many customer problems and either relating to that or to their vision include many, many features in their product development roadmap. However, as we know, it is not about the number of features but their quality, i.e. usefulness in solving the customer pain points.

Why is this important?

Having too many features introduces several problems: feature creep for end-users, loss of time and money, etc. One can perceive it as a form of premature scaling, but it is also has negative marketing consequences for positioning and differentiation: what is the startup all about? Too many features can easily cloud the answer. In brief, too many features pose a problem for both the end-user and the startup’s internal operations.

How to address the issue?

Well, it can be framed as ‘feature priority problem’, i.e. what features should the startup focus on. Say you are a “dance app startup”. Based on a prior assumptions and perhaps some customer development activities, you have defined a set of features reflecting what customers want. This set includes:

  • buy dance event tickets
  • get notifications on dance events
  • see dance events in map
  • get driving directions to events
  • learn to dance better (dancing instructions, videos)
  • search dance partner

You could focus on developing all these features, but according to the above logic, it makes more sense to choose the most relevant ones and solve them. If one problem is large enough, solving only that one would be enough to provide real value.

So, how do you determine which features are more important than others – i.e. how do you prioritize? It’s a very simple process:

  1. Tie them to problems (e.g., “I always miss the interesting dance events in my city” –> Get notifications on dance events).
  2. Prioritize problems through customer development (rank-order questions, customer understanding, relative solution gap).
  3. Thus, you have the features prioritized as well.

The customer development activities should therefore focus on setting the problems (and thus features) in order of preference from customer perspective. The more problems there are, the more useful it is to rank them. You can directly ask customers to rank the presented problems. You can also form a general understanding of the magnitude of different problems by interviewing customers.

Finally, ‘relative solution gap’ refers to the ratio between the magnitude of the problem and competing solutions effectiveness in solving it. The ideal would be a combination of MAGNITUDE: high, EFFECTIVENESS OF COMPETING SOLUTIONS: low. The least feasible problem to solve, according to this logic would be where the perceived magnitude (rank) of the problem is low and, moreover, extant solutions are effective in solving it.

Conclusion

To avoid feature creep, startups should prioritize their customer’s problems and associated solutions. Based on this, they are able to create a “market-oriented” product development roadmap.

Joni

Controlling ad quality in programmatic buying

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Highway to ad quality.

Ad quality is an issue in programmatic buying where ad exchange takes place via computer systems. In traditional ad exchange, there’s a human supervising the quality of advertising, but in a programmatic system it’s possible to receive spammy, illegal, or otherwise undesirable advertising without publishers (ad sellers) being aware of it. Likewise, the quality of performance such as clicks, likes or even impressions might be compromised by fraudulent bot behavior.

In the lack of humans, how to control for quality? Well, some ways include:

  • bot detection — this is what Google uses to filter invalid clicks likely caused by bots. It includes i.a. detecting anomalies in click behavior. Facebook, too, has mechanisms for detecting bots. How well these systems function should be from time to time audited by neutral 3rd parties due to the inherent problem of moral hazard by ad platforms.
  • performance-adjusted pricing and visibility — again, used by Google and Facebook in Quality Score and Relevance Score, respectively. What works cannot be wrong, essentially. The ads with the best response get the most views for the less money. However, this does not directly solve the problem of removing undesirable ads from the system.
  • reporting — again, both Facebook and Google enable reporting of ads by end users. This shows to advertisers as negative feedback – once negative feedback reaches a certain threshold, the ad stops showing. It is in a way crowdsourcing the quality control to the end users.
  • algorithmic analysis of ad content — for example, Facebook is able to detect nudity in the pictures and consequently disqualify them. This is among the best methods, albeit technically demanding, because machine can treat many millions of ad content units in batches. With constantly developing machine learning solutions the accuracy of automatic detection of undesirable content approaches human classifiers.
  • finally, we can have human fail-safe as a “plan B”. Again, both Facebook and Google use manual detection of click-fraud but also in treatment of advertisers’ complaints over refused ads. However, the solution is expensive and does not scale over millions of ad units, so it can be seen as a backup at best.

There – I believe these are the most common ways to control ad quality in modern programmatic advertising platforms. If you have anything
to add, please share it in the comments!

EDIT: Came across with another quality control mechanism: private exchanges. They effectively limit the number of participating advertisers making it manageable for a small number of humans to verify the ads. The whole point of the problem is that this works for a handful or so ads, but when there are millions of ad units, humans cannot be used as the primary solution.

Joni

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

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Introduction

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.

Conclusion

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.

Joni

People vs. business models: Warren Buffet’s dilemma

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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.

versus

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: https://www.quora.com/Why-doesnt-Warren-Buffett-invest-in-startups

Joni

Why human services are needed for world peace

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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.

Joni

Using Napoleon’s 19th Century Principles for Email Writing

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“In this age, in past ages, in any age… Napoleon.”
(The Duke of Wellington)

This is a short post reflecting upon Napoleon’s writing on war and efficient management. I think many of his principles are universal and apply to communication — my special consideration here is writing of emails, which is a vital skill because 1) you want your message to be read and replied! and 2) to get to that end, you need to learn how to write in a concise way.

Napoleon will help you to get there…

Quote 1:

“Reconnaissance memoranda should always be written in the simplest style and be purely descriptive. They should never stray from their objective by introducing extraneous ideas.”

First of all, write simple text. Avoid using complicated words and ambiguity (– expressions that can be interpreted in many ways). Oftentimes I see sentences that have ambiguity (or, in fact I myself writing them — when that happens, I instantly make it more clear so that there is absolutely no room for misinterpretation).

Quote 2:

“The art of war does not require complicated maneuvers; the simplest are the best, and common sense is fundamental. From which one might wonder how it is generals make blunders; it is because they try to be clever.”

The goal should never be to appear smart of whatever type; only to communicate your message efficiently. As I’ve said in other contexts, clear writing reflects clear thinking — and especially when it comes to writing emails, this is the only image you want to convey of yourself.

Quote 3:

“Think over carefully the great enterprise you are about to carry out; and let me know, before I sign your final orders, your own views as to the best way of carrying it out.”

In other words, make it easy for people to reply by asking for their opinion (when it’s such a matter their opinion would be useful). Write so that it’s easy to reply — e.g., don’t give too many choices or add any unnecessary layers of complexity.

Oftentimes I see messages which require considerable thinking to reply, and then it of course gets delayed or canceled altogether. Writing an email is like servicing a client; everything from the recipient’s part needs to be made as easy as possible.

Quote 4:

“This letter is the principle instruction of your plan of campaign, and if unforeseen events should occur, you will be guided in your conduct by the spirit of this instruction.”

This is actually the only quote where I disagree with Napoleon. Let me explain why. His rationale was based on the information asymmetry between him and his local officers. The officers have more immediate information; first of all, because of this it’s impossible to write a detailed instruction which would optimally consider the local circumstances, especially since they might change in the course of delivering the message (remember, in Napoleon’s day communication had a delay of even up to many days depending on the troops’ location).

Second, if the local officers were to verify each action, the delay in communication would result in losing crucial opportunities. In a word, decentralization of decision-making was essential for Napoleon. Napoleon himself explains it like this:

“The Emperor cannot give you positive orders, but only general instructions (objectives) because the distance is already considerable and will become greater still.”

However, in email communications the situation is different. First of all, there’s no communication lag, at least in the practical sense. Second of all, leaving things “open” for the recipient requires more cognitive effort from them, which in my experience leads to lower response rates and delays.

So, I’d say: Tell exactly what you want the other party to do. Don’t hint or imply – if you expect something to happen, make it clear. Oftentimes I see messages that are thought half-way through: the sender clearly implies that the recipient should finish his or her thinking. Not a good idea. Think the course of events through beforehand so that the recipient doesn’t have to.

More about Napoleon can be read from his memoirs, available at http://www.gutenberg.org/ebooks/3567

The author teaches and studies digital marketing at the Turku School of Economics.

Joni

Problem/Solution Space: A Startup Perspective

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I was inspired to write this post by the following pictures that I’d included in my lecture material a few years. Writing it in a bit of a hurry since the class starts soon! (but it’ll good enough to make the point)

(You can find the original source for the pictures by googling.)

Okay, a couple of things.

First, it’s highly important for a startup to define both the problem space and the solution space relating to their product. This includes the particular pain points that the customer whose problems we’re solving is experiencing – at minimum, solving one pain point, if substantial enough, suffices to make a successful business. The solution space includes the competition — here, it is super important to consider not only the direct competition (a common mistake) but also the indirect competition.

I call it the “pen and paper” test — can the problem you’re solving, most often with a high degree of technological sophistication, solved with a simpler, non-technological way?

And more importantly, how are the customers solving it now? It takes a lot for them to change their habits, much more than what founders typically think. The customer will not download an app to solve the problem — no matter if it’s free or not — unless the app provides a solution several magnitudes better than what he currently has. So, bear this in mind.

Second, once the gravity of the problem we’ve set to solve has been “validated” by more trustworthy means than guessing (such as customer development), the problem dimensions need to be tied formally into the product features the team is building (the second picture depicts this).

This way, we avoid waste in the startup development process (remember, waste is your biggest enemy because you’re always on borrowed time).

Third, after this the usage of these features needs to be backed up real usage data — in other words, the product needs to be exposed to real users whose behavior is analyzed based on engagement metrics (e.g., time they spend with the product, what features they use, how frequently, etc.). For this, there needs to be a good analytical system built into the product. Follow the Facebook guideline here: you don’t know what data you might later need, so store everything. This enables maximum flexibility for subsequent analyses.

And finally, of course when we get feedback on the usage of the product, we tie it back to the problem we’ve set out to solve and conclude whether or not we’re actually solving it. If the data suggest low engagement, we need to start over and make radical changes to the core of the product. If the data gives us a nice depiction, we’ll still continue with further adjustments to improve the user experience (which, of course, is by definition never good enough).

That’s it. Thank you for reading (and I’m off to class!)

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]

Joni

Modern Market Research Methods: A Startup Perspective

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EDIT: Updated by adding competitive analysis, very important to benchmark competitors.

EDIT2: Updated by adding experimentation (14th April, 2016)

Introduction

Somebody on Quora was asking about ‘tools’ for validating viability and demand for a startup’s products.

I replied it’s not a question of tools, but plain old market research (which seems to be all too often ignored by startup founders).

Modern market research methods

In brief, I’d include the following options to a startup market research plan:

  1. market statistics from various consultancy and research institution reports (macro-level)
  2. general market (country, city) statistics generated just for your case (macro-level à la PESTLE)
  3. competitive analysis, i.e. benchmarking existing solutions — will help you find differentiation points and see if your “unique idea” already exists in the market
  4. (n)etnography, i.e. going in-depth to user communities to understand their motivations (micro-level, can be done offline and online)
  5. surveys, i.e. devising a questionnaire for relevant parties (e.g., customers, suppliers) to understand their motivations (just like the previous, but with larger N, i.e. micro-level study)
  6. customer development, which is most often used in B2B interviews as a presales activity to better understand the clients’ needs. Here’s an introduction to customer development (Slideshare).
  7. crowdfunding, i.e. testing the actual demand for the product by launching it as a concept in a crowdfunding platform – this is often referred to as presales, because you don’t have to have the product created yet.
  8. experimentation, i.e. running different variations against one another and determining their performance difference by statistical testing; the tests can relate to e.g. ad versions (value propositions, messages) or landing pages (product variations, landing page structure and elements). Here’s a tool for calculating statistical significance of ad tests.

So, there. Some of the methods are “old school”, but some — such as crowdfunding are newer ways to collect useful market feedback. Experimentation, although it may appear novel, is actually super old school. For example, one of the great pioneers of advertising, Claude Hopkins, talked about ad testing and conversion optimization already in the 1920. (You can actually download his excellent book, “Scientific advertising“, for free.)

How to combine different methods?

The optimal plan would include both macro- and micro-level studies to get both the “helicopter view” and the micro-level understanding needed for product adoption. Which methods to to include in your market research plan depends on the type of business. For example, crowdfunding can be seen as a market validation method most suitable for B2C companies and customer development for B2B companies.

The punchline

The most important point is that you, as a startup founder, don’t get lured into the ‘tool fallacy’ — there’s no tool to compensate for the lack of genuine customer understanding.

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]

Joni

How to prevent disruption from happening to you? AKA avoiding the “Vanjoki fallacy”

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Introduction

A major issue of corporations is how they can avoid being disrupted. This is a commonly established issue, e.g. Christensen discusses it in his book “Innovator’s dilemma”. But I’m going to present here a simple solution for it.

Here it is.

Rule Number 1: Don’t look at absolute market shares, look at growth rates

I call this the “Vanjoki fallacy” which is based on the fatal error Vanjoki did while in Nokia, namely thinking that “Apple only has 3% of market share, we have 40%. Therefore we are safe”, when the guy should have looked at growth rates which were of course by far in Apple’s favor. Looking at them forces you to try and understand why, and you might still have a chance of turning the disruption around (although that’s not guaranteed).

“How can I do it?”

So, how to do it? Well, you should model your competitors’ growth – as soon as any of the relevant measures (e.g., revenue, product category, product sales) shows exponential growth, that’s an indicator of danger for you. Here’s the four-step process in detail.

First, 1) start out by defining the relevant measures to track. These derive from your industry and business model, and they are common goal metrics that you and your competitor share, e.g. sales.

Second, 2) get the data – easy enough if they are public companies, since their financial statements should have it. Notice, however, that there is a reporting lag when retrieving data from financial statements, which plays against you since you want as early knowledge of potential disruptors as possible. You might want to look at other sources of data, e.g. Google Trends development or some other proxy of their growth.

Third, 3) model the data; this is done by simply fitting the data into different statistical models representing various growth patterns — remember derivation at school? It’s like that, you want to know how fast something is growing. Most importantly, you want to find out whether the growth resembles linear, exponential growth, or logarithmic growth.

How to interpret these? Well, if it’s linear, good for you (considering your growth is also at least linear). If it’s exponential growth rate, that’s usually bad for you. If it’s logarithmic, depends where they’re at in the growth phase (if this seems complicated, google ‘logarithmic growth’ and you see how it looks). Now, compare the competitor’s growth model to yours – do have reason to be concerned?

Finally, 4) draw actionable conclusions and come up with a strategy to counter your opponent. Fine, they have exponential growth. But why is that? What are they doing better? Don’t be like that other ignorant Nokia manager Olli-Pekka Kallasvuo who publicly said he doesn’t have an iPhone, and that he will never get one. Instead, find out about your competitors products. Here is a list of questions:

  • What makes them better?
  • What makes their processes better?
  • What makes their brand better?
  • What makes their business model better?
  • What makes their employees better?

Find out the answers, and then make a plan for the best course of action. You may want to identify the most likely root causes of their growth, and then either imitate, null (if possible) or counter-disrupt them with your next-generation solution.

Conclusion

In conclusion, don’t be fooled by absolute values. The world is changing, and your role as a manager or executive is to be on top of that change. So, do the math and do your job. The corollary to this approach, by the way, is to create a some kind of “anti-disruption” alert system — that would make for a nice startup idea, but it’s a topic for another post.

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]

Joni

Online ad platforms’ leeching logic

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I and Mr. Pitkänen had a discussion about unfair advantage in business – e.g., a gift card company’s business model relying on people not redeeming gift cards, investment banker’s relying on monopoly to take 7% of each new IPO, doctor’s controlling how many new doctor’s are educated, taxi driver’s keeping the supply low through licenses, governments inventing new taxes…

It seems, everywhere you look you’ll find examples of someone messing with the so-called “free market”.

So, what’s the unfair advantage of online ad platforms? It’s something I call ‘leeching logic’. It’s about miscrediting conversions – channel x receives credit for a conversion while channel y has been the primary driver to it.

Let me give you two examples.

EXAMPLE 1:

You advertise in the radio for brand X. A person likes the ad and searches your brand in google. He clicks your search ad and buys.

Who gets credited for the sale?

radio ad – 0 conversions
google – 1 conversion

The conclusion: Google is leeching. In this way, all offline branding essentially creates a lift for search-engine advertising which is located at a later stage of the purchase funnel, often closing the conversion.

EXAMPLE 2:

You search for product Y in Google. You see a cool search ad by company A and click it. You also like the product. However, you need time to think and don’t buy it yet. Like half the planet, you go to Facebook later during that day. There, you’re shown a remarketing ad from company A but don’t really notice it, let alone click it. After thinking about the product for a week, you return to company A‘s website and make the purchase.

Who gets credited for the sale?

Google – 1 conversion (30-day click tracking)
Facebook – 1 conversion (28-days view tracking)

In reality, Facebook just rides on the fact someone visited a website and in between making the purchase also visited Facebook, while they learned about the product somewhere else. They didn’t click the retargeting ad or necessarily even cognitively processed it, yet the platform reports a conversion because of that ad.

For a long time, Facebook had trouble in finding its leeching logic, but now it finally has discovered it. And now, like for other businesses that have a leeching logic, the future looks bright. (Good time to invest, if the stock’s P/E wasn’t somewhere at 95.)

So, how should marketers deal with the leeches to get a more truthful picture of our actions? Here are a few ideas:

  •  exclude brand terms in search when evaluating overall channel performance
  • narrow down lookback window for views in Facebook — can’t remove it, though (because of leeching logic)
  • use attribution modeling (not possible for online-offline but works for digital cross-channel comparisons)
  • dedupe conversions between channels (essentially, the only way to do this is by attribution modeling in 3rd party analytics software, such as GA — platforms’ own reporting doesn’t address this issue)