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Tag: strategy

Thoughts on Remora’s Curse

Remora’s curse takes place when startup attaches itself to a large platform in the attempt to solve the chicken-and-egg problem of getting users. The large platform then exercises its greater power to void the investments made by the startup into the platform, essentially causing more or less deadly delays and needs for re-design. The idea originates from Don Dodge who wrote about the Remora Business Model.

Examples:

  • Facebook stopping “friends of friends” access
  • Twitter killing ecosystem players (cf. Meerkat)
  • LinkedIn killing Developer program
  • Google’s Panda update dropping sites

The popular platform is not your friend. If their interests collide with yours, they will walk over you. Period.

Solutions:

  • diversify – don’t be dependent on only one platform
  • limit the overall dependence on platforms; i.e. do not make integration your secret sauce (aka “never build your house on rented land”)
  • capture the users (envelopment): when you get them to visit for the first time, make them yours; e.g. email subscription, registration

Purposefully limit the role of platform to user acquisition as opposed to being core value prop. Platforms, seen this way, are just like other marketing channels – if they work, scale. if not, kill. The benefit of platform integration is that it may partially solve the cold-start problem: get faster traction and accelerate user growth.

Read more about Remora’s curse in my dissertation: Startup dilemmas – Strategic problems of early-stage platforms on the internet

Startup due diligence: Some considerations

We had an interesting week with the Qatar Science and Technology Park (QSTP) that had invited several high-profile entrepreneurs from the US to evaluate the technologies of Qatar Computing Research Institute (QCRI).

Unfortunately, I wasn’t able to attend all the sessions, but from what I saw I picked up a few pointers for due diligence work done by investors when evaluating the startups. Here they are:

  • customer references => who are the existing customers and what do they say?
  • investor references => who are the existing investors and what do they say?
  • competitors => feature comparison & position map
  • technology => expert evaluation
  • IPR => defensibility of the core tech
  • key competitive advantage => if not the core tech, then what is the thing preventing others from replicating your success?

Conclusion

It’s worthwhile to mention that the formal due diligence process is something different from an informal one – the latter takes place when the investor does some initial inquiries about the team and the tech, and then decides whether he wants to pursue further discussions. After reaching an adequate level of confidence, formal and detailed due diligence procedures conducted with the help of experts (e.g., tech, legal, science) ensue.

The strategy algorithm

Introduction

The purpose of the strategy algorithm is to present a simple, parsimonius, and proven method for successful creation of a corporate strategy.

In corporations, the problems usually do not relate to lack of resources or options, but to complexity of having in fact too many choices. This can lead to illusion of superiority which is not a short-term problem since the corporation is protected by its existing buffers, but which will become a long-term issue when external conditions have tilted enough to cause a disruption driven by changing customer needs or competitors’ superior solutions. Therefore, any managing director or CEO needs simple guiding principles to reduce compexity into something manageable. The strategy algorithm (SA) is one such tool.

The strategy algorithm

The goal of the SA is to find a unique competitive advantage that the customers appreciate, that can be executed, and that is not the focus of any existing competitors. This goal is known as the strategic goal. The steps are as follows:

Phase 1

1. Define customer segments – what benefits are important for each segment?
2. Conduct competitor analysis – what segments are not focused on by any competitor?
3. Conduct internal analysis – what resources do we have and need to capture that segment?

Phase 2

4. Then, make sure 1-3 are co-aligned (=write out the strategy).
5. Then, define strategic projects to remove bottlenecks and create assets (=resources that serve the strategic goal).
6. Then, execute with strong focus (=anything that deviates from the strategic goal; discard).

Applying the strategy algorithm

As you can see, Phase 1 is geared toward research and planning, and Phase 2 toward implementation.

In step 1, you can use techniques such as:

  • conjoint analysis
  • personas (ethnography, interviews, surveys, social media analysis)

Conjoint analysis aims to find product attributes that customers most value. Another option is to summarize customer segments into personas that are fictive but descriptive characterizations of customer groups.

In step 2, “focus” is the keyword. Competitors can operate in the same market and offer similar products, but the main point is that they are not focusing on it (=their turnover is not dependent on it, they are not investing excessively in product development, marketing and distribution). In other words, by you taking the focus, competitors will remain at bay, because they have more important priorities. An example is Nokian Tyres – at one point, it was a generic tyre company, but as an outcome of strategic work they re-focused on “Trusted by the natives” guideline, i.e. winter tyres.

In step 3, you need to conduct a gap analysis of ‘what we have and what we need’. An example is Stephen Elop at Nokia – he recognized that the mobile world is moving to software ecosystems, and Nokia has redundant know-how about legacy mobile software. In hindsight, we can say he should have fired and hired much more aggressively to transform the company into a focused, competitive unit.

Acknowledgments

The thinking borrows heavily from the Master’s thesis of Lasse Kurkilahti (Turku School of Economics), as well as related works from Michael Porter, W. Chan Kim, Renée Mauborgne, and other strategic thinkers.

 

Startups! Are you using a ‘mean’ or an ‘outlier’ as a reference point?

Introduction

This post is about startup thinking. In my dissertation about startup dilemmas [1], I argued that startups can exhibit what I call as ‘reference point bias’. My evidence was emerging from the failure narratives of startup founders, where they reported having experienced this condition.

The reference point bias is a false analogy where the founder compares their startup with a great success case (e.g., Facebook, Google, Groupon).

According to this false analogy: “If Facebook did X and succeeded, we will do X and succeed, too.

A_x | B_x –> S

or doing A ‘x’, given that B did ‘x’, results in success.

According to a contrary logic, they ought to consider the “mean” (failures) rather than the “outlier” (success) because that enables better preparation for the thousand-and-one problems they will face. (This is equivalent to thinking P(s) = 1- P(f), or that eliminating failure points (f) one can achieve success (s); which was a major underlying motivation for my dissertation.)

Why is this a problem?

Firstly, because in the process of making decisions under the reference point bias, you are likely to miss all the hardship left out from the best practices outlined by the example of your outliers. In other words, your reference point suffes from survivorship bias and post-hoc rationalization.

But a bigger, and a more substantial problem in my opinion, is the fundamental discrepancy between the conditions of the referred success case and the startup at hand.

Let me elaborate. Consider

A{a} ≠ B{b},

where the conditions (a) taking place in your startup’s (A) market differ from the conditions (b) of your reference point (B). As a corollary, as the set of market conditions of A approach B, the better suited those reference points (and their stories & best practices) become to your particular scenario. But startups rarely perform a systematic analysis for discovering how close the conditions whereupon certain advice or best practice were conceived match those at hand.

As a result, discrepancies originating from local differences, e.g. culture, competition, etc., emerge. Some of these dimensions can be modeled or captured by using the BMC (Business Model Canvas) framework. For example, customer segments, distribution channels, value propositions — all these can differ from one geographical location or point in time to another, and can be systematically analyzed with BMC.

In addition to BMC, it is important to note the impact of competitive conditions (a major deficit in the BMC framework), and especially that of the indirect competition [2]. At a higher level of abstraction, we can define discrepancies originating from spatial, temporal, or cultural distance. Time is an important aspect since, in business, different tactics expire (e.g., in advertising we speak of fatigue or burn indicating the loss of effectiveness), and there are generally “windows of opportunity” which result in the importance of choosing the correct time-to-market (you can easily be too early or too late).

So, overall, reference point bias is dangerous, because you end up taking best practices from Twitter literally, and never end up making actual money. In particular, platform and freemium businesses are tricky, and based on my experience something like 90% of the reference point outliers can be located to those fields. It should be kept in mind that platforms naturally suffer from high mortality due to winner-take-all dynamics [3].

In fact, one of the managerial implications of my dissertation was that platform business may not be a recommended business model at all; at least it is one order of magnitude harder than a your conventional product business. The same goes for freemium: giving something for free in the hopes of at some point charging for it turns out, more often than not, wishful thinking. Yet, startups time after time are drawn towards these challenging business models instead of more linear ones.

That is why the general rule “This is not Google, and you’re not Sergey Brin.” is a great leveler for founders overlooking cruel business realities.

But, when is outlier a good thing?

All that being said, later on, I have realized there is another logic behind using reference points. It is simply the classic: “Aim for the stars, land on the moon.”

Namely, having these idols, even though flawed ones, encourage thousands and thousands of young minds to enter the startup scene. And that’s a good thing, resulting in a net positive effect. Sometimes it’s better not knowing how hard a problem is, because if you knew, you would never take on the challenge.

Conclusion

In conclusion, my advice to founders would be two-fold:

1) Use reference points as a source of inspiration, i.e. something you strive to become (it’s okay wanting to be as successful as Facebook)

2) But, don’t apply their strategies and tactics literally in your context.

Each context is unique, and the exact same business model rarely applies in a different market, defined by spatial, temporal and cultural distance. So the next time you hear a big-shot from Google or Facebook telling how they made it, listen carefully, but with a critical mind. Try to systematically analyze the conditions where they took place, not only “why” they worked.

End notes

[1] Salminen, J. (2014, November 7). Startup dilemmas – Strategic problems of early-stage platforms on the internet. Turku School of Economics, Turku.

[2] That is, how local people do things differently: A good example is WhatsApp which was not popular in the US because operators gave free SMS; the rest of the world was, and is, very different.

[2] Katz, M. L., & Shapiro, C. (1985). Network Externalities, Competition, and Compatibility. The American Economic Review, 75(3), 424–440.

Buying and selling complement bundles: When individual selling maximizes profit

Introduction

When we were young, me and my brother used to buy and sell game consoles on Huuto.net (local eBay) and on various gamer discussion forums (Konsolifin BBS, for example). We didn’t have much money, so this was a great way to earn some cash — plus it taught us some useful business lessons along the years.

What we would often do was to buy a bundle (console+games), break it apart and sell the pieces individually. At that time we didn’t know anything about economics, but intuitively it felt the right thing to do. Indeed, we would always make money with that strategy, as we knew the market prices (or their range) of each individual item.

Looking back, I can now try and explain with economic terms why this was a successful strategy. In other words, why individual selling of items in a complement bundle is a winning strategy.

Why does individual selling provide a better profit than the selling of a bundle?

Let’s first define the concepts.

  • individual selling = buy complement bundle, break it apart and sell individual pieces
  • a complement bundle = a central unit and its complements (e.g., a game console and games)

Briefly, it is so because the tastes of the market are randomly distributed and do not align with the exact contents of the bundle. It then follows that the exact set of complements does not maximize any individual’s utility, so they will bid accordingly (e.g., “I like those two games (out of five), but not the three so I don’t put much value to them”) and the market price of the bundle will set below the full value of its individual parts.

In contrast, by breaking apart and selling individually each complement can be appraised at full value (“I like that game, so I’ll pay its real value”). In other words, the seller will need to find a buyer for each piece who appreciates that piece to its full value (=has a preference for it).

The intuition

Tastes and preferences differ, which reflects to individuals’ utility functions and therefore willingness to pay. Selling a bundle is a compromise from the perspective of the seller – he compromises his full price, because the buyer is willing to pay only according to his preferences (utility function) which do not match completely with the contents of the bundle.

Limitations

There are two exceptions I can think of:

1) Highly valued complements (or homogeneous tastes)

Say all the complements are of high value in the market (e.g., popular hit games). Then, a large portion of the market assigns full value to them, and the bundle sets close or equal to the sum of individual full prices. Similarly, if all the buyers value the complements in a similar way, i.e. their taste is homogeneous, the randomness required for the individual selling to perform does not exist.

2) Information asymmetry

Sometimes, you can get a higher price by selling a bundle than by selling the individual pieces. We would use this strategy when the value of complements is very little to an “expert”. Then, if you were less experienced you could see a game console + 5 games the 5 games, however, had very little value in the market and it would therefore make sense to include them in the bundle and to attract less-informed buyers. In other words, benefiting from information asymmetries.

Finally, the buyer of a complement bundle needs to be aware of the market price (or the range of it) of each item. Otherwise, he might end up paying more than the value of the sum of individual items.

Conclusion

Finding bundles and selling the pieces individually is a great way for young people to practice business. Luckily, there are always sellers in the market who are not looking to optimize their asking price, but appreciate the speed and comfort associated with selling bundles (i.e., dealing with one buyer). The actors with more time and less sensitivity to comfort can then take advantage of that condition to make some degree of profit.

EDIT: My friend Zeeshan pointed out that a business may actually prefer bundling even when the price is lower than in individual selling, if they assign a transaction cost (search, bargaining) to individual selling and the sum of transaction costs of selling individual items is higher than the sum of differences between the full price and bundle price of complements. (Sounds complicated but means that you’d spend too much time selling each item in comparison to profit.) For us as kids this didn’t matter since we had plenty of time, but for businesses the cost of selling does matter.

On complexity of explaining business failure

Introduction

During the research period for my dissertation based on startup failures, I realized there are multiple layers of failure factors associated with any given company (or, in reverse, success factors).

These are:

  1. generic business problems (e.g., cash-flow)
  2. individual-level problems (e.g., personal chemistry)
  3. company type problems (e.g., lack of funding for startups)
  4. business model problems (e.g., chicken-and-egg for platforms)

Only if you combine these multiple layers – or perspectives – can you understand why one business venture fails and another one succeeds. However, it is also a relative and interpretative task — I would argue there can be no objective dominant explanation but failure as an outcome is always a combination of reasons and cannot therefore be reduced into simple explanations at all.

A part of the reason for the complexity is the existence of parallel root causes.

For example,

  • A company can said to have failed because it runs out of money.
  • However, why did it run out of money? Because customers would not buy.
  • Why didn’t they buy? Because the product was bad.
  • Why was the product bad? Because the team failed to recognize true need in the market.
  • Why did they fail to recognize it? They lacked such competence.
  • Why did they lack the competence? Because they had not enough funding to acquire it.

Alas! We ended up making a circular argument. That can happen with any failure explanation, as can coming up with a different root cause. In a team of many, while also considering several stakeholders, it is common that people’s explanations to cause and effect vary a great deal. It is just a feature of social reality that we have a hard time of finding unambiguity.

Conclusion

In general, it is hard to dissect cause and effect. Human beings are inclined to form narratives where they choose a dominant explanation and discard others. By acknowledging a multi-layered view on failure, one can examine a business case by applying different lenses one after another. This includes interviewing different stakeholder groups and understanding multiple perspectives ranging from individual to structural issues.

There are no easy answers as to why a particular company succeeds or fails, even though the human mind and various success stories would lead you to believe so!

Buying? How to determine the offer price for a website

Introduction

A few years back I was considering of buying a website. In the end, I didn’t end up making the offer, largely because I couldn’t figure out how to calculate the offer price in a plausible way. Since then I’ve had a bit more experience in estimating figures in other contexts, as well as participating in some M&A discussions in the ecommerce field. But today, while cleaning my inbox, I happened to read that old email from many years ago, and thought of sharing some thoughts on the topic — hopefully as a bit wiser person!

Basic figures

If you are planning of buying a website and thinking about the offer price, you should know some basic figures of the website:

ARPU, or average revenue per user

if there is none, you have to estimate the earning potential. If the monetization model is advertising, find some stats about avg. CPMs in the industry. If it’s freemium, consider avg. revenue per premium user as well as the conversion rate from free to paid (again, you can find some industry averages).

Number of users/visitors

This is easy to get from analytics software.

Revenue

Revenue or revenue potential (if there is none at the moment) can be calculated by multiplying the two previous figures. So you would move from unit metrics to aggregate numbers.

Profit

You also need to consider the cost of maintenance, marketing and other actions that are needed to keep the site running and growing. Deduct those from the revenue to get profit. If you want faster growth, you need to factor in an investment for that; although it’s not exactly a part of the offer calculation, it still needs to be considered in the overall plan for making money with the website.

Calculating the offer price

Then, to determine offer price you need to multiply the profit with a time unit, e.g. months or years, to get the offer price. This figure is like a line in the sand — you can try and think it from the seller’s perspective: how many years or months of profit would he want to recoup in order for him to be willing to sell.

As an investor, your best break can be found when the profit is low, but revenue potential and number of visitors as well as visitor loyalty are high. The high revenue potential means that there is likely to be a realistic monetization model, but because that has not been applied yet, one can negotiate a good price if the seller is willing to let go of the website. Loyalty – manifested in high rate of returning visitors – indicates that the website provides real value for its visitors instead of relying e.g. on spammy tactics to lure in casual browsers. In the end, the quality of traffic matters a lot in whatever business model you apply.

You should also consider the stability of the figures – in particular, the historical growth rate. With the historical growth rate, you are able to project the development of traffic and revenue in the future. At this point, be realistic of what it takes to uphold the growth rate and thorough in asking the current owner in great detail what he has done so far and why. This information is highly valuable.

Because there is a lot of imprecision in coming up with the aforementioned figures, you would be wise to factor in risk at every stage of the calculation. Convey the risk also to the buyer in a credible way, so that he sees ‘it won’t be easy’ to get your money back. This is a negotiation tactic but also the real state of affairs in many cases.

Closing remarks

I don’t include any “goodwill” on things like brand or design in the calculation, because I think those are irrelevant for the price determination. All sunk costs that don’t serve the revenue potential are pretty much redundant — sticking to real numbers and, when they are absent, realistic estimates — is a much better way of determining the price of a website.

Defining SMQs: Strategic Marketing Questions

Introduction

Too often, marketing is thought of being advertising and nothing more. However, already Levitt (1960) and Kotler (1970) established that marketing is a strategic priority. Many organizations, perhaps due to lack of marketers in their executive boards, have since forgotten this imperative.

Another reason for decreased importance of marketing is due to marketing scholars pushing the idea that “everything is marketing” which leads to decay of the marketing concept – if it is everything, it is nothing.

Nevertheless, if we reject the omni-marketing concept and return to the useful way of perceiving marketing, we observe the linkage between marketing and strategy.

Basic questions

Tania Fowler wrote a great piece on marketing, citing some ideas of Professor Roger Martin’s HBR article (2014). Drawing from that article, the basic strategic marketing questions are:

  • Who are our customers? (segmentation)
  • Why do they care about our product? (USPs/value propositions/benefits)
  • How are their needs and desires evolving? (predictive insight)
  • What potential customers exist and why aren’t we reaching them? (market potential)

This is a good start, but we need to expand the list of questions. Borrowing from Osterwalder (2009) and McCarthy (1960), let’s apply BMC (9 dimensions of a business model) and 4P marketing mix thinking (Product, Place, Promotion, Price).

Business Model Canvas approach

This leads to the following set of questions:

  • What is the problem we are solving?
  • What are our current revenue models? (monetization)
  • How good are they from customer perspective? (consumer behavior)
  • What is our current pricing strategy? (Kotler’s pricing strategies)
  • How suitable is our pricing to customers? (compared to perceived value)
  • How profitable is our current pricing?
  • How competitive is our current pricing?
  • How could our pricing be improved?
  • Where are we distributing the product/solution?
  • Is this where customers buy similar products/solutions?
  • What are our potential revenue models?
  • Who are our potential partners? Why? (nature of win-win)

Basically, each question can be presented as a question of “now” and “future”, whereupon we can identify strategic gaps. Strategy is a lot about seeing one step ahead — the thing is, foresight should be based on some kind of realism, or else fallacies take the place of rationality. Another point from marketing and startup literature is that people are not buying products, but solutions (solution-based selling, product-market fit, etc.) Someone said the same thing about brands, but I think solution is more accurate in the strategic context.

Adding competitors and positioning

The major downside of BMC and 4P thinking from strategic perspective is their oversight of competition. Therefore, borrowing from Ries and Trout (1972) and Porter (1980), we add these questions:

  • Who are our direct competitors? (substitutes)
  • Who are our indirect competitors? (cross-verticality, e.g. Google challenging media companies)
  • How are we different from competitors? (value proposition matrix)
  • Do our differentiating factors truly matter to the customers? (reality check)
  • How do we communicate our main benefits to customers? (message)
  • How is our brand positioned in the minds of the customers? (positioning)
  • Are there other products customers need to solve their problem? What are they? (complements)

Defining the competitive advantage, or critical success factors (CSFs), leads into natural linkage to resources, as we need to ask what are the resources we need to execute, and how to acquire and commit those resources (often human capital).

Resource-based view

Therefore, I’m turning to resource-based thinking in asking:

  • What are our current resources?
  • What are the resources we need to be competitive? (VRIN framework)
  • How to we acquire those resources? (recruiting, M&As)
  • How do we commit those resources? (leadership, company culture)

Indeed, company culture is a strategic imperative which is often ignored in strategic decision making. Nowadays, perhaps more than ever, great companies are built on talent and competence. Related strategic management literature deals with dynamic capabilities (e.g., Teece, 2007) and resource-based view (RBV) (e.g., Wernerfelt, 1984). In practice, companies like Facebook and Google do everything possible to attract and retain the brightest minds.

Do not forget profitability

Finally, even the dreaded advertising questions have a strategic nature, relating to customer acquisition and loyalty, as well as ROI in regards to both as well as to our offering. Considering this, we add:

  • How much does it cost to acquire a new customer?
  • What are the best channels to acquire new customers?
  • Given the customer acquisition cost (CAC) and customer lifetime value (CLV), are we profitable?
  • How profitable are each products/product categories? (BCG matrix)
  • How can we make customers repeat purchases? (cross-selling, upselling)
  • What are the best channels to encourage repeat purchase?
  • How do we encourage customer loyalty?

As you can see, these questions are of strategic nature, too, because they are directly linked to revenue and customer. After all, business is about creating customers, as stated by Peter Drucker. However, Drucker also maintained that a business with no repeat customers is no business at all. Thus, marketing often focuses on customer acquisition and loyalty.

The full list of strategic marketing questions

Here are the questions in one list:

  1. Who are our customers? (segmentation)
  2. Why do they care about our product? (USPs/value propositions/benefits)
  3. How are their needs and desires evolving? (predictive insight)
  4. What potential customers exist and why aren’t we reaching them? (market potential)
  5. What is the problem we are solving?
  6. What are our current revenue models? (monetization)
  7. How good are they from customer perspective? (consumer behavior)
  8. What is our current pricing strategy? (Kotler’s pricing strategies)
  9. How suitable is our pricing to customers? (compared to perceived value)
  10. How profitable is our current pricing?
  11. How competitive is our current pricing?
  12. How could our pricing be improved?
  13. Where are we distributing the product/solution?
  14. Is this where customers buy similar products/solutions?
  15. What are our potential revenue models?
  16. Who are our potential partners? Why? (nature of win-win)
  17. Who are our direct competitors? (substitutes)
  18. Who are our indirect competitors? (cross-verticality, e.g. Google challenging media companies)
  19. How are we different from competitors? (value proposition matrix)
  20. Do our differentiating factors truly matter to the customers? (reality check)
  21. How do we communicate our main benefits to customers? (message)
  22. How is our brand positioned in the minds of the customers? (positioning)
  23. Are there other products customers need to solve their problem? What are they? (complements)
  24. What are our current resources?
  25. What are the resources we need to be competitive? (VRIN framework)
  26. How to we acquire those resources? (recruiting, M&As)
  27. How do we commit those resources? (leadership, company culture)
  28. How much does it cost to acquire a new customer?
  29. What are the best channels to acquire new customers?
  30. Given the customer acquisition cost (CAC) and customer lifetime value (CLV), are we profitable?
  31. How profitable are each products/product categories? (BCG matrix)
  32. How can we make customers repeat purchases? (cross-selling, upselling)
  33. What are the best channels to encourage repeat purchase?
  34. How do we encourage customer loyalty?

The list should be universally applicable to all companies. But filling in the list is not “oh, let me guess” type of exercise. As you can see, answering to many questions requires customer and competitor insight that, as the startup guru Steve Blank says, needs to be retrieved by getting out of the building. Those activities are time-consuming and costly. But only if the base information is accurate, strategic planning serves a purpose. So don’t fall prey to guesswork fallacy.

Implementing the list

One of the most important things in strategic planning is iteration — it’s not “set and forget”, but “rinse and repeat”. So, asking these questions should be repeated from time to time. However, people tend to forget repetition. That’s why corporations often use consultants — they need fresh eyes to spot opportunities they’re missing due to organizational myopia.

Moreover, communicating the answers across the organization is crucial. Having a shared vision ensures each atomic decision maker is able to act in the best possible way, enabling adaptive or emergent strategy as opposed to planned strategy (Mintzberg, 1978). For this to truly work, customer insight needs to be internalized by everyone in the organization. In other words, strategic information needs to be made transparent (which it is not, in most organizations).

And for the information to translate into action, the organization should be built to be nimble; empowering people, distributing power and reducing unnecessary hierarchy. People are not stupid: give them a vision and your trust, and they will work for a common cause. Keep them in silos and treat them as sub-ordinates, and they become passive employees instead of psychological owners.

Concluding remarks

We can say that marketing is a strategic priority, or that strategic planning depends on the marketing function. Either way, marketing questions are strategic questions. In fact, strategic management and strategic marketing are highly overlapping concepts. Considering both research and practice, their division can be seen artificial and even counter-productive. For example, strategic management scholars and marketing scholars may speak of the same things with different names. The same applies to the relationship between CEOs and marketing executives. Joining forces reduces redundancy and leads to a better future of strategic decision-making.

Online ads: Forget tech, invest in creativity

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.

Conclusion

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.

Startup dilemmas: Feature priority problem

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.