Income generating websites as investments

I’ve been looking into websites as an asset class from an investment point of view lately. Given I’ve dabbled around with public companies, private companies, real estate and consumer loans previously, I wanted to make some notes on what I’ve learned about websites as an asset class until now.

In this post, I’ll start with saying a few words about different asset classes to set the scene and give some frame of reference. Then I’ll dive into websites as an asset class, their risks, opportunities and so forth.

Overview of investment types

Bear with me for some background, I’ll dive into the specifics about websites in a minute.

One of the best investment advise I’ve heard is to only invest in assets you understand.

If we’re talking about companies, this means you should understand that company’s business. Because when you do, you understand what makes a company strong or weak and thus better grasp the threats and opportunities it’s facing.

At the end of the day, the better you understand what you’re investing in, the better you can pick your investments and the better you understand the risks.

I’d venture a guess that publicly traded companies and mutual funds that are investing in publicly traded companies, are the most common investment people have.

If we’d count people’s own homes as investments, this would come in as number one. But I won’t, since it’s not a pure investment. Given this limitation, I’d imagine real estate coming in as number two, measured in popularity.

(Site note: Robert Kiyosaki of Rich Dad, Poor Dad fame writes about owned homes being liabilities since they cost money. I’m not that strict since (a) a home can appreciate in value giving its owner a return and (b) in many cases owning is less expensive than renting, thus giving its owner a quantifiable saving which can be paralleled to an investment generating cash flow used to pay rent.)

Both public companies and real estate are well understood and mainstream investment vehicles for both big and small investors. There are huge amounts of money, people and focus in both asset classes and thus markets are generally pretty efficient.

This means it’s difficult to find investment objects that are priced really, really wrong, if you do even a little bit of background research and comparison.

Because of efficient markets and because of regulators forcing availability of information, we can invest in both public companies and real estate without really understanding those investments without huge risks.

(Side note: I don’t recommend investing in anything you don’t think you understand very well. Just saying…)

The same does not hold for other types of investments, such as the asset class known as SWAG. SWAG is short for silver, wine, arts and gold.

I can imagine a thousand ways for how things can go wrong if I’d try to pick pieces of art to buy as investments. I’d give it a 90% chance of failure, since I wouldn’t be able to just pick up a Picasso and hope things work out 10 years from now.

From my point of view, investing in websites is much more like investing in art than investing in the S&P500 stock index. It requires expertise and things can go horribly wrong really quick, unless you know what you’re doing.

Taking this train of thought further, the best parallel I can draw is to acquiring a small or medium sized business. This type of investment comes with huge risks compared to public companies, are much less liquid and usually require a at least moderate involvement by the owner. Actually, most small and even medium businesses are build around the assumption of major owner involvement whereas public companies are designed around absolutely no owner involvement whatsoever.

Websites as investments and my background in this game

Since websites require expertise as investment objects, I’ll just call them a “concierge asset” like small businesses or art. Something that you should only buy if you have the proper knowledge to grasp the risks.

As for myself and my background in this field, I’ve been working with digital marketing and digital services since the late 1990s. So even if I’m not the best at everything, I’d imagine qualifying as a “concierge” of developing and growing websites in general.

I’m not an expert in SEO, but I know the basics. I’m not an expert copywriter, but I’ve written all sorts of content including books. I’m not a developer, but I have handcrafted both websites and apps, coding line-by-line. You get the gist of it.

I’ve built hundreds of websites over the years. I’ve subcontracted work, I’ve build things myself and I’ve even bought one ready-made, income-generating site. Still, I feel there are a lot of things to learn about the affiliate marketing kind of sites.

I’m currently somehow involved in running the following Finnish sites:

  •, a site for dog owners. The site was purchased in 2017 and I run it together with a business partner. Income is based in advertising and content marketing partnerships.
  •, a site about personal finance. The site was built together with a business partner in 2018 and has not been monetized yet. It generates about 1/10 of the traffic compared to Kuono.
  •, a product review site for blenders. The site was built by me in 2016 to test if I can still get a site to rank properly in Google. It generates very moderate affiliate income.
  • Verokuitti, a site to exemplify how tax money is spent. It’s neither maintained nor monetised, but won our project team some awards.
  • is also worth mentioning, even though it doesn’t exist anymore. It was a content site around building website creation. It generated affiliate income, but given a competitor to my employer acquired the main affiliate partner, I didn’t feel comfortable getting income from them anymore and so I closed down the site.

After buying Kuono in 2017, I’ve been looking for other sites to buy. It seems like most Finnish sites are either minuscule or already properly monetized and sold to bigger media companies.

Since not finding proper sites to buy in Finland, I’ve started looking abroad.

The most commonly sold type of website from an investment perspective is one that’s doing affiliate marketing and generating income through referral based sales. There are some sites monetised through ads and lead gen out there as well, though.

This type of affiliate marketing website is a species on its own.

There are several marketplaces like Flippa, Empire Flippers and Investors Club that post sites for sale. These sites publish content in English and usually make a majority of their income thought the Amazon associates affiliate program.

Most sites seem to be priced around 30 x monthly profit, although prices commonly vary from 25-35x.

It seems like small, <$10k sites get sold in days. Once pass the $30k threshold, demand drops and >$100k sites seem to have much less buyers already.

If you want to start small, you’ll have to accept more risk, since the few day turnaround time doesn’t allow for proper due diligence.

Even if you do proper due diligence, there are still many inherent risks to these type of sites, like:

  • The traffic is usually based on Google searches. If Google changes their algorithm, you might lose tons of business.
  • Many sites make money on the Amazon affiliate program. Amazon has previously decreased the commissions they pay their affiliates and if this happens, you can lose tons of business.
  • Previous owners might have used black hat SEO tactics that haven’t yet been discovered by Google. Once discovered, your site can get punished, resulting in losing tons of business.

It’s also worth noting that new sites pop up every day and thus competition is fierce. If you don’t develop your site, it might hit a decline and eventually get worthless. This isn’t something that happens when you buy Apple stock. Then you can just sit back and wait, time will probably help appreciate rather than depreciate the stock you hold.

Growing the investments you’ve made

Once acquired, I’d assume both you and me want to grow our sites in order to generate more income and appreciate in value.

There are some basic measures that help almost any site, such as:

  • Publish more content on the topic of your site
  • Publish content in neighboring topics to what your site is about, in order to expand the niche
  • Improve content already published by updating, expanding and optimizing it
  • Get quality backlinks from other sites
  • Improve click-through to affiliate sites
  • Improve site speed
  • Add more revenue streams such as display advertising on an affiliate site

The best way to buy a site is to already know what can be improved before you purchase the site. This requires both research (to find the opportunities) and experience (to understand how easy or difficult it will be to do).

Sites that have already grown large, meaning at least 6 or maybe 7 figure price point, almost certainly have the basics covered. They are fairly authoritative, have good content, have broad content, have a lot of backlinks, have multiple revenue streams etc.

Smaller sites usually have much more room to expand and be optimized.

My goal is to learn how to take sites generating some revenue and grow them by 10x in a few years. This would let me grow much faster than starting sites from scratch. It would also require less capital than buying high 6 figure sites from the start.

Future topics and opportunities

The more I learn about this business, the more I understand I still have things to learn.

To be good at growing sites, you need to have good freelancers or the willingness and skills to do the work yourself. I’d rather outsource since, that enables more growth than making everything dependent on the availability of my time.

While running a digital agency in the past, I learned the value of good freelancers. They’re easy to work with, reliable, decently priced and very good at what they do. Like the dream employee, but without the downsides.

Once running, I believe the best deals are made with off-market opportunities, but I don’t yet know where to find them. The same holds true for real estate, privately held companies etc. If you’re the only bidder, it’s easier to get a good deal.

Sketchnotes from the Industry Product Management conference in Dublin, Ireland 16-17.4.2019

Product Collective organized a conference on product management in Dublin, Ireland on 16-17.4.2019. You can find my sketchnotes from most presentations here. Enjoy!

Day 1

Day 2

What are retailers thinking about in 2018?

I attended the eTail Nordic 2018 event and wanted to summarise some findings from selected keynotes on 2.10. – 3.10.2018.

Peter Mold, CDO, ICA

Peter Mold, the Chief Digital Officer of Swedish grocery and pharmacy giant ICA was first up. He stated ecommerce for groceries still hasn’t picked up in Sweden, concluding only 2% of the purchasing volume was coming in through digital channels in 2016.

One of the issues with ecommerce for groceries are the expensive and cumbersome logistics. As a grocer, you need to store, pick and transport fresh produce taking care of the cold chain all the way to the consumer, making it expensive.

Mold continued by describing the importance of data telling us that data is what feeds AI, which will become even more important.

Mold described the future of physical retail being all about the customer experience. He said retailers need to provide good experiences and even become a sort of hub connecting like-minded people or people with similar interests.

One of his views did not resonate that well with the audience. It was the future of voice vs keyboard controlled devices. Mold believed that we’ll see the keyboard vanish within the next five years. Asking the audience, there was quite some scepticism around this happening.

I’d like to support Mold’s view here. Looking at where efforts by Apple, Google, Amazon and other tech giants are, it’s AI enabled voice control. The technology is slowly but surely growing out of being a curiosity into being a usable interaction method.

Being a Finn, I expect to be among the last to use natural voice control, but in English the technology is maturing fast.

Mikael Lenneryd, Director of Digital and Loyalty, Apoteket

Mikael Lenneryd from Apoteket described a case from his former employer, Samsung. He told the story about how they connected their own first party data with the second party data from a telco to run better digital campaigns.

They used the combined data to target real people based on their interests. This was a challenge both technically and legally.

The technical challenge was combining the data and feeding it into the normal programmatic buying architecture. The legal issues were around sharing data between two large companies and then feeding it onto the other actors in the value chain. It took seven months to sort out the legalities to be able to execute.

But the results were good. Average click to conversion had a 35x uplift and the best segments had a 50x uplift. Which is, in one word, impressive.

The campaign was run on a regular promotion and not an extra sweet deal. So the results should be comparable. The product was a Samsung S8 with a 24-month contract.

Mei Chen, International Business, Alibaba

Next up is Mei Chen from Alibaba. Personally, I found this keynote very interesting given I have almost no knowledge about the Chinese market, but have been interested in it for a while.

The first shock is grasping the sheer volume of the market. The Chinese version of Black Friday is Singles Day. During the sale, Alibaba hit more than a billion dollars per hour for a 24-hour period. This means they totalled over 25 billion dollars during the day and night.

One key difference comparing China with the US or Europe is the age of the consumer. China has a huge number of young consumers and they want to stand out. This can be done by choosing what to wear, what to put on their faces (particularly women) or what to eat.

Alibaba is carrying a lot of European and Nordic brands as well. Given the wish to stand out, products coming from small and (from a Chinese point of view) obscure markets might have a lucrative opportunity ahead. And that’s how Alibaba wants to be seen: as an opportunity to move product, not a threat to local retailers focusing on Europe or a particular country within the region.

In China, marketplaces have a much stronger position than in the US or in Europe. Chen’s take was that the Chinese consumers don’t see a point in using a lot of different sites when you can find almost everything bundled together in just one place as well.

This is a trend we can see in the US as well with Amazon seeing that they have surpassed Google as the most used search engine for product search. So maybe this is the future of retail with platform players acting as supersized department stores and landlords deluxe for whomever wants to get their product out there en mass?

Caroline Carlqvist, Program Manager Personalization, Zalando

Caroline Carlqvist, working on personalisation for Zalando, talked about the challenges of fashion in particular. She described a small boutique in Italy where the owner got to know her so well her boyfriend could shop there for her and the shopkeep would make sure the clothes were a fit for her, in both style and size. That’s what Zalando wants to be as well, but at scale.

The particular challenge for fashion is size. It’s difficult to know if a medium is the same medium as you’ve gotten used to with another brand.

Sizing connected back to data. Zalando has a lot of data about returns and the reason for said returns. This data can help find the right fit. If you have a lot of people who bought brand A in medium sending back brand B in medium since it’s too small, Zalando can warn the next buyers of brand B to size up if they see medium from brand A as a good fit.

Zalando is also pushing this data back to the manufacturers so they know if their brand is consistently getting a bad fit from multiple people.

The threat of Amazon and the Intersport approach

There was a debate hosted on Amazon. I’m not going to dive into more detail about the debate, but I’d like to highlight something interesting presented by InterSport. They have started a cooperation with Tmall (a part of Alibaba) in China.

The partnership is an experiment into combining the upsides of physical retail and ecommerce into one package. Instead of bringing your shopping with you, you can stroll bag-free to lunch and get your new sneakers delivered to your house two hours later.

Louisa Nicholls, John Lewis

Louisa Nicholls from John Lewis shared some insights from the UK market. This is interesting for Nordic and Swedish retailers given that Amazon is already active in the UK market.

Nicholls pointed out that consumers are moving from buying more stuff for fulfilment into searching for experiences.

Given the trend, John Lewis have started adding services to their offering to lure people into the stores. E.g. their style studio service gets an uplift of 30% measured in revenues compared to fashion shoppers who don’t use the service.

Nicholls added to the stories by others before her on the value of data. She told us retail used to be about three things: location, location and location. Now that has changed into data, data and data.

Summary and reflections

Amazon is, of course, on everyone’s mind given the rumours about them entering the Nordic markets. Sweden would be first up, given it’s the biggest population in the region. The severity of the threat seems to divide people.

As a reflection on Amazon’s possible level of threat, I’d like to reminisce on video rentals in Finland. In an article published in 2013, the two major video rental companies thought companies such as Netflix and HBO are a curiosity, not posing any real threat for them. In hindsight, it’s painfully obvious how wrong they were. Disruptors have a way of looking harmless early on.

Data, both the importance of data and how to use it properly, was a part of most keynotes and case studies. Well, it was the main topic of my case study as well, so I might be a bit biased. Yet I’d conclude the significance of data is well understood in retail, but many companies still lack in tools and tactics to actually make the data work for them.

The future of the physical store was also a big debate. This is natural, given most incumbents come from the physical space and have expanded into ecommerce. The issues is, no one really knows what role brick-and-mortar will play in the years to come.


Adding layers of complexity

A colleague asked me why we had issues introducing a new feature into a product. On a high level, the feature was pretty simple. So I needed to explain how adding layers of complexity made the design and implementation increasingly difficult. Here’s the analogy I gave to explain the problem.


At the end of the day, most tasks are conceptually easy. Need to install a piece of software? Just click a button, wait 30 seconds and voila, success.

Any trivial task can become enormous when you start adding layers of complexity.

I just noted installing software is trivial, right? But what if you need to do it on computers running OS X, Windows and Linux? What if you need to install 24 different language versions depending on the language of the OS? What if you need to install across phones, tablets and computers? What if you need to do it all automatically?

Getting complicated, right? Let’s keep the complications coming.

What if the automation needs to do the installation during nighttime, which you need to deduct depending on what timezone the device resides in just now? What if users have to be able to opt-out of specific installation times? What if you need to have a plan for how to maintain and update said software before being able to install?

Even one of these specific needs makes the installation much more difficult. Adding a new dimension makes the task exponentially more difficult.

Based on the discussion we were having, the same colleague told me an anecdote about Facebook’s logo redesign. She said that turning the logo from blue-on-white into white-on-blue cost the company 200 million Euros. Crazy, right? (Note: I have not fact checked this anecdote.)

If Facebook needed to test the logo to make sure it doesn’t contain unplanned meanings across most countries in the world, across most religions in the world and across a substantial set of sub-cultures throughout the world, the price tag starts to make sense.


I’m often tempted to remind people of the exponential difficulty of adding layers of complexity when they wonder how it’s so difficult to do simple things in large organizations.

On the other hand, this presents a huge business opportunity for anyone who wants to serve the enterprise segment. Just select what types of complexity you want to support and build a product or a service to mitigate said complexity.

Hyvän työpäivän metsästys

Tiedättekö sen tunteen, kun työpäivän jälkeen on varsinainen voittajafiilis? Tuntuu kuin olisi saanut aikaiseksi vaikka mitä ja energiaa piisaa muille jaettavaksi?

Niin minäkin. Mutta liian harvoin.

Ikävän usein tunnen itseni päivän päätteeksi väsyneeksi. Energiatasoni on nolla tai se on pakkasella. Huonoimmillaan tuntuu kuin päivän päätteeksi olisi enemmän ongelmia kuin mitä oli ennen työpäivän alkua.

Halusin enemmän hyvin päättyviä päiviä ja vähemmän huonosti päättyviä päiviä. Niinpä päädyin pohtimaan: voisinko suunnitella ja muotoilla työpäiväni sellaisiksi, että useampi päättyisi hyvään fiilikseen ja energiseen tunnelmaan?

Kävin läpi hyviin ja vähemmän hyviin tunnelmiin päättyneitä päiviä. Havaintojeni pohjalta tein seuraavan viisikohtaisen sotasuunnitelman hyvän työpäivän metsästystä varten.

1. Varaa rauhoittumisjakso päivän loppuun

Tämä voi kuulostaa itsestäänselvältä, mutta ei ole sitä. Jos et koskaan pääse pois työmoodista, niin et koskaan pääse pois työmoodista.

Oma kokemukseni on, että kiireessä työpaikalta lähteminen jättää päälle sekä kiireen tunteen että työmoodin. Työmoodin päättyminen vaatii jotakin muuta, johon keskittyä, kuten treenit tai jotakin sosiaalista tekemistä.

Parhaiten ja helpoiten työmoodista pääsee pois, kun ei lähde “kesken töiden” kovassa kiireessä. Noin 30 min omaa aikaa viimeisen puhelun tai palaverin jälkeen auttaa kummasti käsittelemään ja arkistoimaan keskeneräiset ajatukset, minkä jälkeen työmoodista on helpompi poistua.

2. Tee jotakin valmiiksi ennen koneen lyömistä kiinni

Tämä liittyy vahvasti rauhoittumisjaksoon. Usein parhaat päivät ovat juuri niitä, kun rauhoittumisjakson aikana saa useita pieniä asioita ruksittua pois tehtävälistalta. Kyse voi olla banaalista asiasta, kuten matkalaskun tekemisestä tai rasittavaan sähköpostiin vastaamisesta.

Kun on saanut yhden tai useamman asian valmiiksi ja ruksittua pois listalta, on yleensä hyvä fiilis. Eli juuri sellainen fiilis, mihin työpäivä kannattaa päättää. Josta pääsemmekin seuraavaan kohtaan.

3. Älä tarkista sähköposteja puhelimelta heti kotiin päästyä

Varmin tapa pilata hyvin päättynyt päivä on tarkistaa työpäivän jälkeen josko sähköpostiin olisi vielä tipahtanut jotakin, joka on hoidettava kiireesti. Voin kertoa, että keskimääräinen illalla lähetetty sähköposti (a) voi odottaa aamuun ja (b) ei tule olemaan innostavan positiivinen.

Olen jo sulkenut sähköpostin ilmoitukset puhelimesta. Ikoni ei edes näytä lukemattomien viestien määrää, koska muuten kiusaus avata äppi olisi liian suuri. Silti päädyn usein rutiininomaisesti selailemaan sähköposteja metrossa, kotisohvalla ja milloin missäkin. Yleensä vain pilatakseni oman mielialani.

4. Älä tunge päivää liian täyteen

Tämä ei varmasti tule kenellekään yllätyksenä, mutta yli kymmenen palaverin päivät eivät ole kivoja. Jatkuva kiire, kasaantuvat sähköpostit, ainainen context switch ja väliin jäänyt lounas eivät tee hyvää kenellekään.

Joten muistutus itselleni: silloin kun tuntuu kaikista houkuttelevimmalta tunkea päivä liian täyteen löytääkseen aikaa kaikelle on itse asiassa huonoin mahdollinen aika tunkea päivä liian täyteen. Yritä siis välttää ylibuukkaamista.

5. Suunnittele päivän ohjelmaan jotakin kivaa/hauskaa/energisoivaa

Luterilaisen työmoraalin omaavana masokistina voin muistuttaa itseäni tästä maailman tappiin saakka ilman, että viesti menee perille. Yritän silti.

Kun päivän aikana on odotettavissa jotakin mukavaa, niin sekä odotus että itse mukava asia ovat palkitsevia.


Nyt tiedän mitä tavoitella. Jäljellä on vain harjoituksen vaikea osuus: suunnitelmasta kiinni pitäminen silloin, kun se on vaikeaa.

AI, data ja automaatio

”Robotit tulevat ja vievät työpaikkamme.”

Suurin piirtein näin lehdistö on otsikoinut meneillään olevan murroksen mm. täällä, täällä, täällä ja täällä. Niinpä innostuin tiivistämään omia ajatuksiani automaatiosta, joka on koko trendin pohja. Varoitus: aion seuraavaksi käyttää monia inhottavia insinööritermejä.

Jotta jotakin voisi automatisoida, täytyy ymmärtää prosesseja. Prosessit koostuvat kahdesta osasta: päätöksistä ja toimenpiteistä. Ensin tehdään päätös tarvittavasta toimenpiteestä ja sitten suoritetaan itse toimenpide. Toimenpidettä seuraa päätös parhaan jatkotoimenpiteen suorittamisesta ja sama toistuu.

Insinöörit ovat aina olleet hyviä automatisoimaan toimenpiteitä. Robotti hitsaa kaksi palkkia yhteen tehtaassa. Ohjelmisto koostaa raportin. Tiskikone puhdistaa astiat.

Päätösten automatisointi on paljon vaikeampaa, sillä päätökset ovat monimutkaisia. Tarkastellaan tätä käyttäen autoa esimerkkinä.

Auton suorittamien toimenpiteiden automatisointi on lasten leikkiä. Hieman yksinkertaistaen autossa voi painaa kaasua, painaa jarrua ja kääntää rattia. Kolme helppoa toimenpidettä. Ensimmäisen vuoden automaatio-opiskelija osaa säätää kolmea ulostuloa samanaikaista, varsinkin, kun kaksi näistä on toisensa poissulkevia.

Silti itse ajavan auton tekeminen on tavattoman vaikeaa, koska päätösten automatisointi on tuskaisaa. Koska painan kaasua ja miten paljon? Mihin suuntaan käännän rattia ja kuinka paljon?

Auton ohjaamiseen liittyviin päätöksiin tulee dataa monesta lähteestä. Mitä ympärillä tapahtuu? Millaisia rajoituksia on voimassa? Minne auton halutaan päätyvän?

Syy itsestään ajavan auton isoihin kehitysaskeliin on, että käytössä olevat työkalut ovat parempia keräämään ja analysoimaan saamaansa dataa. Ohjaavien algoritmien ei tarvitse olla valmiiksi ohjelmoituja kaikkiin mahdollisiin tilanteisiin, vaan kone itsessään oppii. Edistysaskeleet ovat nimenomaan päätösten, eivät toimenpiteiden automatisoinnissa.

Päätökset syntyvät datan avulla. Siksi suosittelen kaikkia automaatiosta kiinnostuneita aloittamaan datasta. Olennaista on ymmärtää mitä dataa yrityksestä löytyy jo nyt, mitä muuta dataa voidaan kerätä ja miten laadukasta kerätty data on. Data määrittää millaisia päätöksiä sen avulla voi ja kannattaa automatisoida.

Yhteenveto kaavan muodossa: automaatio = data + algoritmi + toimenpide.