Broadly speaking, an NFT (Non-Fungible Token) is a representation of an asset (digital or physical) implemented on a blockchain. Even though it uses the same technology as cryptocurrencies, unlike cryptocurrencies NFTs are not liquid and cannot be divided. For example, 5 euros are still 5 euros whether they are banknotes, coins, a check, or your account balance. NFTs, however, represent indivisible assets (non-fungible). They can represent unique one-of-a-kind items, like the deed to your house that represents your house, or repeatable items with limited supply, like collectible cards in a set, or stamps in this case. Remember that an NFT is just a token, a symbol, a ticket. It is not the house, it is the deed. The value proposition of NFTs is that strong blockchain cryptography proves you are the real owner. So, instead of a notary or a government registry, you get a decentralized network plus a bunch of cryptographic algorithms proving it.

Blockchain has a bad reputation because it can consume more electricity than countries such as Argentina, but that is basically a Bitcoin issue. Ethereum no longer has that problem since the Ethereum 2.0 transition a few years ago. Also, Correos’ NFT runs on an alternative network called Polygon, a chain similar to Ethereum but much faster and more efficient (including energy efficiency).

In that sense, Correos did not do too badly. But the two main reasons to use blockchain are transparency and decentralization. In the rest of this post I will analyze these crypto stamps from those perspectives, and finally whether people are actually using them, and how much.

Transparency

This already starts poorly: the bare minimum transparency you should expect from something blockchain-based is publishing the smart contract address, and they did not do that.

Not publishing the contract address is like saying you have a transparency portal but not saying where it is. It hides the essential information users need to interact with the contract.

As someone who researches this stuff, I managed to find the contract on my own. Its address was 0x8fA19F4316dF640e14b30B2fE749cbdd79Da9335.

Update June 14, 2024: Some weird stuff happened and they migrated the contract to another address, in a rather clumsy way.

They also do not publish the smart contract source code, so users cannot audit how it works or whether it is implemented correctly. There could be a bug that allows someone to grab all crypto stamps, and we might never know.

Even if you do not know programming, a common practice in this ecosystem is paying someone to audit contract code, yours or someone else’s.

At least blockchain transfers are transparent, so we can still see who owns these exclusive Mortadelo NFTs.

Decentralization

On the decentralization side, the solution is also quite disappointing. Normally NFTs use decentralized standards that let you use them across the wider web3 ecosystem: set one as your social media profile picture, show it in a virtual gallery, use it in games, and so on. With these crypto stamps, you must use the Correos web app to view the associated image. When the consultancy firm maintaining that website drops support in a couple of years, you may lose access to your crypto stamp.

If crypto stamps are neither transparent nor decentralized, why do they exist?

I guess to increase stamp value and sell more units, right? We do not know how many stamps have been sold, but we can track how many were “redeemed” (or “claimed”) on-chain, and what kind of users did it.

This post updates automatically with new data. Last update: .

Drum roll… a total of crypto stamps have been claimed, an average of per day.

However, that does not mean there are as many people as stamps. In reality only different wallets hold at least one crypto stamp. We cannot claim these are unique users, because just like with email there is nothing stopping one person from creating multiple accounts. In crypto this is normal: keep one wallet with a very strong key for long-term storage, and another easier-to-use one (for example on your phone) so if it gets hacked, losses are limited.

Each user that holds at least one crypto stamp is called a holder. Although each holder has an average of stamps, this is the classic “if I eat two chickens and you eat none, on average we ate one each” problem.

The reality is that one user has way more NFTs than everyone else: , who holds crypto stamps. Meanwhile, most users ( ) hold one or two.

Another interesting question is whether these users had stamps from other collections. In other words, were they already familiar with this technology, or did Mortadelo bring them in?

Curiously, the wallet with the most crypto stamps had no previous NFTs, though maybe that person has another wallet with some; we can never know. Maybe it is a stamp seller from Plaza Mayor, who knows.

Overall, only of users had ever held at least one NFT in their wallet. We do not even know whether they bought those NFTs or received them as gifts (or spam), so we cannot claim those few users are true crypto enthusiasts. What we can say confidently is that or more had never used NFTs before. What this means is that this product did not manage to attract crypto enthusiasts to the stamp collecting hobby, but the other way around.

Note that I am checking not just Polygon (where these crypto stamps live), but all chains indexed in Dune Analytics.

Money talk

We all know crypto can move serious money, with some collections reaching millions of dollars, but how much money do these crypto stamps move?

So far there have barely been any transfers, and none of them involved money through auction houses, so from that angle we cannot say whether owning a crypto stamp has any value beyond the physical stamp.

Still, we can estimate the profit this strategy has generated for Correos. Each unit costs 15€ and has a face value of 10€, meaning you can use it for postage up to 10€ and Correos keeps a 5€ markup.

Since stamps have been sold so far, Correos has made at least € in markup revenue.

Depending on whether the stamp is eventually used and for which postal product, real profit could be higher.

There are likely many stamps that were bought but not yet claimed on-chain. Still, I think it is fair to assume that if a buyer did not register it, then the crypto part added no value for that person.

Speaking of money: while I am not an expert in Spain’s public procurement platform, it seems Correos has spent at least EUR across contracts to launch this collection. That said, part of that budget went into business-model research and framework design, so it could be amortized over future collections.

You can download the procurement data I collected here. If you spot anything wrong, please let me know.

Conclusions

In my humble opinion, Correos arrived very late and somewhat awkwardly to the 2021 NFT boom (already three years ago). On top of that, the lack of decentralization and transparency, two core values in this ecosystem, may make users less likely to buy crypto stamps.

Maybe they will recover the investment in future collections, hopefully with better implementation choices, because right now this is still far from what could reasonably be called web3. On the plus side, the website seems fairly accessible and works well.

That said, maybe this crossover has made at least one crypto nerd start collecting physical stamps and become a lifelong customer.

Data was obtained through Dune Analytics, a blockchain data analysis platform. You can find the queries and datasets used here.

A recommendation system, also known as “the algorithm,” is a system designed to predict how you will rate items like Netflix series, YouTube videos, or Amazon products based on your past ratings. It goes beyond just your explicit likes or dislikes and takes into consideration factors such as watching a video until the end, which can be even more influential in understanding your preferences.

In this article, I won’t go into detail about how these systems work. There is plenty of information about it available online, and I want to keep this article concise. You can find some videos and articles I found interesting at the end of this article.

In simple terms, recommendation systems are typically machine learning systems that aim to find groups of users with similar preferences and recommend items within those groups. E.g: if Alice and Bob have similar tastes and Bob discovers a new music group that he enjoys, probably, Alice will also like that group.

It is quite common for these systems to not know the content or genre of a video or song. They solely consider the similarity of tastes between Alice and Bob. The recommendation systems don’t take into account the specific details of the content but rather focus on the alignment of preferences between Alice and Bob.

However, the ultimate goal of any machine learning system is to optimize something. Is it for “fun,” “entertainment,” or “learning”? Well, most likely, the companies that design these algorithms decide to optimize them for generating the highest possible amount of revenue. In other words, they aim to keep you hooked on their recommendations for as long as possible. And they are incredibly effective at achieving this goal.

Sometimes, we want to break free from the comfort zone created by “the algorithm” and explore new things. We might want to start buying fantasy books even if we’ve never read one before or listen to some electro-psychedelic cumbia, if such a genre exists. However, taming the algorithm to show us exactly what we want can be extremely challenging. It often leads us either to mainstream content or down a rabbit hole with no way out, eventually leading us to unexpected and undiscovered niches.

For these reasons, in this article, I present 6 alternatives to recommendation algorithms:

This article is alive and was updated on January 22, 2026

1. The Curator: Podcasts, radios, blogs…

I will start by talking about Radio 3, from whom I borrowed the slogan “death to the algorithm!” for the title of this article. For readers outside of Spain, Radio 3 is a Spanish public radio known for its alternative but wide programming. In their last publicity campaign, they decided to emphasize human curation and DJ selection rather than relying on algorithms for music recommendations.

A great option for discovering new things is to seek out knowledgeable individuals who specialize in discussing those topics. Read blogs, listen to radio shows and podcasts, watch videos and vlogs, ask people you know, read articles in magazines—whatever works for you!

In addition to discovering new things, actively engaging in your favourite hobbies can provide a fresh perspective and be an enjoyable hobby in itself. The mere act of reading about a topic can be entertaining and fulfilling. For instance, when it comes to anime and video games, I personally enjoy reading both online and offline magazines. In addition to discussing manga and anime, they also feature various articles that analyze Japanese culture and the industry itself. It’s incredible how many titles I wouldn’t have discovered if it weren’t for their coverage.

When it comes to music, in addition to their live radio broadcasts, Radio 3 uploads all of their shows in a podcast format so you can listen to them whenever you want. Some programs focus on playing music with minimal commentary, while others feature interviews or analyze the latest releases of the week. Lately, I’ve been hooked on El sótano (The Basement) and Melodías Pizarras (“Pizarre” Melodies, a pun with bizarre and the name of the host) which expose me to music that isn’t readily available on many platforms.

In the end, you end up building a roster of “influencers” to whom you can return to discover new things.

2. Roll with playlists, mixes, series…

However, it is true that sometimes we just want to watch a movie without delving into an interesting program about the director’s inspirations or related topics. Similarly, there are times when we simply want to hit play and listen to music without considering the specific song, album, or artist playing at that moment.

That’s why film series, playlists, and remixes were created. They are curated packages of content that someone thought would go well together.

In Deezer, for example, you have playlists created by specialists based on moods, genres, eras, or whatever you prefer. Additionally, there are plenty of community-created playlists available through the search feature. If nothing satisfies you, you can always rely on automatic mixes and let the algorithm guide you. On the other hand, Filmin completely bypasses algorithms and exclusively offers handcrafted collections and film series with titles like “Time for Elections,” “00’s Icons,” or “California Dreamin’.”

Personally, when it comes to music, I love the hour-long videos on YouTube from the channel My Analog Journal. The channel umetokakun also offers mixes with creatively titled playlists such as “Citypop to Escape Your Feelings” or “Rare Psychedelic Soft Indie Rock to Lie in the Snow and Contemplate Life.” Just the way the songs are presented, including the titles, their order, and the subtle transitions, creates an experience in itself that surpasses any algorithm.

3. The snowball effect

The snowball effect is widely used by scientists to discover new articles to read. In our case, you go to the citations and references of an article that interests you to discover new interesting articles. In those articles, you go back to the references again to discover even more articles, and before you know it, you experience exponential growth in discovery.

If we want to apply it to entertainment, we can look for things that have something in common with what we just read/listened/watched. We can search for more albums and songs from the same band (or even the same record label), more books from the same publisher, more movies from the same director or a specific actor, more TV series from the same production company, etc. Before you know it, you’ll have a long list of things you want to explore, and you’ll have learned a bit of history and culture along the way, which can come in handy for trivia games.

For example, Bandcamp allows you to explore the tags of an album, where you can discover genres you didn’t even know existed.

4. Platforms and user-generated content

There are user-generated content platforms like MyAnimeList where users can make recommendations based on what they’ve watched. Usually, these recommendations can be accompanied by a brief text where you justify why you would recommend that. For books, you also have Goodreads. And for movies and series, there’s Letterboxd. In the music world, you can rely on the old and trustworthy last.fm.

Additionally, it’s not necessary to explicitly visit recommendation pages. You can find room for suggestions on any social media or platform. Try searching on Google for “Reddit recommendation [TOPIC]” and you’ll be surprised by the good results you get. And if all else fails, you can always ask for recommendations yourself.

5. Judge a book by its spine

It is often said, “Don’t judge a book by its cover”, but if that were true, then why do books have covers? I propose letting ourselves go a little more and being more judgmental, not overthinking things and judging the book by its spine.

In this accelerationist society, we are optimizing even our leisure time, and it seems necessary that every minute we spend consuming content is of the highest possible quality and provides us with the most value. We end up prioritizing watching things that are “of better quality” over things we would like to watch or simply ignoring something because “it doesn’t ring a bell” before even considering whether to watch it.

The next time you see the cover of a movie that catches your eye, or a book with a very interesting title, take a look at it even if you’ve never heard of it before and you’re not sure if it’s the movie of the year or not.

6. Transparent algorithms

Saying that a website has no algorithms is like saying that fruit has no chemicals. Organic matter is composed of molecules, and software is composed of algorithms, it’s a fact.

However, just as there are chemical compounds to avoid for not being particularly good for health, there are also better algorithms that can help users discover what they want.

An example of this is music-map.com, which shows you a wide range of artists similar to a given artist, where the distance represents similarity.

Every Noise at Once is a similar website that showcases a huge variety of music genres, and you can see which ones are similar to each other. Additionally, by clicking, you can listen to an audio sample and see if you like it.

Certainly, any algorithm that shows you why it recommends you something or allows you to select the starting point will be better for expanding your horizons.

Conclusion

Although recommendation algorithms are powerful tools that help us navigate through the vast amount of content available on our favourite platforms, sometimes we desire to escape their influence and discover new things on our own. Fortunately, there are other options that empower us to take control of our choices and broaden the horizons of our entertainment.

If you think there’s something else I can add to this article, feel free to leave a comment or send an email to david [at] ddavo.me.

Further reading

• The entertaining 5-minute video channel Half as Interesting presents Spotify’s Mathematical System for Determining Your Music Taste.
• How Recommender Systems Work: A 10-minute video that delves into the mathematics behind the subject.
• To celebrate reaching one million subscribers, Answer in Progress has created an extensive (50-minute) yet engaging video on the history of the YouTube algorithm, explaining in the process how its opaque system works.
• Towardsdatascience has a really great introductory article to recommendation systems