Chief Notion Officer

I’ve been thinking a lot about corporate knowledge management systems recently.

If we think about a company as an organism, then a knowledge management system is essentially the (collective) brain that keeps that organism alive and running. A corporate knowledge management system should contain every single bit of codifiable information within the company resulting in a library of all projects, processes and procedures.

In an ideal state, it is the single source of truth that helps to inform every individual in the firm about what everyone else is up to. Information should be easy to add (input) as well as easy to search and find (output) resulting in quick knowledge transfer between different employees.

In reality, however, this hardly ever is the case. As anyone who has ever worked at a larger company can attest to, company knowledge bases always end up being a huge mess.

What starts with a neatly organized Confluence wiki, over time morphs into a multi-headed monster consisting of millions of notes and documents that live across Google Docs, Dropbox Paper, Asana and half a dozen different wiki tools. Most docs will be outdated, some will contradict others and the one you are really looking for only shows up on page 14 of your search results.

It seems like things usually start to fall apart once a company surpasses the Dunbar number of 150 employees. This is probably when people start to realize that all the different documents of explicit knowledge they were amassing over the years have been held together with implicit knowledge.

It’s easy to find – and understand – the right documents when you know every other person in the company, but once you’re past that point, you need a system to organize all the data so that people can make sense of it.

The idea behind tools like Notion is to solve this problem by using just one tool for all your different knowledge documents. Instead of Google Docs AND Asana AND Trello AND Airtable, you just do everything in Notion. This reduces complexity because you don’t have to switch and search across different apps. At the same time, Notion forces you to think about a system that makes information easy to find with its folder-like structure and links between different databases.

I’ve never used Notion with more than half a dozen people myself, but from what I’ve heard from people at larger companies, Notion knowledge bases also don’t scale very well beyond a certain number of users. Once too many people start contributing to it, things become bloated and unnavigable.

A friend at Stripe recently suggested – half-jokingly – that we should hire a librarian to organize all our internal data and documentation. The more I think about it, the more I like the idea. Perhaps every company should hire a Chief Notion Officer once it hits 100 employees?!

An alternative approach to Notion is a knowledge management system that can live across different tools and without active manual curation because it’s based on really powerful search. The folder structure of your Google Drive, for example, doesn’t really matter because looking up documents via search is faster and more convenient. Meta search tools like FYI are supposed to offer the same but across different productivity tools.

But again I’m skeptical that this really works beyond a certain amount of users (and thus documents). I remember even Google’s internal search engine doing only a mediocre job of surfacing the most relevant documents (and even if it did you weren’t sure if there wasn’t a better or more up-to-date version of it).

I’m sure we’ll get there eventually, but until then we probably need a mix of automated search and manual human help – which is where Slack comes in. I’ve always thought Slack plus Notion plus Spoke would make a really powerful product (and I’m surprised Slack hasn’t made any major acquisitions in this space).

If you think about it, Slack is basically a search engine powered by humans: Most Slack messages are just questions. It’s 911 for when everything else fails. So if Slack had access to your entire knowledge base, it could answer at least the most commonly asked questions automatically. The rest would still get answered manually by the channel participants. Or your Chief Notion Officer.

Do you have thoughts on this topic? Please leave your feedback here. Thanks to Jan König for reading drafts of this post.

Twitter launched their version of Stories last week (called Fleets) – some initial thoughts:

>_ Books

Order Without Design (Alain Bertaud) ░░░░▓░░░░░░░░░░░ Progress: 25-37%

A History of Future Cities (Daniel Brook) ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓ Progress: 0-100%

Breasts and Eggs (Mieko Kawakami) ▓░░░░░░░░░░░░░░ Progress: 0-6%

Blood and Oil (Bradley Hope & Justin Scheck) ▓▓▓▓▓▓▓▓▓▓░░░░░ Progress: 0-64%

Working in Public (Nadia Eghbal) ▓▓░░░░░░░░░░░░░ Progress: 0-12%

>_ Recommended Articles

Is the Internet Different? (Stratechery)

No More Clown Shit (Mike Solana)

The German Elon of the 70s (Moritz Müller-Freitag)

The Command Line Comeback (Gaby Goldberg)

Airbnb: The Disaster Artist (Mario Gabriele)

>_ Recommended Podcasts

Jimmy Wales on Systems and Incentives (Conversations with Tyler)

Emmett Shear – The New Language of the Internet (Founder’s Field Guide)

Top Artists: Sufjan Stevens (35 plays), Franz Joseph Haydn (27), Stafford Bawler (26), Paul Kalkbrenner (22), Royal Blood (16)

> Hello > This is my lifelog and digital playground

01 Intro

If you’ve been following this blog for a while, you probably know by now that one of my favorite topics to think and write about is “status signaling”.

Signaling explains most of our everyday actions: what clothes we wear, which universities we pick and which religion we subscribe to. Everything has a hidden signaling component with which we communicate our desired tribal affiliation.

In Signaling-as-a-Service, I described the implications signaling has on the monetization of software businesses. For many traditional industries, monetizing the display of status is not a new concept. A Rolex watch, for example, is not better at telling the time than a cheap Casio watch. But a Rolex reveals something about its owners’ wealth and, thus, their status in society. It’s that status message that explains the difference in price.

Similarly, driving a Prius says something about your views on climate change. A Make America Great Again cap reveals something about your political affiliations. And Nike athletic wear signals a healthy, pro-active lifestyle.

Software is at a crucial disadvantage compared to these physical products because of its intangibility. A fitness app also signals a healthy, pro-active lifestyle, but no one can see it because it only lives on your phone. Everyone can see your Nike gear whenever you wear it in public. Software can’t offer the same benefit. It doesn’t have a signaling distribution channel.

This is why there is no software equivalent of a Rolex watch or a Louis Vuitton handbag. People aren’t willing to spend money on things other people can’t see they spent money on.

But it doesn’t have to be that way. As software is eating the world, the lines between physical and digital products are becoming increasingly blurry. As I have pointed out in my original essay, one way for software companies to solve the signaling distribution problem is to add a physical element to their software product.

In this post I want to explore this idea a little bit further. Specifically, we’ll look at neobanks – and their opportunity to monetize credit card signaling.

02 Neobanks

In the last couple of years we have witnessed the birth and rise of a new startup vertical: neobanks.

Neobanks differ from traditional banks in two ways:

1) Rather than relying on a physical branch network, the entire banking experience is managed via an app

2) Instead of the “how do you do, fellow kids”-cringiness that ad campaigns of traditional banks usually invoke when they try to appeal to a younger audience, neobanks are actually perceived as cool. In fact, many of them feel more like lifestyle brands than banks or tech companies.

Interestingly though, neobanks still use one very traditional banking element: physical cards.

At first glance, this might seem counterintuitive. If you are building a mobile-first bank, why not offer virtual cards and let users pay with their phone? Why go through the hassle of producing and shipping physical cards?

The answer is – you guessed it – signaling.

Think about it: Paying for things (offline) is a social activity. It’s an interaction between at least you and a cashier or waiter. But ideally, in a dinner scenario for example, you are surrounded by other people you want to impress: a date, a group of friends, or work colleagues.

This makes the moment you take out your card to pay the bill a great opportunity to make a statement and build social capital.

If you look at neobanks out there today, it’s pretty obvious that signaling is in fact one of the main benefits they offer – and almost the only thing they monetize (apart from interchange, of course):

Neobanks are popping up like mushrooms after the rain at the moment and it’s unlikely that this trend will end any time soon. Thanks to banking-as-a-service providers, we’ll likely see a lot of non-banking-companies add banking functionalities and cards to their product offering.

There’s an old Twitter joke that every app evolves until it eventually becomes a chat app. The 2020 version of that joke is that every app evolves until it eventually becomes a bank.

When I did some research on credit card designs recently, I was surprised by the sheer amount of different neobanks already in existance. And yet, even though almost all of them offer well-designed cards, it’s shocking how similar they all are. It seems like all of them are focusing on the same target audience instead of differentiating their signaling messages.

Let me explain.

03 In-Groups, Out-Groups and Artificial Scarcity

In every signaling scenario there are two possible target audiences: An in-group and an out-group.

The in-group is the tribe you want to join and signal your affiliation to. The out-group is everyone else – people you want to distance yourself from.

iMessage is a great illustration of this: the chat bubble colors clearly indicate who belongs to the in-group (blue = iOS) and who is part of the out-group (green = Android).

It’s important to note that signaling in iMessage is limited to the in-group since these color codes are only visible for iOS users – Android users can’t see who in the group is using which operating system.

Signaling, however, grows stronger the larger the out-group is – as long as the out-group knows about the in-group. This is why luxury car manufacturers deliberately extend their advertising campaigns to people who will never be able to afford their cars: they are increasing the size of the out-group by educating people about the in-group.

At the same time, brands need to control the size of the in-group. The more exclusive the in-group, the higher the signaling strength and, thus, the monetization potential of a customer.

The easiest control mechanism for the size of the in-group is price. If you set the price high enough, few people will be able to afford the product. Ironically, this, in turn, justifies the high price.

Alternatively, companies create artificial scarcity by setting a hard number on supply. Limited supply creates FOMO and hype which increases the size of the out-group and results in higher social status for members of the in-group. Artificial scarcity explains the price of Bitcoin, Pokémon trading cards and why people spend hours queuing in front of Supreme shops.

The problem with keeping the in-group small is that it also limits the number of potential customers and, thus, overall revenue potential. Companies need to walk a fine line between maximizing the number of customers while simultaneously maximizing the number of people they can (afford to) exclude.

04 What Neobanks Should Build

The problem with neobanks today is that they all focus on the same in-group. Here are the premium cards of some of the largest European challenger banks – notice any difference?

It seems like everyone is trying to become the Apple of Banking – including Apple itself. The signaling messages are all about displaying economic power.

But we are slowly seeing new banking apps that are focusing on different audiences. For example, there are now a handful of “green” neobanks that help users signal environmental altruism.

Or how about this Razer Card targeted at the gamer community?

The question for these companies and their investors is whether the in-group is big enough to justify building an entire bank around it. Making the unit economics of a bank work requires a certain amount of users, but as we discussed earlier, the signaling strength decreases as the size of in-group increases.

So how do you solve this problem? By introducing multiple in-groups.

See, the current model looks like this:

(In fact, given how undifferentiated most of the offerings and cards are, there are actually multiple neobanks within the same small in-group bubble.)

But what if one bank would target multiple, different in-groups?

For example, what if N26 had dedicated cards for soccer fans, hip-hop enthusiasts and gamers? Instead of focusing on just one signaling audience, their total addressable market would massively increase.

The way they would target these audiences is via brand collaborations. N26 does not have the necessary reputation in any of the above-mentioned areas to build credible signaling messages. It would not be able to build attractive in-groups on its own – but other brands could lend N26 their social capital.

Apple has long worked with RED, IKEA recently teamed up with Virgil Abloh, and Nike partners with Headspace. Why wouldn’t this concept work for neobanks?

What would N26 x Manchester United look like? Or Chime x Supreme? Or Revolut x 100 Thieves?

Because of a bigger target audience overall, individual in-groups could be kept smaller. Cards could be released as limited edition drops transforming them into collectibles, which would justify a higher price tag per card.

It’s worth noting that different signaling audiences are not mutually exclusive. We don’t just subscribe to a single in-group – our identities are prismatic. This means that some users might purchase multiple cards to signal to different in- and out-groups resulting in even higher expected LTV per user.

A few neobanks have already started to experiment with brand collaborations and limited edition cards (see Cash App x Hood By Air or Point x Laura Berger). I expect there will be a lot more once neobanks realize what most of them really are: Signaling-as-a-Service companies.

05 A Closing Ask

What card designs and neobank collaborations would you like to see? Let me know in this Twitter thread – I’d love to hear your ideas!

And if you’re an (aspiring) 3D artist or designer: Would you like to bring some of these card ideas to life? There will be a follow-up post to this essay featuring the best card mock-ups. Send me a Twitter DM or email (hello at julianlehr dot com) if you want to learn more.

Thanks to Brandon Jacoby, Jan König, Mario Gabriele, Max Cutler and Zack Hargett for reading drafts of this post.

Today marks the 77th day since I got onboarded to Clubhouse.

Clubhouse, for those not familiar with it, is essentially an audio-first social network. It’s kind of a mix between Reddit and a podcast. An interactive radio show. The app lets you jump into different chat rooms and participate in – or just listen to – live audio conversations around different topics.

It’s an exciting product. And yet, in these last 77 days, I have actively used Clubhouse exactly three times.

The problem with Clubhouse is that you can only listen to conversations live as they happen. Given that the majority of the current user base is in North America, the most interesting conversations usually happen in the middle of the (European) night when I’m asleep.

The first thing I see on my phone after I wake up are a handful of Clubhouse notifications telling me about the all the interesting conversations I missed. I wish I could just download these conversations as podcasts and listen to them later.

Some have pointed out that the live nature of Clubhouse is exactly what makes it so special, comparing it to the ephemerality of Snapchat. And while I disagree on the Snapchat comparison (ephemerality ≠ synchronous creation and consumption), I do think it makes sense for Clubhouse to find its own native format rather than compete with podcasts directly.

While Clubhouse feels like live podcasts at the moment, I think over time it will probably evolve into something else. Something more unique.

The current state of Clubhouse reminds me of the early days of Twitter: People knew it was a unique new form factor, but they didn’t know how to use it yet. Most tweets were just short status updates. It took some time until the platform found its current form and use cases.

One of those use cases is “Twitter as a second screen”: Live commenting TV shows and sports events. I strongly suspect that this will become one of Clubhouse’s main uses cases as well.

As I pointed out in Airpods as a Platform, I see audio primarily as a secondary interface: You listen to music while you’re working out, for example. You consume podcasts while you are driving or commuting. You talk on Discord while you’re playing a game.

Audio is a medium that supports and augments other activities.

So instead of thinking about whether Clubhouse should make conversations available as downloads, a perhaps more interesting question is what activities could best be augmented with live audio? What does Clubhouse as an audio layer for other content look like?

The most obvious use case seems to be sports (and other events that have to be consumed live). I would love to replace the audio track of my TV sports broadcasters with a select group of (Clubhouse) experts whose opinions I’m actually interested in.

I wonder what other events or activities this would work for. Do you have any ideas?

I set myself 24 goals for this year and completed 9 of them (38%), which is a significantly lower success rate compared to my 2019 and 2018 lists (60% and 56%, respectively).