Forem: Jega Pradeeba

Monzo — A Product Strategy Case Study

Jega Pradeeba — Mon, 22 Jul 2024 06:14:09 +0000

Key Takeaways

Built for scale - Monzo's infrastructure uses a modular, fragmented services infrastructure (microservices approach), utilizing advanced tools like AWS and Kubernetes to ensure agility, resilience, and scalability.
Designed for virality - Its intuitive mobile app, eye-catching 'hot coral' debit cards, and referral programs have not only attracted users but also encouraged them to share their positive experiences with friends and family, creating a viral effect that has propelled Monzo into the mainstream of modern banking.
Rooted in transparency and community - Monzo stands out for its commitment to open communication and engaging with its user base. This approach has helped foster a strong sense of trust and loyalty among its customers, and distancing itself from traditional banking.

Introduction
The essence of any product is the feeling users get from it. For Monzo and other neobanks, the core tenet of that feeling is trust. That trust needed to take 2 forms though: users needed to trust that Monzo would provide them with the functionalities they would expect from a normal bank (namely if I leave my money here, can I trust you to look after it?), and at the same time, can users trust the startup bank to also represent the complete opposite of what traditional banks represent (frustration, time-wasting, lack of transparency).

In this case study, we look at how Monzo was able to address these two points, specifically looking at its technical product strategy and product marketing strategy, and how these helped Monzo shift the banking landscape.

I hope you enjoy the read.

The founding of Monzo
Monzo, a neobank (digital-only banking platform) based in the UK, has redefined the landscape of banking with its customer-centric approach and innovative technology. Founded in 2015 by Tom Blomfield, Jason Bates, Gary Dolman, Paul Rippon, Jonas Huckestein, it quickly distinguished itself by offering a seamless, intuitive banking experience.

The founding team had a strong mission driving them of simply making banking better, and they had the experience to help get them there with three of the five being early members of Sterling Bank (another neobank), and Tom Blomfield (CEO of Monzo) having founded another fintech company, GoCardless, incubated at Y Combinator in 2011.

“Tired of the way traditional banks do business, we believed we could build a real alternative. One that’s totally transparent, treats people fairly, and caters to the way we all actually live our lives.” - Tom Blomfield, CEO of Monzo. [1]

Starting initially as a prepaid card combined with a digital app to track expenses, Monzo evolved into an official bank in 2017, and today boasts 7.5 million users[2, making it the UK’s 7th largest bank by customer count.

Product Strategy
Monzo’s success was never down to solely how good its marketing was nor just its technical architecture, but a combination of both sides of the business and the synergy between them.

Technical Product Strategy
From the beginning, Monzo was building to scale. The company’s strategy involved the deployment of robust cloud-based solutions, agile software architectures, and the ability to generate insights from their data.

This approach was crucial for two main reasons:
Banking is a ubiquitous service: Success in banking requires the capacity to handle large numbers of customers, and vast numbers of transactions per customer, efficiently. In addition, as we will see later, Monzo used referral systems to market the product. For any one user who refers Monzo to another two users, each one of them can refer another 2 users, and soon you get exponential growth. Whilst that’s great from the marketing KPIs, it can be a real headache if your product infrastructure is not set up to handle that kind of exponential growth in demand from users.

Customer Attraction to Neo-Banks: The primary appeal of neo-banks like Monzo lies in their ability to streamline and simplify banking processes, thereby eliminating common frustrations. If Monzo had encountered operational issues due to a high number of users, it would have contradicted this value proposition, deterring customers and diminishing their trust and satisfaction. Once trust is lost in products, particularly financial products, it’s very difficult to get back. So in other words, Monzo had no room for error.

Bottomline, this foresight of building to scale was necessary to prevent operational bottlenecks that could erode customer trust, a key factor for any financial service.

Amazon Web Services

“By using AWS, we can run a bank with more than 4 million customers with just eight people on our infrastructure and reliability team.”
Matt Heath, Distributed Systems Engineer, Monzo [3]

Amazon Web Services (AWS) is a comprehensive cloud computing platform, providing a wide range of services like computing power, database storage, and content delivery. It's known for its scalability, reliability, and flexibility, making it a popular choice for businesses of all sizes. By leveraging AWS's cloud infrastructure, Monzo could manage its banking services with a lean team, overseeing operations for millions of customers. There were 2 main angles for facilitating this:

First, regulatory compliance, as AWS's reputation for meeting the Financial Conduct Authority's (FCA) guidelines, such as through AWS CloudTrail, made it a trustworthy choice for hosting FCA-regulated workloads.

Second, Monzo adopted a technical strategy centered on a microservices and containerized architecture, leveraging the scalability and agility afforded by this design (i.e. a flexible system made of small, independent components that expand and contract with demand). By harnessing the power of AWS's cloud environment along with Kubernetes for streamlined container management, Monzo was able to efficiently operate a multitude of microservices[4], enhancing both performance and reliability.

The use of this architecture is like constructing with many smaller Lego bricks as opposed to one big “monolithic” brick. Each microservice is a separate 'Lego brick', small and manageable on its own. When combined, they form a larger, more complex structure. This modular approach enabled Monzo to efficiently build and adjust its digital banking services, piece by piece, to create a cohesive and flexible system, and adapt as it learned about user behavior and needs.

This infrastructure facilitated Monzo's ability to provide “real-time” banking services, a stark contrast to the traditional banks' slower processes, and supported Monzo's exponential growth in services and customer base. The microservices architecture also enabled rapid deployment of new features and quick adaptation to changing customer needs, underlining the importance of flexibility in product development.

[A more detailed journey of Monzo’s backend architecture which can be found [here].

Google BigQuery

“As a tech team we value simplicity, and with Google BigQuery we’ve created the simplest and most scalable setup we could imagine.For four or five years, banking conferences have discussed the need to bring all data together in one place for analysis. With Google BigQuery, we’re actually doing it.” - Dimitri Masin, Head of Data at Monzo [5]

One potential drawback of a microservices architecture, is that it can complicate analytics compared to a monolithic architecture - i.e. because data is fragmented across independently operating services, it can be more difficult to gather data and draw insights.

Google BigQuery is a fully managed, serverless data warehouse and analytics platform that allows organizations to analyze large datasets in real-time. Monzo's utilization of Google BigQuery enabled them to consolidate their data, ensuring that all teams had access to the same up-to-date information. This unified source of truth not only simplified data access for new team members but also facilitated more efficient and scalable analytics, even as Monzo's user base continued to grow.

Furthermore, using BigQuery also reduced the gap between engineering, data, and business, as it enables non-technical staff to self-serve 85% [5] of their business intelligence queries without consulting the data team:

“We do all of our analysis on the fly because Google BigQuery can execute such gigantic joins of tables at speed. That’s an incredible advantage. We define and analyze segments as we think of them, instead of creating an ETL (extract, transform, load - a more traditional/time-consuming process to gather insights from data) process and realizing the next day that we want something else”, Dimitri Masin (Head of Data).

For example, Monzo’s data team set up dashboards via BigQuery for customer support, showing trending issues users had. They were able to identify the most frequently recurring problems by looking at customer behaviour on the app just before the put in the support request. This granular insight on user behaviour and where things were going wrong, allows them to reduce the number of support requests they received by 50% over 10 months. Again, the impact this alone would have on the trust and confidence users have with Monzo is significant.

What’s interesting, is not just taking this strategy from a data and business-centric view, but also purely financially. “In other companies of our size you need a data engineering team of at least two to four people constantly on-hand to maintain and run day-to-day analytics infrastructure,” says Dimitri. “Google BigQuery doesn't need a dedicated team to maintain it. In the two and a half years since we set up the solution, it’s been so robust and so scalable that it’s required no maintenance work whatsoever.”

The bottom line is that Monzo leveraged Google’s BigQuery to overcome the drawbacks of a distributed microservices backend architecture, giving them a single source of truth that even non-technical staff could leverage.

Opinion:
One thing you may have noticed is that by leveraging services like AWS and BigQuery, the Monzo team was able to maximize their technical capabilities whilst minimizing the size of the team, which is often a startup's biggest expense.
Despite Monzo doing this back in 2016/2017, as such services expand and improve, it’s likely this lean set-up will be how most startups (and even more established companies) operate.

Other Points
Another notable mention is their commitment to a mobile-first approach. In contrast to many traditional banks, which transitioned from non-digital to digital services optimized for web/desktop computers before eventually focusing on mobile, Monzo prioritized mobile usability from the outset. This approach reflects a forward-thinking perspective on banking services, acknowledging the growing importance of mobile devices in modern banking. It's worth noting that even today, several major banks struggle to offer a seamless mobile experience.

Opinion:
I think Monzo understood that when it comes to banking, users just want to get things done. And I think that’s the sweet spot for mobile services in general - mobile apps are primarily for task-orientated activities (outside of social media that is). This is in contrast to more immersive activities like media consumption, in-depth research, or leisurely shopping, which often suit desktop environments better - e.g. it is why Amazon did not need to be mobile first. If traditional banks had adopted a mobile-first strategy earlier, they likely would have given neobanks like Monzo a better run for their money.

I believe this also highlights the importance of building a flexible infrastructure from the ground up. Moving from non-digital to web banking to mobile-first, traditional banks were always on the back foot. But how we as consumers interact digitally is always changing, beyond mobile we’re already seeing the application of VR and AI pins. It’s easy to say banks should have been mobile-first from the beginning, but it is difficult to anticipate trends - so I don't think we should. Instead, I think it is about building a flexible infrastructure that can adapt to new use cases.

Product Marketing Strategy
User Experience
While UX/UI design is typically considered an integral component of technical product strategy, its role in Monzo's case goes beyond functionality. It plays a critical role in shaping the brand's identity and molding customer perception. Monzo's user-friendly design isn't just about ease of use; it serves as a psychological bridge connecting the simplicity of banking tasks with the overall user experience. This aspect of design has been instrumental in establishing a positive and enduring impression of the brand within its user base.

A great example is the onboarding process:

“Our vision is to let new customers create a Monzo account in minutes— anytime, anywhere. We want our customers to start the process as they enter a queue at their local coffee shop and have an account created by the time their coffee is served.”
Head of Marketing and Community at Monzo [6]

It’s worth remembering that the whole point of Monzo, and other neobanks, was to offer a new alternative to the frustrating processes of traditional banks, and so by that very premise, every activity done on Monzo needed to be easy, painless and frustration-free. During the setup process, Monzo faced high abandonment rates, particularly during online identity verification.

To address this, they partnered with Jumio, a software identity verification service. One significant insight during testing revealed that many new users abandoned the process when asked to take a selfie. Monzo recognized that users might not be in a suitable environment for taking a verification selfie, such as being at work or in a public place. To mitigate this, they implemented a strategy of sending reminder emails over the following days to encourage users to complete the process. This multi-touch approach, akin to the way Duolingo sends reminders to stay on track, significantly improved new account conversions.

Furthermore, Monzo's decision to leverage Jumio's backend infrastructure for identity verification, rather than building it in-house, resulted in a significantly faster verification process. Approximately 95% of accounts were verified within just 270 seconds. This accomplishment was crucial in achieving Monzo's goal of delivering a swift and effortless customer experience, especially when compared to the potentially lengthier verification processes offered by traditional banks.

Marketing Campaigns
The Golden Ticket
One of Monzo’s more famous marketing strategies was the golden ticket - a referral program to boost customer engagement and loyalty.

After launching its beta version in 2017, Monzo gave out "golden tickets" to existing customers [7]. These customers could then give these tickets to their friends, who could skip the waiting list and get immediate access to the Monzo app. The idea was influenced by the gamification and waitlist-style referral system from Robinhood, a popular online trading platform. This method proved highly effective in building customer loyalty, as studies show referred customers are 18% more loyal than those acquired through other means (plus referred customers are 25% more profitable per year than un-referred customers).

[Image source]

A screenshot of the waiting list to get the Monzo bank card when they were launching their beta in 2017/2018, and to the right a screen shot of the ‘golden ticket’ you could send to your friends to skip ahead in the queue.

The campaign was hugely successful with 40% of its signups in 2017 coming from the golden tickets alone, helping them push from 70k users in 2016 to 600k by the end of 2017 [8]. I think it is easy to stop here and believe that this cleaver marketing strategy was just that, clever marketing, but there are a few more nuances that are worth mentioning.

First, timing. The Monzo team did not push this campaign in 2016, when they were still perfecting the product. The campaign increased their number of users nearly ninefold, if they had done this any earlier when the product was not perfected, they would have dug their own grave. So you have to give the leadership team the props for actually having the patience to push only when they were confident and ready - something a lot of other startups fail to do.

Secondly, trust. As previously touched on, trust is the core emotion for financial products, particularly for neobanks, who have to deal with the cognitive bias that e.g. only traditional banks are safe. But this is particularly important for referrals. It’s one thing for you to take a chance, and leave your money with a new startup and things go wrong, it is a completely different thing if you told your friend or family member to leave their money in a startup, and things go wrong.

So the success of the golden ticket campaign was not just a testament to the clever marketing strategy itself, but it was another nod to just how good the product was, because people were telling their loved ones to join, which meant they had strong confidence in the safety and efficiency of the Monzo product.

Opinion:
I genuinely believe that this idea of gradually building consumer confidence is such a core tenet of their success: build product → test on a few thousand customers → perfect product → viral marketing campaigns.

It’s also worth noting that Monzo never came out of the gates being a fully-fledged bank. They began as a prepaid card, users could see the benefits of digitalising their transaction history in a user-friendly way, without forking over all of their money, and allowed Monzo themselves to collect data, analyse, learn, plan and build upwards. They eased consumers into using their product as a bank, gradually building up users’ confidence in them.

Design
Beyond just making the interface easier to understand and navigate, Monzo is well known for its creative design thinking. One of the best examples of this is Monzo’s famous coral-pink cards.

From the beginning, the colour was chosen as a marketing strategy: “We mostly wanted it so when we went to a restaurant or something, people would ask about the card,” head of design Hugo Cornejo. “Then when we realised people really liked it, we kept it.” As a user of Monzo myself, I have to admit, I only came to know about it after seeing my friend’s bright pink card, and asking about it.

“In order for any product that’s customer-facing, design must happen. You might do it with care, you might do it as an afterthought. In our case, we know of the importance of it because of the hot coral card – people really like it, but it doesn’t happen by accident. It was a lucky strike, but there’s some reasoning and design behind it.”

Throughout the app, you can tell the Monzo team has put a lot of thought behind their design - making it seem clean, modern and approachable. Given that their customer base is mostly millennials and Gen Z, who are used to and largely appreciate design, it definitely does not go unnoticed, and further cements the idea that Monzo is so diametrically different from traditional banks.

Transparency as part of its brand
Despite its success, it wasn’t always smooth sailing for Monzo, and yet even when things did go wrong, they maintained their core value of transparency.

For example, during a sudden and unexpected outage (due to some changes to their backend service), Monzo did not hesitate to warn their customers not to use that app and in fact to “carry another card”.

“Because we jumped straight on it and put an immediate message out saying ‘please carry another card out, we’re having an outage and we’re looking into it and will update you immediately’, the PR that came back from it was really strong… From the depths of despair hope blossomed - people said this is a really good firm to be with.”

Gary Dolman, the CFO of Monzo

Given the deteriorating trust consumers had in traditional banks since the 2008 financial crisis, which was epitomized by a lack of transparency, it was never going to be enough for neobanks to win by just having a more convenient user experience. Monzo knew this from the start, and their efforts in being an ‘emotionally’ superior product by simply being honest and transparent won consumers over.

Opinion:
It may also be worth noting that the types of consumers a startup neobank attracts as its initial customer base, is always going to be those who are willing to accept some degree of risk/understanding that there will be teething problems.

This means that the presence of these issues was never going to make users turn away (although obviously, this depended on frequency and severity of issues), but the point is that the initial customer base was looking for something - a bank they could trust, that would be honest with them, and that represented the opposite of what traditional banks stood for.

This is a core part of their product marketing that deserves nothing but praise and serves as a great learning point for other startups.

Culture and Leadership
The transparency and honesty that Monzo showed its customers, was not just a marketing strategy, but it was part of their culture. Culture is always top-down, and I think it’s fair to say that the senior leadership had a strong emphasis on engraining their values into the roots of the company.

For example, Dolman, Monzo’s CFO, attributes their success to the team's fearless approach to challenges - characterized by the five finger push, where not all attempts may succeed, but it’s the one that breaks through that leads to significant achievements:

“Five finger push - four of those fingers won’t break through, but the fifth will and it will break through to something big. It’s not being scared to fail in certain aspects.”

This philosophy encouraged not fearing failure in certain aspects, recognising it as an integral part of the journey to success. In its quest to create the "best current account in the world,"

Monzo showcased a blend of ambitious goals and technological advancement, while maintaining a unique focus and ignoring its competitors. Dolman emphasizes the importance of concentrating on their own strengths and innovations, rather than being preoccupied with what others in the field are doing - (the old adage of competition is for losers [Peter Thiel]). This strategy allows Monzo to stay ahead, with a firm belief in their ability to outperform and outpace the competition.

“You worry about your own game, not what the opposition are doing and let them catch up with you - not the other way round. You are constantly saying ‘these are our ideas; this is what we want to do’, and you have the courage to publish it.
What you are banking on is the fact that you are going to be able to do things better and faster than the opposition.” - Gary Dolman, the CFO of Monzo. [9]

These principles are not only pivotal to Monzo’s success but also serve as valuable lessons for other sectors, demonstrating the power of positive leadership and a strong, cohesive company culture.

Case #2
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Midjourney — A Product Strategy Case Study

Jega Pradeeba — Wed, 17 Jul 2024 07:27:48 +0000

Intro

Midjourney is an AI-driven platform that specialises in generating images from natural language inputs. It was built by an independent research lab with the same name, consisting of only 11 full-time staff to date, yet generating over $200m ARR and 16 million users - having only started less than 2 years ago.

In this case study, we will examine the key factors contributing to its success, focusing on technical product and product marketing strategies, what lies ahead for the company, and some more high-level points for consideration.

I hope you enjoy the read.

Source: Midjourney showcase

The Beginnings of Midjourney: Foundation and Development
Early Days: The Formation by David Holz
Midjourney was established in 2022 by David Holz. Before that, Holz's background includes studies in physics and math, followed by a pursuit of a PhD in applied math, a period during which he also worked at NASA and the Max Planck Institute. In 2011, he relocated to San Francisco to start Leap Motion.

Leap Motion, known for its precise hand-tracking technology similar to a 3D mouse, gained significant traction with over 300,000 developers using the technology, attracted funding from major VCs - an experience that would later influence Midjourney - and eventually was acquired by Ultrahaptics for $30M in 2019. [1]

Transition to Midjourney:
After Leap Motion, Holz found himself contemplating the future and what people would need in an uncertain world. He identified three core pillars he believed to be essential: reflection, imagination, and coordination. This contemplation and his personal philosophy significantly influenced the conceptualization of Midjourney. [1]

Origin of the name:
Holz attributes the concept of Midjourney to Daoist influence, specifically Zhuangzi. On the name itself though, Holz says he feels like we are actually mid-journey - that “we come from a rich and beautiful past, but ahead is this wild, unimaginable, unfathomable future”. [2]

The Vision is bigger than you think:
Holz envisioned Midjourney not just as a technology product but as a platform for creativity and expression. He focused on creating an AI-powered platform that would transform text prompts into visual imagery, enabling users to explore new realms of creativity and imagination. This vision was rooted in his belief in the power of AI to expand human imagination and capability.

“We don’t think it’s really about art or making deepfakes, but — how do we expand the imaginative powers of the human species?” [3]

Right now, there is a lot of fear-mongering around AI, but Holz sees things differently, he likens AI to an engine - engines are without feeling, without motivation, and without direction - it is only the human’s application of the engine that those things are derived.

An engine is a tool that is to be wielded by humans, to get us from A to B much more efficiently, and in doing so, take us on a journey that opens our minds to new ways of thinking and looking at the world. Midjourney was designed to help influence new frontiers of imagination, to be a creative partner, not a replacement.

In an interview with The Verge, Holz goes on to compare the discovery of these AI models to the discovery of water. In the sense that they both represent fundamental elements that can be harnessed for transformative purposes. Just as water can be both a peril and a boon to humanity – capable of causing harm but also essential for life and progress – AI too holds dual potentials. The point is not to be afraid of its potential, but to understand how we can build tools to harness its potential to better our lives:

“How do we teach people to swim? How do we make boats? How do we dam it up? How do we go from people who are scared of drowning to kids in the future who are surfing the wave? We’re making surfboards rather than making water. And I think there’s something profound about that.”

Opinion:
I don't think the importance of the vision of a company gets as much emphasis as it should. Perhaps we forget that humans are driven by emotion, and when you develop a moonshot, something that is a little bit abstract, but is exciting and adds value to the world - supercharging human imagination in this case - that is what galvanizes the team around you and what attracts the best talent to you.

The Ethos
The ethos of Midjourney, as encapsulated in the quote, “It’s just about having a home for the next 10 years to work on cool projects that matter —hopefully not just to me but to the world — and to have fun,” reveals a company culture deeply committed to passion-driven innovation and the pursuit of projects with global impact.[3]

This eleven-person team operates without external capital, a unique position that liberates them from the typical financial pressures and constraints often faced by startups. This independence is key to understanding their approach. The absence of external financial motivations and external forces trying to pull the strings, allows for a purer focus on crafting a product that genuinely connects with users, fostering a deeper level of engagement and satisfaction.
Bottomline is Holz has managed to protect the core of the business and his team from being pulled in the wrong direction, optimising for a product that users love - nothing more, nothing less.

Opinion:
I think this is an important lesson for early stage founders. Whenever we read about startups in the media, its usually about how much money the startup raised and therefore how much it is valued at. So in our minds we associate the amount of money you can raise to the amount of value a startup creates.

I.e. we assume:
value a startup creates == valuation of the company == f(amount of money raised from VCs)
I think founders, and perhaps even VCs, really need to disconnect from this mental model, and realise that the true value of a company, is a function of the value created for each individual user of your product. And when you optimise for this, as Midjourney clearly do, the financial rewards will come - they were always a lagging indicator anyway.

Product Strategy:
Its worth looking at their product strategy from two angles: the technical product strategy, i.e. more focused on how they were building and optimising their model, and the product marketing strategy, more focused on how they positioned and their product and engaged with users.

An intro to product:
Midjourney, like other generative AI platforms, operates on a foundation of advanced machine learning techniques, primarily using diffusion models. The core principle behind these models is to start with a sample image, incrementally add noise, and then train the model to reverse this process, effectively learning to generate new images that are similar to the original. This process allows for the creation of unique, yet familiar, visual content.

The training of these models is a data-intensive process. Platforms like Midjourney typically gather vast amounts of data from the internet, which includes scraping images and text. For instance, Midjourney has utilized open-source training models and extensive datasets, such as the 2 billion image-text pairs from the English subset of CLIP’s open dataset, created by the German non-profit LAION. This approach of aggregating and processing massive datasets enables these AI models to learn and replicate a wide range of styles and content, making them versatile tools for various creative applications. By continuously analyzing user interactions and preferences, platforms like Midjourney further refine their models, ensuring that the generated content resonates with user expectations and emerging trends.

Technical Product Strategy
Offense
Default style of MJ:

Midjourney’s default style is intentionally designed to be more artistic and interpretative than the specific input provided by the user, serving a distinct purpose in its product strategy. According to Holz, the rationale behind this approach is that users often don’t know exactly what they want when generating images. If precise replication were the goal, one could simply use Google Images. However, platforms like Midjourney aim to elevate human imagination, necessitating a more creative and proactive role in the image generation process.

The essence of Midjourney's approach is to avoid the mundane. For instance, a simple prompt like “dog” could yield a straightforward photo, but that lacks creativity and purpose in the context of AI-driven artistry. Instead, Midjourney aspires to produce works that are not just responses to prompts but artistic interpretations. This is evident in the model’s inclination towards whimsical, abstract, and somewhat peculiar outputs, often blending elements in unexpected yet aesthetically pleasing ways. Holz notes that the model has preferences, such as favoring certain colors and styles, which contributes to its unique artistic identity.

This distinctive style is a deliberate choice, ensuring that the output is more than just an answer to a query - it's a creative journey, offering users a blend of beauty, surprise, and artistic flair. [4]

Source: Miss Journey - a default face the model has a tendency to draw

Defense:
On restrictions
What’s important about Midjourney’s product strategy, is not just what it allows users to do, but also what it does not allow users to do.

Another important part of Midjourney's product strategy is not only the creative possibilities of what users can do, but also the limitations it places on what users cannot do. Considering the boundless scope of user imagination, generative AI platforms have sometimes been used to create content that is graphic and violent.
One way Holz and his team found a way to deal with this, was to inject accountability of the images created by putting that user’s name on the images created - “When you put someone’s name on all the pictures they make, they’re much more regimented in how they use it. That helps a lot.” Essentially, by promoting transparency over who made it, it almost created a self-policing mechanism.
On top of this, they added in more robust guard rails, from moderators to the team actively intervening and banning specific words such as “ultragore and everything within a mile of that”

Opinion:
I think the point here is that yes there’s this moonshot vision that’s clear to the team and the users, but Midjourney also set up guardrails to ensure that no one veers off from the track, and ends up morphing the platform into something the team did not want it to be.

On artists:
The issue of copyright within platforms like Midjourney and ChatGPT are still in open discussion right now, so I won't delve into this too much.

But it is worth noting that the fact that Holz and his team have been aware of addressing the concerns of the artistic community from the start, has likely also played a role in their success. This is not just to do with anticipating liability issues, but for a product that is built on a community, the community needs to maintain trust in the product, and by actively engaging with their artists it is no wonder why around 4 million of its users are working professional artists.

“We do have a lot of artists in the community, and I’d say they’re universally positive about the tool, and they think it’s gonna make them much more productive and improve their lives a lot. And we are constantly talking to them and asking, “Are you okay? Do you feel good about this?” We also do these office hours where I’ll sit on voice for four hours with like 1,000 people and just answer questions.” [3]

Product Marketing Strategy

Partnership with Discord
Their partnership with Discord has more to it than at first glance.
Firstly, by not being on a simple to access website, Discord in a way, acted as the sandbags, holding back the flood of users that inevitably come with virality - a problem that OpenAI faced. In fact, it allowed the team to continue to engage with the community they did have, and perfect their product, before opening the flood gates - which they are now doing.

Secondly, even in its very early stages, Midjourney still had to support hundreds of thousands, and soon millions, of users trying to access their model. By piggybacking off of Discord’s infrastructure, to handle the traffic, Midjourney was able to keep its head well above the water, and is also a contributing factor to why the team could stay as small as it has.

Third is engagement. It’s not simply just that Discord already had a large and active community, but also how the engagement specifically ended up influencing their output. The idea is essentially a “round-robin” story - where one person starts, and then another person adds to it, and then another, and another, and by the end, you create something that no one individual could have dreamed of.

Holz explained it pretty well in his interview with the Verge:
“We found very quickly that most people don’t know what they want. You say: “Here’s a machine you can imagine anything with it — what do you want?” And they go: “dog.” And you go “really?” and they go “pink dog.” So you give them a picture of a dog, and they go “okay” and then go do something else.

Whereas if you put them in a group, they’ll go “dog” and someone else will go “space dog” and someone else will go “Aztec space dog,” and then all of a sudden, people understand the possibilities, and you’re creating this augmented imagination — an environment where people can learn and play with this new capacity.”

Furthermore, because it is so community-driven, you automatically end up with art that is fun, diverse and completely original. And because you’re showcasing the generated images back into the community, there is a much higher chance of things going viral - and when they do, it reinforces interest in the Midjourney platform - case and point the Pope in a puffer jacket image that broke the internet, and led to even more mass interest in Midjourney.

Opinion:
I think this point here opens up a whole new can of worms. Because yes it AI can augment human output, but humans adjusting the output from another human’s AI output, creates a flywheel that is way beyond what any one person, or even isolated interaction with AI can achieve. And honestly, its this that is the future of AI - human + AI + more human inputs creating a flywheel of innovation.

Sandbox-and-watch strategy
Perhaps one of their main product strategy could be described as sandbox-and-watch. By this I mean, they created the playground of what could be done, put in some general guidelines of what should not be done, and then just watch the community take the product in its different directions.

Whilst this has led to Midjourney being used to create some incredibly fun art (an anticipated outcome), as well as using it for bad (also anticipated), some users have been using it for art therapy - where people create images of their loved ones who recently passed away - definitely not anticipated by the team.

And it’s not just a few users, around 20% of all users on Midjourney use it for art therapy. In fact the man behind the viral Pope in a puffer jacket initially started using the platform to create images of his brother who passed away. [5]

Opinion:
I think there is something to this strategy - because by simply providing the sandbox, you are stepping away from any confirmation bias you/team has (because when you build something, you just assume it will be used in the way you’re anticipating), and instead, you open the door to diverse and unforeseen user innovations. This not only challenges your initial assumptions but also enriches the product's evolution, driven by actual user creativity and need.

Business model
A few brief points worth noting about the business: From a top-line perspective, Midjourney are currently doing around $200m ARR, and for a team of only 11, that’s pretty impressive. It has around 16million users, with 30% of their users being professionals, which likely includes industries like graphic design, marketing, and perhaps even entertainment. [3] How exactly the outcomes of the legal proceedings around generative AI will impact Midjourney, and this segment of its customers, is still yet to be seen.

On the cost side, the expense of training image models is significant, around $50,000 per training session, especially considering that multiple iterations are often necessary to achieve the desired accuracy and quality of the models. This iterative process, which might require “three tries or 10 tries or 20 tries”, implies a considerable investment in research and development. “It is expensive. It’s more than what most universities could spend, but it’s not so expensive that you need a billion dollars or a supercomputer.” They are also running on $20,000 servers, which they rent. The point here is that the compute power is enormous for simply just generating the images, in the order of thousands of trillions of operations (petaops) per second - “there has never been a service before where a regular person is using this much compute”. Nonetheless, Holz anticipates costs will drop as competition increases and investors plough in more money.

Opportunities
This month, Jan 2024, Midjourney have released their platform onto their own web service in an effort to increase accessibility and stay competitive. Though it’s worth noting, they are still sticking to the strategy of holding back the flood until they are ready as the website will initially be available only to people who've racked up more than 10,000 images via Midjourney on Discord - allowing them to test and refine the platform’s experience.

The next step beyond image generation is obviously video generation. Many platforms are already making notable strides in video generation technology. As this field evolves, the platform that excels in producing high-quality video content is poised to gain a substantial competitive edge.

The ability to generate videos effectively and innovatively could become a crucial determinant in leading the market. This suggests that the future of AI in visual media might very well hinge on mastering video generation. It’s likely that the increased revenues from greater accessibility via the web platform, will help fund the training of the models for video enhancement.

Threats: Competition:
There are a number of similar platforms to Midjourney, from OpenAI’s DALLE to Stable Diffusion. The graph above shows that pre-V5 release, the gap between these three platforms has been very tight, and it’s likely that this will continue to be an arms race between the top players.

What’s important here, is that whilst objectively they all seem to do the same thing, generate new, creative images, they still do it in very different ways. The graph below is from a quantitative study analysing the performance of the 3 different models against real images. FID (Fréchet Inception Distance) is simply a way to evaluate the quality of images generated by models - where the lower the FID score, the more realistic the image.

As you can see, Stable Diffusion is much better can generating hyper-realistic images, but the importance of this completely depends on who’s using it and for what. Midjourney has a core artistic community, likely because the Midjourney is not so hyper-realistic, with its default style, it provides a better use case for continuing to “expand the imaginative powers of the human species”. [6]