Why MAU Pricing Is Breaking Your SaaS Business: Lessons from the Field

(MAU = Monthly Active Users)

Remember when software licensing was simple?

You'd buy a perpetual license, maybe pay for maintenance, and call it a day. Then the cloud happened, and suddenly everything became "as-a-service." While this shift has brought incredible flexibility, it's also created a pricing puzzle that many SaaS companies are still trying to solve.

For companies in the Fan Engagement space, this puzzle is particularly critical - imagine your costs suddenly skyrocketing during a viral moment or a major event, precisely when your platform should be celebrating its success. This is why understanding the evolution of SaaS pricing models isn't just an academic exercise - it's crucial for building sustainable, scalable fan experiences.

The Promise of Modern Pricing

The SaaS industry has come a long way from the rigid seat-based licenses of the past. Companies like Slack revolutionized the game by charging only for active seats, while AWS transformed infrastructure pricing with its pay-per-second model. These innovations showed us what's possible when we truly align pricing with value.

For frontend developers and teams building real-time features like chat, live updates, or streaming capabilities, this pricing evolution is particularly relevant. As you scale your applications and integrate more real-time functionality, the pricing model you choose can significantly impact your bottom line and your ability to deliver value to users.

But here's the thing: not all "modern" pricing models are created equal. And sometimes, what seems like a customer-friendly approach can actually be hiding some serious flaws. This is where Monthly Active Users (MAU) pricing comes in – a model that's gained popularity but, according to Ably 's CEO Matthew O'Riordan , might be doing more harm than good, especially for teams implementing real-time features in their applications.

Read more directly from Matt’s article: https://ably.com/blog/consumption-based-pricing ?

The MAU Trap: A Closer Look

O'Riordan's recent analysis of MAU pricing is particularly eye-opening because it challenges what many consider to be an intuitive pricing model. For frontend teams considering implementing chat or real-time features, understanding these pricing implications is crucial - it could mean the difference between a scalable solution and one that becomes prohibitively expensive as your user base grows.

The "Average User" Fallacy

Think about it: when was the last time you met an "average" user? O'Riordan illustrates this brilliantly with real-world examples. Take a SaaS business using a chat service – their users might be online eight hours a day, but only during weekdays. Meanwhile, a live events platform might have users who connect for just four hours a month but send messages at an incredibly high rate during those sessions.

Here's where it gets interesting: the MAU model forces both these dramatically different use cases into the same pricing box. The result? One customer pays for connection time they'll never use, while the other gets hit with overage charges for exceeding message quotas. It's like paying for an all-you-can-eat buffet when you only want coffee, or being charged extra because you ate too much salad.

The Hidden Cost Bomb

"Predictable pricing" is the siren song of MAU models, but O'Riordan exposes this as largely a myth. He points to a particularly striking example: imagine running a successful live event where all your users show up at once.?

This is especially critical in the fan engagement space, where peak usage during live events can lead to astronomical costs under MAU pricing - you're essentially being penalized for your success. With some MAU-based services, you could face bills up to 95 times higher than your regular rate, simply because your success exceeded their concurrent user assumptions.

The Storage Spiral

Perhaps the most insidious effect O'Riordan identifies is what he calls the "virtuous circle" of storage costs – though "vicious circle" might be more accurate. When storage is bundled into MAU pricing, customers have no incentive to manage their storage efficiently. They store everything indefinitely because, hey, it's "free," right?

But here's the catch: that storage costs the vendor real money, leading to price increases, which in turn encourage customers to use even more storage to "get their money's worth." It's a spiral that benefits nobody in the long run.

Breaking Free: The True Consumption Model

O'Riordan's solution, implemented at Ably, offers a refreshing alternative. Instead of forcing customers into a one-size-fits-all MAU box, they've taken a page from AWS's playbook: charge for what customers actually use, at the most granular level possible.

This means tracking and billing for specific resources like connection minutes, message volume, and storage separately. It's more complex to implement, sure, but it creates a fundamentally healthier relationship between vendor and customer. When customers pay for what they actually use, they're incentivized to use resources efficiently, and vendors can price their services sustainably.

Looking Ahead

The future of SaaS pricing isn't about finding a single perfect model – it's about creating pricing structures that accurately reflect value delivery while maintaining transparency and predictability. O'Riordan's critique of MAU pricing isn't just a complaint; it's a call to action for the industry (both on the SaaS vendor side and the clients’ one) to think more carefully about how we align pricing with actual usage patterns.

The companies that will win in this space are those that can strike the right balance between simplicity and accuracy, between predictability and fairness. They'll be the ones who understand that true consumption-based pricing isn't just about counting users – it's about measuring and charging for the actual value delivered to each unique customer.

The days of one-size-fits-all pricing are numbered. O'Riordan's critique is a call to action for SaaS and PaaS vendors to think more carefully about how we align pricing with actual usage patterns. Whether you're a SaaS provider or a customer, it's time to demand pricing models that work in the real world, not just on a sales sheet.

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