Scalable Startup Revenue Models for Sustainable Growth

In short, the business model for startups is a broader term, and many founders analyze companies like Amazon and its revenue model for inspiration.. It explains the underlying system that creates value and makes earning money possible. A startup revenue model is all about pricing logic and revenue scalability. 

Let’s imagine you want to create a wellness mobile app delivering workouts and nutrition videos to users. The business model for startups includes:

• how your startup operates (cost structure), 
• its key resources (how your app makes videos), 
• customer segments, and 
• channels (web app, mobile app, or both). 

However, the issue of whether you will be selling lifetime access for $50 or taking a monthly subscription of $10 is a matter of a startup revenue model. In this example, the first one is not scalable, the other one is. In terms of other options, you can make the base version of your app for free and offer premium content within the freemium revenue model. This one is scalable as well. 

In this blog, we’ll look at what makes a startup revenue model scalable, and talk about the revenue models that make the best first choice for startups.

Business Model vs Revenue Model: Netflix Case Study

In our article “Netflix Business Model & Revenue Model to Consider for a Startup“, we’ve looked at both in detail. There, it is mentioned that the startup revenue model is secondary to its business model. A business model for startups is often put into a business model canvas like the one below.

A business model for startups, like the one of Netflix, explains all system’s elements: partners, activities, value proposition, customer relationship management, channels, customer segments, cost structure, and revenue streams. So a business model is a system, and it can have several revenue models on top of it. 

When we discuss Netflix’s revenue model specifically, the questions revolved around:

• The decision to adopt the subscription revenue model in the early days, when Netflix was still a mail DVD rental.
• The economic considerations around making the subscription unlimited.
• Pricing tiers dependening on streaming quality & the number of devices, and geographic discrepancies in pricing.
• Consumer psychology in pay-per-view vs unlimited subscription.
• Netflix’s Lifetime value vs Customer acquisition costs and comparing metrics against competitors.

As such, you can clearly separate concerns of the startup revenue model from its business model. 

Scalable Startup Revenue Model: Definition

A scalable revenue model is a way to boost revenues and margins without increasing costs nearly as much.  Scalable revenue models often prioritize repeatability and predictability of revenue streams, such as subscriptions, commissions on transactions, etc. The scalable revenue model relies on a business model for startups that emphasizes technology and automation over human labor to deliver value. 

According to Tom Mohr, author of Scaling the Revenue Engine: 

“The revenue engine is a whole system. It encompasses a diverse set of integrated components, each doing its part to advance the system’s purpose. The engine is not just comprised of marketing and sales— it includes product, accounting, and the underlying technology and data infrastructure required to keep everything flowing. It involves people, tools, workflow, and metrics. Its purpose is to optimize reach, conversion, and expansion of customer spend.”

This quote conveys the interdependence: one cannot build a scalable revenue model without carefully crafting its business model. For a revenue model to really take off, the company has to minimize costs for adding each new client, consider the resource load of taking care of light users, build organic growth loops, and so much more.

Business Model for Startups & Multiple Revenue Streams

Case studies of established companies are generally more available. What you find there is often multiple revenue streams, meaning multiple revenue models. However, when it comes to the scalability of your startup, you should focus on optimizing one startup revenue model. Same as the target user for your MVP, where you cannot appeal to all user segments at once, your revenue model should be tuned to work with that one segment rather than all customer tiers. 

Moreover, as we’ve said above, the choice of revenue model should be based on the scalable business model in place. This means getting the cost structure and the ease of serving the target user right. 

Finally, you should account for the most natural choice in terms of user experience: your revenue model should enhance it, or at least not damage.

Subscription Startup Revenue Model

Subscription relies on providing each customer with access to your product or service, charging a flat fee. There can be different tiers, and they can have usage quotas or be unlimited. 

The scalability depends on a business model for startups, whereby adding a new user adds very little cost. So, with growth, costs change very little while revenue grows predictably, which makes a stronger case for your startup funding strategy. 

In this revenue model, the key metrics are:

• Monthly Recurring Revenue – MRR;
• Net Revenue Retention – NRR;
• Churn Rate;
• LTV/CAC ratio.

MRR shows the predictable revenue part, while NRR captures the upsells or extras that the existing users purchase. For instance, if you have a subscription with quotas and then extra use is paid for separately, and so on. Churn rate should be minimal for scalability. LTV/CAC ratio is basically a measure of how scalable your app is overall. Your LTV should be at least 3 times more than your CAC. 

When it comes to fine-tuning your subscription revenue model for scalability, here are some A/B tests to consider:

• pricing tiers and their quotas;
• billing cycles. For instance, Audible introduced a bi-monthly subscription. It charges users only once every 2 months, retaining users who listen less frequently;
• free trial length;
• discounts for longer subscriptions.

When subscription is a good first choice

In terms of consumer psychology, subscription makes sense when a user will benefit from the predictability and peace of mind that a subscription provides. Often, pricing is tested against the ‘sunk-cost’ effect: just how much users need to pay so that they will engage with the product to get their money’s worth? Finally, there is the endowment effect that helps to reduce churn. For instance, Netflix keeps track of watched content and provides personalized recommendations. Users perceive these as something they ‘own’. As such, it becomes a psychological lever to prevent the cancellation of the subscription.

Freemium Revenue Model

The freemium revenue model means offering a basic version of your product or service for free to your users. Then, you can offer extras, advanced features, or more use for a premium price. The scalability of this startup revenue model depends on a large free user base and converting a fraction of it to paid users. The metrics that are essential for tracking scalability are:

• conversion free-to-paid;
• activation rate;
• retention by cohorts.

The conversion is the most straightforward indicator of revenue. However, activation rate and cohort retention of free users signal about the scalability potential, meaning the ability to nurture free users into paying ones.

In terms of optimizing your freemium revenue model towards scalability, the following A/B tests are common:

• the timing of premium features, e.g., at what point premium functionality is offered; 
• time-gated access for trying out premium features; 
• the balance between free usage vs premium usage;
• testing which features to keep free and which ones to make premium.

It is best to launch these tests early in your product lifecycle. For instance, edtech company Quizlet paywalled its previously free and unlimited “Learn” and “Test” functionality in 2022. Before this, students created study sets and relied on these free modes to learn them. Now, they have only 5 rounds of Learn and 1 round of Test for free. The company faced a lot of backlash and alienated some of its users. Articles came out with headlines “Quizlet’s paywalls place priority on profits over pupils”. Ultimately, Quizlet was ready to sacrifice part of its free user base for profits. Overall, the company survived the backlash and increased its revenues. However, having done this earlier would have saved the negativity. 

When freemium is a natural choice

The IKEA effect refers to making free users invest effort in a setup. For Quizlet, it is about creating study sets. By the time Quizlet paywalled essential features, many users had been creating study sets and learning them literally for years. For Spotify, it is about creating users’ own playlists. The IKEA effect is leveraged for retention as well as for upgrading to paying customers. The basic consumer psychology effect, though, is the Foot-in-the-Door effect. Some products that automate or digitize habitual workflows or actions require users to try them first. It is also useful when adoption is likely to be an obstacle (for novel products and ideas). Lastly, paywalling valuable features speaks to loss aversion, when they are framed as ‘do not miss out on…’. 

Pay-Per-Use / Pay-As-You-Go Startup Revenue Model

The pay-per-use revenue model bases pricing on usage. The scalability stems from minimizing the costs. The critical points are generally the human support and related admin services, such as onboarding, accounting, etc. This is why this revenue model often has a minimal price.

The metrics to track to monitor scalability:

• Volatility of Average Revenue Per User (ARPU);
• Expansion revenue;
• Gross margin per unit of usage.

Volatility of ARPU should be minimal, as customers are likely to churn after a ‘shock bill’ situation. Low volatility also signals about customers integrating the usage of your product into their routines, making your revenue consistent and predictable. 

Expansion revenue is about the organic growth of revenue. It is when existing customers do not need the sales effort to use more of your product. The stronger the metric, the higher the scalability potential. 

Finally, gross margin per unit of usage should improve with scale. If not, you still need to work on your business model. 

The A/B tests to optimize the scalability of this startup revenue model include:

• usage pricing units – e.g., per minute vs per 10 minutes, per GB vs 100 GB.
• testing minimum monthly pricing.

Twilio uses solely this revenue model, and offers discounts at high volumes, indicating its cost structure is well-aligned with scalability.

When pay-per-use comes first

From a consumer psychology perspective, pay-as-you-go appeals well to perceptions of fairness and control. Paying for only what you use and controlling one’s spending are perceived as advantages. However, ‘bill shock’ is a common problem when usage increases substantially and unexpectedly, leading to user anxiety and user churn. For AWS, for instance, ‘bill shock’ is a recurrent issue.

Marketplace / Brokerage Revenue Model

The marketplace revenue model derives revenue from transactions between sellers or service providers and customers. Scalability depends on the ability of the underlying business model to produce network effects. The latter means creating organic growth loops that bring more sellers and buyers to the platform. Metrics that track the revenue growth are:

• the overall value of processed transactions;
• take rate;
• liquidity;
• CAC payback period.

The value of transactions and the take rate indicate overall revenue volume. Liquidity is essential as it shows successful matching between the demand and supply sides. Monitoring the CAC payback period is critical. This is essential for startups in early growth stages. In addition, paid marketing efforts are likely to be involved to balance supply and demand. 

In terms of optimizing for scalability, the following A/B tests should be run:

• testing out different fee structures, such as flat fee, and the variations on tiered commissions. 
• testing different incentives to join and then to make a transaction for both, demand and supply sides.

One of the A/B tests conducted by Etsy aimed to test the free shipping threshold and the corresponding ‘free shipping’ label. It showed certain items with the label ‘free shipping’, and saw increased sales for such items. Sellers also adapted and learned to qualify their items for this label. 

What consumer psychology factors drive the scalability of the marketplace revenue model

This startup revenue model scales when:

• Your startup pushes for creating a trusted platform – trust by association is the driving factor for marketplace growth;
• Social proof – the legitimacy of sellers grows with the evidence of transactions of others;
• Convenience bias – if you build your marketplace as a one-stop shop for a particular purpose, customers will stick and be ready to pay more due to the simplicity of their shopping experience.

Final Thoughts

Those revenue models above are mainstream ones. There are also others, which are more context-specific and require a specialized business model for startups. For instance, White Label revenue model will make sense if you have a product that will be widely adopted by partners who will be able to monetize it rather than you selling it directly. Often, it is an additional revenue model, like in the example of Shopify. A retainer-based revenue model will suit a startup in a service-heavy segment where customers need peace of mind and predictability. Finally, the razor-and-blade model requires selling the base product at low cost, or sometimes even at a loss, and monetizing the high-margin consumables.

FAQ: Scalable Startup Revenue Models for Sustainable Growth