💵 Startup Pricing Strategies

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👋 Hi there - it’s Egemen, thanks for reading Scalable.

I hope you are wrapping up an Olympic week 🏅 It’s a fun time.

Even in the best of times, startups in their early growth stage are essentially organized chaos. As in YC’s essential advice to startups, all startups are badly broken at some point.

Pricing can easily become a sub-optimal piece in a much larger puzzle - and pricing strategy is hardly ever discussed.

In this week’s edition, we’ll examine some pricing examples of successful startups and how their strategy is shaped in each funding round.

Here’s a snapshot of what’s on the menu today:

☝️ Scaled this past week: Momentum

Momentum raised $13M in Series A, bringing its total funding to $18M — they are the scale of the week!

Based in the US, the customer intelligence platform detects blind spots in sales to optimize operations so customer-facing teams can move faster.

What Momentum does:

• Captures customer data from interactions like calls and emails, using AI to generate actionable insights​.

• Integrates with tools like Salesforce and Slack to process and present data seamlessly​.

• Supports revenue leaders in making better decisions by optimizing operations and identifying risks.

🧠 Deep-dive: Startup Pricing Journey

Pricing strategy can be a tough nut to crack for startups.

Early-stage startups are typically laser-focused on one product, a few customer personas, and one simplified GTM motion.

This has been a topic that I’ve been thinking about for a while now. I came across this report published by Bessemer Venture Partners and Simon-Kucher & Partners, and I must say it’s been an absolute gold mine.

When focusing more on product development and customer acquisition, dismissing the pricing discussions is easy. The lack of initial data and the need for input from various customers make it even harder.

Initial pricing often lacks comprehensive data but should still be informed by some research rather than guesswork.

Treat it almost like a product feature - regular feedback loops are essential to keep pricing strategies updated and aligned with market dynamics.

Getting it right is vital. It’s one of the most effective ways to drive revenue growth without huge investments.

Imagine a hypothetical company: Company A. It’s actually a real company but for anonymity reasons, let’s keep it Company A as in the report.

Pricing adjustments and their impacts on revenue are above.

Company A launches a premium product at a competitive price, adjusting it based on market demand.

For years, the pricing has remained unchanged, missing optimization opportunities. Eventually, they adopted a tiered pricing model to better match different customer segments.

• Launched a premium version for $10 more than an inferior product.

• Following market demand, increased price to $39, then left pricing alone for years.

• Effectively didn’t change pricing for six years and then got a 30% boost on their most popular offering.

This is how it changes as companies grow from early stage to maturity:

Some might think it's okay to set pricing and then move on to other urgent tasks. But, taking a closer look, focusing on pricing is one of the best ways to boost revenue with minimal effort compared to other strategies.

It’s more than just the price level you set and leave off.

It affects both your top-line and bottom-line.

👉 By adopting a structured, iterative approach, you can navigate more effectively and drive success for your startup.

🗺️ Method: Good-Better-Best Framework

First thing I absolutely love GBB framework: It draws on consumer psychology.

It shifts customers from a binary “buy/don’t buy” mentality to a consideration of incremental value and spending. This is massive for any startup that is just starting out.

The assumption that “Consumers are highly price-sensitive, and most will buy the least-expensive plan they can find” do not hold valid any longer - especially not for SaaS platforms.

Obviously, effective implementation requires identifying key features that differentiate each tier, using market research to set prices, and ensuring clear communication of the value offered at each level​.

👉 This doesn’t always mean you need to have a high number of features, you can create these tiers based on the usage credits and quick wins like priority customer support.

For B2B context, and more relationship-based use cases, I stumbled upon these two wonderful bullet points in a YC video - almost on a note of “if you don’t know where to start”.

Might shed some light - this is actually called value-based pricing.

Rather than basing prices on production costs or competitor pricing, this strategy prioritizes the value seen by the customer.

The aim is to determine the highest price a customer is willing to pay, reflecting the product's perceived value and benefits.

👉 This is an ongoing and complex exercise you should monitor daily.

In the early days, you will see significant benefits if you adopt a culture of continuous adjustments and refine the number based on what customers tell you.

💡 Spotlight: AI-First Customer Service Platform

Since we’re talking about pricing, I highly recommend checking out Intercom's 90% off offer for startups. It’s a good deal.

Intercom for Startups

Join Intercom’s Early Stage Program to receive a 90% discount.

Get a direct line to your customers. Try the only complete AI-first customer service solution.

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