Pricing Strategies for Startups
Updated: Nov 25
Moving Beyond Cost-Based Thinking
TLDR
Start simple with cost-based pricing, but don’t stop there.
Understand your customers, their needs, and the value you’re delivering—and evolve your pricing accordingly.
Experiment with different pricing models to find what works best, as you grow.
Remember, pricing is not set in stone; it’s a living strategy that evolves as your startup learns more about its customers and market.
Consider leveraging the latest AI-driven pricing models to align more directly with the value your product delivers.
1. Introduction
SparkTech, a fictional startup, was like many other startups when they first began their journey — pricing felt like a guessing game. They needed a pricing strategy that would cover their costs, attract customers, and reassure investors. However, they soon realized that pricing wasn’t just a number but a powerful lever that could shape their growth and market positioning.
In this story, we’ll follow SparkTech on their journey from basic cost-based pricing to a more sophisticated strategy, exploring the questions and experiments that helped them evolve.
2. The Early Days: Cost-Based Pricing
In the beginning, SparkTech adopted a cost-based pricing approach during their MVP (Minimum Viable Product) phase. It was simple: add up the costs of building and delivering the product, then add a margin. This gave SparkTech a clear idea of baseline profitability. However, this approach didn’t help SparkTech understand how customers perceived the product’s value or capture that value effectively. They found themselves wondering if they were charging too much or too little, especially compared to competitors. Although cost-based pricing was a reasonable starting point, SparkTech quickly recognized the need to transition beyond it as they learned more about their market.
3. Finding the Right Revenue Model
As SparkTech moved from MVP to finding product-market fit, they realized they needed to evolve their revenue model. This stage was challenging — there wasn’t much customer data to guide them, and they had to balance immediate needs with long-term flexibility. SparkTech’s team explored several key considerations:
Price Discovery: SparkTech engaged in direct conversations with early customers and looked at competitor pricing to understand customers’ willingness to pay (WTP). They wanted to determine an appropriate pricing level while keeping in mind how mature the market was and the perceived value of their product.
Selecting a Price Model and Value Metric: SparkTech debated whether to use seat-based, usage-based, or outcome-based pricing. They knew that how they charged could be more important than how much they charged. They needed a pricing model that was sustainable, scalable, and easy for customers to understand.
Setting the Price Level: Initially, the price point was a mix of guesswork and market research. SparkTech was unafraid to adjust pricing based on early feedback and tried to find the sweet spot that would attract customers without undervaluing the product.
As they found product-market fit, they knew it was time to experiment with different pricing models. They tried several approaches:
Paid Pilots: SparkTech collaborated with early customers through paid pilots to learn how they used the product and the value it provided.
Freemium Models: They offered basic features for free, with advanced capabilities available at a cost, to attract users and validate willingness to pay.
Pay per Seat: This model was used to scale pricing based on team size, especially as they started targeting larger organizations.
Pay per Use: For customers who were wary of upfront costs, SparkTech offered a pay-per-use model, letting them pay based on product usage.
Pay per Time Period: They also experimented with subscription-based pricing for customers wanting predictable, time-based access to the product.
These experiments helped SparkTech refine their pricing, finding the sweet spot where customers saw value while SparkTech achieved profitability.
4. The Role of Value-Based Pricing
Once SparkTech gained traction, they began shifting towards value-based pricing. This model involved pricing their product based on the value it provided to customers and considering alternatives in the market. For example, if SparkTech’s software saved a business CHF 10’000 annually, they priced it at CHF 3’000 to make the value proposition clear and compelling, while still covering their costs and remaining competitive.
Value-based pricing allowed SparkTech to move away from simply covering costs and instead focus on matching their price to the value customers perceived. This helped them maximize revenue as their understanding of the market and customer needs matured.
5. Segmentation of the Customer Base
As SparkTech’s customer base grew, segmentation became increasingly important. They needed to tailor their pricing to different segments based on usage patterns, company size, or willingness to pay. Key indicators made it clear that segmentation was necessary:
Growing Total Addressable Market (TAM): As SparkTech built more functionality, their TAM expanded, revealing new, diverse customer needs.
Diverse Customer Cohorts: Different customers had different WTP, making it essential to create tailored offerings.
SparkTech developed effective segmentation through packaging plans such as tiered offerings and a “Good-Better-Best” model:
Tiered Packaging: Customers could self-select the tier that fit their needs, aligning different features with different value propositions.
Good-Better-Best Model: This allowed SparkTech to offer a basic package for budget-conscious customers while offering premium versions for those seeking more tailored features.
By segmenting their customer base, SparkTech was able to better monetize their product and avoid undercharging customers who could afford to pay more.
Overall, pricing developed into a strategic value driver for SparkTech and a continuous area of exploration and optimization.
6. Latest Developments in Pricing Models
Recent industry shifts, particularly driven by advancements in AI, have led to innovative pricing models that go beyond traditional pricing approaches. Startups are increasingly moving from selling access to selling the actual work performed by their products. This evolution reflects the value delivered by AI and automation technologies:
Outcome-Based Pricing: Charging for specific outcomes or work completed by AI. For example, Intercom’s AI agent charges USD 0.99 per successful resolution, ensuring customers only pay when they derive tangible value from the AI’s work.
Task-Based Pricing: Companies like Zendesk are introducing pricing based on the number of successful tasks or resolutions performed by AI agents, shifting from static seat-based subscriptions to a more flexible and value-driven model.
Consumption of AI Services: AI-driven models like Salesforce’s Agentforce, which charges per AI interaction (USD 2 per conversation), are gaining popularity. This approach aligns pricing with the value generated through AI-driven outcomes rather than just software access.
These models represent a shift towards bundling software and service, potentially offering lower total cost of ownership for customers while allowing vendors to better capture value. Moving forward, startups should consider these innovative approaches to align pricing more closely with customer success and work output.
7. Conclusion and Call to Action
Pricing isn’t just about covering your costs; it’s an opportunity to understand your customers, communicate value, and fuel growth. As you build your startup, keep iterating on your pricing strategy—the more you learn, the more powerful your pricing will become.
Ready to take the next step? Start asking these key questions and experiment with different pricing models to find what works best for your customers and business. The team at Alfred has successfully supported founders in finding answers. Let us know if you’d like to explore how we can assist you in refining your pricing strategy.
Contact Alfred
Diego Seitz, Founding Partner, Business Consulting
+41 44 499 0050
Bahnhofplatz 1, 8001 Zürich
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