by Steven Forth

One of the big questions founders struggle with is price. Even mature companies struggle with price and often reach out for help from consulting companies, so it is not surprising that founders have questions here. In the last few years, the explosion of SaaS and business AI models has only made the problem more visible.​​

I look at a lot of pricing and pricing models in the SaaS and business AI space, more than 100 different examples most years. Across those examples, there are three common failure modes and one consistent path forward.​​

Three common failure modes

Most early-stage pricing mistakes fall into one of three patterns.​

• Cost-plus pricing that looks safe on a spreadsheet but ignores customers.

• Market-driven pricing that copies competitors and erodes differentiation.

• Random experimentation with price points divorced from value or strategy.

Each of these has a logic. Each of these will hold you back.

Cost plus: safe and wrong

Cost-plus pricing is still the default in many companies, even with all the talk about value-based or outcome-based pricing. It is regarded as the safe option, one that protects margins and is easy to defend to a buyer.​​

There are at least three problems with cost-plus pricing for early-stage, innovation-driven companies.​

• The buyer does not care what your costs are.

• Start-ups often have distorted costs: higher than large companies, or artificially low because founders underpay themselves.​

• “Cost” itself is ambiguous: variable costs only, or allocations for R&D, sales and marketing, and general overhead.​

Cost-plus pricing is internally focused. Early-stage companies, especially in SaaS and business AI, need to be focused on customers and on how value is created for them. Cost-plus pricing does not help with that.​​

Copying competitors: playing the wrong game

A second common approach is to look at the dominant competitor and then price at a discount, very rarely at a premium. When asked what their differentiation or strategic advantage is, founders in this mode often answer, “We are just like them, only cheaper.”​

“Cheaper” is not competitive differentiation; it signals lower value. Founders should not assume that large competitors cannot match or undercut their prices. They generally can, at least long enough to put you out of business.​​

The deeper problem is attention.​

• Market-driven pricing focuses you on competitors, not customers.

• You start optimizing against another company’s strategy rather than your own value creation.​

There is one important exception. If you can deliver an order-of-magnitude reduction in price for the same results, that can be game-changing. This is showing up more often with AI: something a conventional solution would charge 10,000 for can sometimes be delivered through an AI-based solution for 100. That shift removes constraints on use and can open entirely new patterns of adoption.​​

But if the price advantage is “only” 10 percent, or even 50 percent, it will be a hard sell. Incumbents are deeply embedded and good at defending their territory. Do not play by the incumbent’s rules.​​

Throwing it at the wall

The third pattern is to throw prices at the wall and see what sticks. The more disciplined founders run structured A/B tests; others flounder and try anything that comes to mind.​

Price changes are not inherently bad. In fact, most companies should change prices as they learn and as their offer evolves. But price changes need to be planned and well communicated to customers, partners, and the go-to-market team.​​

Can you A/B test pricing? Sometimes. Before you start experimenting with price points, consider testing different pricing models. Pricing is not just about the number you put on the price tag; it is about what you put the price tag on.​​

This is where two critical metrics come in.​

• The pricing metric: the unit of consumption for which a buyer pays.​

• The value metric: the unit of consumption by which a user gets value.​

Understand and test your value metric first. For most early-stage companies, the best way to do this is by talking with customers and making those conversations part of the operating rhythm.​​

There is an old joke in early-stage fundraising.​

• If you want to get advice, ask people to invest.

• If you want an investment, ask them for advice.

Pricing has a similar joke attached to it.​

• If you want to learn about price, ask about value.

• If you want to learn about value, ask about price.

Most customers are surprisingly willing to tell you how, and even how much, value they expect your product to deliver. Once you understand how they get value and how much they will pay for that value, pricing gets much easier.​

Customer-focused pricing

The alternative to these three failure modes is customer-focused pricing. For early-stage companies, that means building a discipline around understanding value, modeling it, and connecting it to willingness to pay.​​

There are three pillars.

• Build a value model.

• Use value to understand and shape willingness to pay.

• Target pricing to a specific use case for your ideal customer profile.

Build a value model

To price on value, you need a value model. Subscription pricing expert Michael Mansard at Zuora has argued that every application should embed a value model, and this is especially true for SaaS and AI applications.​​

A value model is a simple system of equations that estimates how you impact your customer’s profit and loss statement, or in some cases their balance sheet.​

Ask concrete questions.

• Do you help them increase revenue, for example by impacting pipeline or net revenue retention metrics?

• Do you reduce costs, and if so, which costs and where in the process?

• Do you reduce operating capital requirements or the scale and timing of capital investments?

• Do you reduce risk, and can you quantify that risk reduction?​​

The standard approach to value models in B2B pricing is called Economic Value Estimation, or EVE, which comes from Tom Nagle’s work. His book The Strategy and Tactics of Pricing is a demanding read, but for many pricing teams it is worth more than a dozen more popular titles.​​

Shape willingness to pay

Value does not equal price. Price is based on customer willingness to pay (WTP); value shapes WTP and sets an upper bound, but other factors matter as well.​​

Two of the most important are perceived risk and emotional connection.​​

• Perceived risk tends to be high for early-stage companies, and that depresses willingness to pay.

• Emotional connection—trust in the team, belief in the vision, alignment with the problem—can raise it.​​

You can address risk directly in your pricing.

• Offer a risk discount that phases out over time as risk goes down and evidence accumulates.​

• Or offer credits if the agreed value is not delivered, tying those credits to your value model.​

Always listen to customers about how they are getting value and why it matters to them. Make those conversations part of customer success, product discovery, and sales enablement.​​

In general, early-stage companies should aim to capture 5 percent to 10 percent of the value they create. In rare cases, when there is very strong differentiation and an opportunity to use a high price to signal high value, they may capture as much as 20 percent. Mature companies, with lower perceived risk and stronger evidence of value, can sometimes claim up to 30 percent, but it is very hard to sustain prices that claim more than 30 percent of the value created over time.​​

Focus on a specific ICP use case

Many early-stage companies are unsure who they are selling to and try to sell to everyone. That instinct is understandable. You want to take advantage of every opportunity and explore the possibilities as a way to find direction.​​

Part of you, and part of your company, does need to stay open to exploration. It is central to innovation and discovery. But this mode will not help you price, it will not help you scale, and it will not lead to predictable revenue.​​

Design your pricing for the value created in a specific use case for your ideal customer profile. When you do that:​

• Pricing innovation becomes easier because you are not trying to solve for everyone at once.

• Learning cycles speed up, which lets you evolve pricing faster.​​

Speed is life for early-stage, innovation-driven companies. Treat pricing as part of innovation, not as an afterthought once the product is “done.”​​

Steven Forth is a founder at valueIQ.ai, where he contributes to the design of Pricing Intelligence and Value Sales agents. He shares his insights on pricing and innovation on the Pricing Innovation Substack and has designed some of the most successful SaaS pricing models, including leading credit-based pricing models for vertical AI.