Most startups play defense when discussing pricing with customers. They dance between asking for too little, leaving money on the table, and asking for too much, only to lose the customer’s interest. The very best companies lead their customers in that dance. They use pricing as an offensive tool to reinforce their product’s value and underscore the company’s core marketing message.
For many founding teams, pricing is one of the most difficult and complex decisions for the business. Startups operate in newer markets where pricing standards haven’t been set. In addition, these new markets evolve very quickly, and consequently, so must pricing. But throughout this turmoil, startups must adopt a process to craft a good pricing strategy, and re-evaluate prices periodically, at least once per year.
The Three Core Pricing Strategies
There are only three pricing strategies startups should pursue: Maximization, Penetration and Skimming. They prioritize revenue growth, market share and profit maximization differently.
Maximization (Revenue Growth) – maximize revenue growth in the short term. Startups should pursue maximization when there are no clear differences in customer segments’ willingness to pay, and when the optimal short term and long term prices are equal. Many mid-market software companies price with the goal of revenue maximization, negotiating for the highest possible price in each sale.
Penetration (Market Share) – price the product at a low price to win dominant market share. A bottoms-up strategy lends itself to penetration pricing. Price low to minimize adoption friction, grow quickly, and then move up-market after developing broad adoption. Penetration pricing leads to land-and-expand sales tactics. Expensify, Netsuite, New Relic, Slack follow this model. Penetration prioritizes market share.
Skimming (Profit Maximization) – start with a high price and systematically broaden the product offering to address more of the customer base at lower prices. Skimming is widespread in consumer hardware. Apple sells the latest iPhones at the highest prices, and repackages older models at lower prices to address different customer segments. As Madhavan Ramanujam tells it, Steve Jobs was both a product genius and pricing genius. By pairing the two skills, he led Apple to record-breaking profits quarter after quarter.
Skimming is less common in the software world because few startups develop a product at launch that will be accepted by the most sophisticated customers (and those willing to pay prices that generate the greatest margin). There are exceptions: Oracle’s database, Tanium’s security product, Workday’s human capital management software.
The Seven Factors to Consider When Pricing Your Product
1. The Basis for Pricing
There are three ways to justify a pricing plan:
Value-based pricing charges customers a fraction of the incremental value created by the product or a fraction of the costs saved by the product. This is often seen in ad tech or any type of optimization technology. A startup increases conversions by 50% and they take 10% of the gain as their fee. Value based pricing is also employed in slightly less rigorous ways. Salesforce sells CRM seats based on an aggregate ROI of increased sales productivity for example. So does Expensify, which decreases the time to file expenses.
Cost-based pricing is when startups mark up the product they sell by some margin. Many infrastructure as a service companies do this. AWS, Twilio, Heroku, etc. It’s very common in commodity or nearly-commodity industries, where customers know the prices of the components used to provide the service.
Competition based pricing works well in markets where the price and value of a particular type of product are well established. Startups adopt the pricing model well known in the industry.
2. Positioning
Positioning is the most frequently forgotten of the 4 Ps in Marketing. Salesforce exemplifies exceptional positioning. Used strategically, pricing can be a weapon, a source of competitive advantage in the market. Your company can employ pricing to communicate to the market whether your product is a premium, mid-market or low cost alternative.
Startups can choose to price below the market, to gain share and grow quickly (Zendesk, AirWatch); they can choose to price at the market price and differentiate based on product features (Dropbox and Box); or they can charge a premium for their product, which reinforces their positioning as the gold-standard in the sector (Palantir and Workday).
To be effective, a startup’s pricing strategy must align with its marketing case studies, website messaging, PR releases and sales pitches. If all the arrows point in the same direction, then pricing becomes an asset to reinforce the company’s position in the market.
3. Customer Base Size
The number of total potential customers multiplied by the selling price of the product equals the total addressable market (TAM) for a startup. Generally speaking, bigger TAMs are better. If there are a small number of relevant customers, as in Veeva’s case where the entire market is about 200 pharmaceutical companies, the average revenue per customer must be very high. At IPO, Veeva’s average customer paid the company about $750k per year. On the other hand, if there are millions of potential customers, as in Expensify’s case, the average revenue per company can be much smaller and still justify a billion-dollar-plus TAM.
4. Sales Team Structure
Pricing impacts the structure of a sales team and their day to day performance for two reasons. Higher price points decrease sales velocity, the number of deals closed per sales rep per unit time, and increase sales volatility, the chances a deal closes.
Inside sales teams selling $5-30K products can sustain a deal velocity of 3-8 transactions per month, depending on quota. This keeps morale high and creates a very predictable revenue forecast. No individual customer signing or balking will materially alter the company’s ability to achieve plan.
On the other hand, higher price points require more skilled, more expensive salespeople. Called field sales or outside sales people, their compensation starts at about $250k per year for on-target earnings (OTE – combination of salary and sales commission). Outside sales teams chase larger accounts, and may close 1-3 per year. But if all of them go sideways, the company’s revenues for the year will suffer materially.
5. Contract Length
Many SaaS startups launch with monthly pricing which encourages customers to try the product and engenders demand. At some point, most SaaS startups switch to annual contracts for three reasons. First, revenue becomes much more predictable. Second, annual contracts often include terms that require pre-payment up-front which rewards the startup with lots of cash to grow faster. Third, contracts mitigate churn rates because the customer is only making a renewal decision once per year, instead of 12x per year. Employing contracts can materially improve a startup’s cash position, unit economics and predictability.
6. Your Startup’s Unit Economics
Your pricing plan has to enable the company to become profitable at some point. The value of your business is the discounted sum of all its future profits. Adopting a lower price point may increase sales velocity, create lots of demand, and keep sales teams happy, but if the price point doesn’t generate enough gross margin to achieve reasonably quick payback periods, and the business suffers from an increase in churn, the company is in trouble.
Just a quick reminder:
Payback Period = Cost of Customer Acquisition/Gross Margin
The gross margin is the revenue per customer minus the costs to provide the service. A decrease in price reduces gross margin and will consequently increase payback period.
7. Margin Structure of the Customer Base
Compared to software companies, grocery stores are terrible customers because grocery stores have single digit margins. The margin structure of your startup’s customers matters a great deal when setting pricing. All of your product’s cost must be paid from your customers margin. The more margin your customer has, the more they can pay you for your product.
Pricing Models: Seat-Based vs. Usage-Based
When to use per seat pricing
If your customers demand predictable bills, then per seat pricing is the way to go. The question is do they prefer it or do they demand it? Most customers will prefer predictability, but won’t necessarily demand it. Would they switch if the pricing weren’t predictable? That’s a question worth examining in your pricing research.
If you would like to create switching costs, per seat pricing with annual contracts establishes some lock-in. Usage pricing provides more flexibility to customers to try alternatives.
The Rise of Usage-Based Pricing
Usage-based pricing (UBP) or activity-based pricing (ABP) has emerged as a dominant model for many of today’s most successful software companies. As Lee Kirkpatrick, former CFO of Twilio, noted during Office Hours, “Twilio was one of the pioneers of usage-based pricing.” The company grew from $15M in ARR to more than $1B with this model, consistently achieving better than 130% net dollar retention.

The Strategic Advantages of UBP

Aligns vendor success with customer success: When a customer like Uber grows, their usage naturally expands, benefiting both parties. This creates genuine mutual interest in the customer’s growth.

Reduces adoption friction: Individual developers or small teams can begin using the product with minimal financial commitment, making it easier to start a relationship that can expand over time.

Manages cost structure: For companies with significant COGS (cost of goods sold), UBP allows better management of gross profit by passing through costs when appropriate.

Enables natural expansion: MongoDB and Ethereum, two database companies with nearly identical revenue trajectories through 2020, both employ usage-based models that have supported their explosive growth.

Lubricates the conversion funnel: Prospects can sign up and grow their accounts seamlessly. Usage data feeds product-led growth (PLG) lead scores, enabling account executives to outbound to the most promising users. As customers’ needs evolve, they can expand naturally without friction.

The Hidden Costs of UBP
While UBP offers many advantages, it does come with tradeoffs:

Complicates churn measurement: If a customer uses your product intermittently (every third month, for example), standard monthly churn calculations will show the account churning and reactivating, skewing your metrics.

Challenges sales compensation: Building effective compensation plans for sales teams is more difficult because the value of an account can’t be fully measured at the point of sale. Teams must reinvent their GTM strategy with new quota structures, sales materials, and margin calculations.

Makes capacity planning harder: With less visibility into maximum usage requirements, engineering teams may struggle to provision infrastructure appropriately.

Requires ongoing purchase decisions: Customers must implicitly or explicitly decide to continue using the product each billing period, rather than making a one-time annual commitment.

Customer frustration with estimation: Customers may struggle to estimate how much of a product they’ll use and experience surprise from overage charges. This creates anxiety in the purchasing process that doesn’t exist with more predictable seat-based models.

Longer sales cycles: Recent data shows usage-based pricing models experienced 29% longer sales cycles in 2023 compared to 21% for seat-based companies. Enterprise-focused companies with usage-based pricing bore the greatest increase at 44%.

The Evolution of Usage-Based Pricing
Many successful companies begin with pure UBP and then evolve their pricing models over time. As Twilio demonstrated, even usage-based companies can create predictable revenue streams by implementing annual contracts with committed usage levels, with overages billed at higher rates (a two-part tariff).
Amazon Web Services exemplifies this hybrid approach with a “spot market” for instances charged via usage alongside a “reserved instance” market where capacity can be pre-purchased for discounts of about 50%. Similarly, Salesforce began with a usage-based approach before shifting to annual seat contracts when churn rates became significant and revenue predictability faltered.
The Deliberate Underselling Strategy
One powerful strategy for usage-based pricing is deliberate underselling. As Lee Kirkpatrick shared, Twilio account executives would intentionally undersize initial contract commitments to:

Ensure customer happiness and success
Create natural opportunities for expansion conversations
Accelerate the initial sales cycle
Improve net dollar retention metrics

While this approach trades smaller initial deals for long-term growth, it creates healthier customer relationships and more efficient expansion opportunities. With this model, Twilio maintained contracted revenue at less than 50% of ARR while achieving industry-leading retention metrics.
Implementing Usage-Based Pricing
When selecting a usage-based pricing model, ask these three questions:

Is my startup selling an application or infrastructure?

Application software companies typically sell seats. Infrastructure companies sell API calls, licenses per core or host, SMSs, bandwidth, storage by the GB. Switching from the norm in your category introduces friction.
Most application software companies don’t sell via UBP. Slack is a notable exception. Selling constant seat counts stems from the perception that the number of people using software shouldn’t change much from one month to the next. For most application software, the predictability of fixed costs outweighs the benefits of flexibility.
Infrastructure usage, however, can vary widely depending on:

Seasonality (retail traffic spikes in Q4)
Developer activity (migration from one architecture to the next)
New product launches
Other business-specific factors

Selling UBP to a buyer accustomed to buying a flat seat count introduces friction into the sales process. This effort may not be worth it unless your company’s strategy is specifically to differentiate on price structure.

Company
Product
Unit
Pricing

AppDynamics
APM
CPU Core
$6 / core / month

ScoutAPM
APM
API Call
$1 / API call / month

Lightstep
APM
Service
$85 / service / month

Instana
APM
Host
$75 / host / month

Splunk
APM
Host
$55 / host / month

DataDog
APM
Host
$31 / host / month

Even within the same category (Application Performance Monitoring), companies use different units for their usage-based pricing. This diversity can be an advantage: it makes it harder for customers to directly compare prices. How many API calls per host or services per host equal $31 per host per month? The difficulty in comparison potentially reduces price competition.
However, it might also confuse customers who are accustomed to buying the service in a different way. Consider whether your startup is differentiating on pricing to compete with an incumbent, or if you’re selling a superior product at a premium, in which case using the same pricing model with higher fees reinforces your brand positioning.

What should my unit of pricing be?

The goal of UBP is to align the cost of software with the value. The unit of pricing is crucial to unlocking that alignment.
The unit must be:

Easy for a customer to understand
Simple to predict
Crystal-clear to avoid future disputes about what constitutes a unit
Directly tied to the value delivered by your product

Can this pricing model achieve certain boundary pricing conditions?

How much should a Fortune 500 bank pay for your startup? How about a 50 person SaaS company? The pricing scheme needs to satisfy these boundary conditions.
Often, a straight UBP pricing model doesn’t scale into the enterprise. A Fortune 500 company may not consume enough units to justify a $250k or $2M deal. To remedy this challenge, consider introducing pricing layers:

Basic units cost $1
HIPAA-compliant units cost 3x as much
FINRA-compliant units cost an additional dollar per unit

Another approach is adding a platform fee to create a two-part tariff. The platform fee instantly boosts the annual contract value and can be tailored per customer segment.
Managing Customer Concerns with UBP
Some customers fear the sticker shock of dramatic usage in the first billing period. To offset this risk, many sales teams cap the charge in the first billing period to ensure customers who sign up and use substantially more of a service don’t experience bill shock. This approach builds trust and gives customers time to adjust to the usage-based model.
A hybrid approach: Two-Part and Three-Part Tariffs
There are many companies who employ a two-part tariff: a base platform fee and an ongoing usage fee to capture positive aspects of both types of pricing strategies. Segment is a good example of this. The platform fee establishes a stable relationship and the usage pricing enables the customer to scale up or down as a function of their traffic which might vary throughout the year.
Modern behavioral economics points toward three-part tariffs as potentially the optimal structure, especially when the number of vendors in a category is small. In a three-part tariff, the software has a base platform fee, but the fee includes a certain amount of usage for free, and each additional unit of usage costs extra.
For example, the software might have a base platform fee of $25,000 because it includes the first 150k events for free. Each marginal event costs $0.15.
Research suggests 3PTs capture more value because customers tend to buy larger plans than they might need. Customers who switch to a three-part tariff increased their usage by 15.1% on average, while those who remained on a two-part tariff increased usage by only 0.9%.
Challenging Pricing Models: Veblen Goods and Performance Pricing
Startups struggle to set the right price for their products because pricing dynamics in the field don’t obey the laws taught in the classroom. The standard supply and demand curves imply that as price increases demand decreases, but this isn’t always the case.
Veblen Goods in SaaS

Veblen goods defy traditional pricing theory. Demand for Veblen goods increases as prices rise. This behavior is commonly observed with luxury goods, but it also manifests in SaaS sales processes, particularly for enterprise customers.
Bill Macaitis, the former CMO of Zendesk, described Veblen goods behavior when Zendesk began to address enterprise customers. The product marketing team initially charged a modest premium for the enterprise product, but demand was immaterial. As they experimented with other price points, the team discovered demand surged as the price ballooned. Today, the Zendesk enterprise plans cost 10x as much as standard plans.
Enterprise buyers often equate price with quality. At a very small price point, they ask: Since the product is so inexpensive, is it a toy or true enterprise solution?
Performance Pricing Challenges
Performance pricing means explicitly pricing a product in terms of the customers’ revenue gained or cost reduced from its use. Conceptually, performance pricing is very rational. The buyer should be willing to pay between 10 to 15% of the revenue or cost savings for the use of the product.
But performance pricing has three significant challenges:

It cedes pricing power to the customer. Each year when the contract comes up for renewal, the customer will ask, “What have you done for me this year?” If the SaaS startup cannot continuously improve the performance for the customer, the customer is bound to churn.

It commodifies the category by reinforcing a single dominant purchasing parameter: performance. Vendors will all compete on percent improvement of the key metric, leading to discounting and price erosion.

Sales teams lose leverage. If the only metric that matters is performance, then great account executives won’t be able to shine. Building a relationship won’t be valued in the category, or at least it’s not enough to overcome sub-par performance.

The Impact of Economic Conditions on Pricing Strategy
Economic conditions significantly impact the effectiveness of different pricing models. During economic contractions, sales cycles tend to lengthen, particularly for usage-based pricing models.

Recent data from 2023 shows:

The average startup saw a 24% increase in sales cycle length compared to early 2022
Enterprise-focused companies experienced a 36% increase, twice that of Mid-Market and SMB focused companies
Usage-based companies suffered greater increases in sales cycle than seat-based companies: 29% vs 21%
Enterprise-focused companies with usage-based pricing bore the greatest overall increase at 44%

These statistics suggest that during economic uncertainty, predictable pricing models become more attractive to buyers who need to carefully manage budgets. Companies may need to adapt their pricing strategies during these periods, potentially by:

Increasing sales pipeline-to-quota coverage ratios
Focusing more on annual contracts with predictable costs
Offering capped usage options to reduce buyer uncertainty
Emphasizing ROI and cost savings in sales materials

AI’s Impact on Pricing Models
In a world where AI agents are 2.5-3x as productive as humans, software pricing will need to evolve. The traditional SaaS business model of annual prepaid contracts based on seats faces challenges when a human is no longer operating the software.
There are a few alternatives for AI-driven products:

Triple the per seat price: If the AI agent is 3x as productive as a human, the software company could charge 3x as much per seat. This would be a significant increase in price, but the value of the software would be much higher.

Move to usage-based pricing: AI software might be priced like databases, charging for compute. This aligns value well but may inject unpredictability into the pricing model.

Pay for performance: Some AI companies are exploring charging for outcomes. If an AI agent replaces a role that is compensated for specific outcomes, then pricing could align with those outcomes.

Looking at current AI pricing trends in SaaS, there’s significant variance. Google charges more for their AI features than the base seat, while Loom charges about a 33% premium. The ratio of AI price to base price ranges from 0.32 to 1.11 across major SaaS vendors. This variance indicates that the market is still determining the optimal pricing approach for AI capabilities.
Common Pricing Mistakes to Avoid

Complex or unintuitive pricing model. A good pricing model appears simple and logical to the customer. It may be complex behind the scenes, but the tax should align itself to the customer’s perception of ROI clearly.

Moving to annual prepay too late. Annual prepay generates cash flow to accelerate growth. Customers effectively lend the startup money to grow. Push for it as early as possible.

Employing static pricing. Price demand curves aren’t static. They change with time as your marketing team builds a brand, develops reference customers, and creates ROI case studies.

Failing to embed concessions in the proposal. When selling to mid-market companies, structure proposals with the expectation that procurement teams will negotiate lower prices.

Using the wrong price discovery questions. When asking customers about pricing, focus on relative price rather than absolute price. How much are they willing to pay compared to another product?

Conclusion
Like product development, developing pricing is a never-ending exercise. A startup’s environment, its product and its positioning change with time, and price must evolve in tandem. The best way for a startup to ensure its price is reasonably optimal is to create a framework for evaluating price and revisit the data a few times per year.
To end this conversation on pricing, I’ll quote Lawrence Steinmetz who wrote a book on sales called How to Sell at Margins Higher Than Your Competitors: “The first thing you have to understand is the selling price is a function of your ability to sell and nothing else. What’s the difference between an $8,000 Rolex and a $40 Seiko watch? The Seiko is a better time piece. It’s far more accurate. The difference is your ability to sell.”
Sales, marketing, product and pricing, when aligned, create powerful branding and margin-expansion effects.
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