This is Nauta’s essential introduction to software pricing and packaging, based on a workshop we host for founders, but, as you can imagine, there is significantly more detail behind it.

These concepts will be helpful in shaping the initial pricing model at Pre-seed and Seed stage, but the real pricing optimisation (with extensive customer research and analysis) isn’t necessary for companies before the Series A stage.

In this guide we cover:

• Pricing essentials
• Value metrics
• Price targeting  
• Tier package construction
• Pricing in GenAI
• Shaping GTM

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Pricing Essentials

Why is pricing a key tool for success?

Pricing and packaging are intrinsically linked to your business model and is vital to success. It defines the incentives of your business: why should people spend money / time on your product and how they benefit.

ProfitWell found that spending money on monetization (pricing) was ~4x more efficient than acquisition and ~2x more efficient than retention in improving growth in SaaS companies.

Being unable to command a proper price can signal deeper commercial issues, such as product quality and differentiation, positioning or customer targeting.  

Who should decide pricing?

Typically, in a bigger company, there will be a pricing committee with the following team composition:

• Management and Finance
• Sales
• Marketing
• Product

For early-stage startups, it’s common that founders will cover all four of those roles but make sure to factor in the value from each perspective.

What are the main pricing strategies?

Why is it important to review pricing?

As your product evolves, so should its pricing. Ideally it should be reviewed 1-2 times annually, to reflect product changes and market conditions.

Pre-seed and Seed: At this stage, you’re a small team with an unvalidated product. It’s natural for customers to view your company as lower in value compared to more established competitors. Affordability helps you lock in early adopters to go on the journey with you. It’s also unlikely you’ll have ROI proof points so may need to base the price on competitive benchmarks rather than value-based.

Series A and beyond: As you develop and improve the product, it becomes differentiated and outperforms competitors. it also becomes easier to demonstrate ROI with several case studies under your belt, meaning customers can recognise the value and are willing to pay for a premium product with value-based pricing.  

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Value Metrics

Value metrics are essential to a SaaS pricing strategy

The value metric is the primary metric that is used to determine which pricing plan a customer will use or how much they will pay.

Examples:

• If you’re selling coffee, it’s usually the volume of liquid (small, medium or large)
• For Uber it’s the journey distance and duration
• For Google’s Workspace (G Suite) it’s the number of users

A good value metric:

• Allows the price to correlate with the value a customer gets ‍
• Simple and easy to understand
• Aligns with the customer needs (predictable)

A good guideline is: value delivered should be 10x greater than the price. E.g. buying software for £10K that saves £100K a year becomes a no brainer.

Case studies

Zapier: the number of completed tasks per month. This is simple to understand, the price clearly correlates with the value, it aligns with what the customer wants (completed tasks that save time), and finally the value is much greater than the price: doing 50K tasks and paying £350 seems like great value (>10x ROI).

Mailchimp: has more than one value metric. In the past, they only charged for the number of contacts – now they also charge for the number of emails sent and number of users. Things like customer support can be additional feature requirements on top of the value metric.

What if there is no clear value metric?

1. Combine several (like Mailchimp)
2. Avoid cost-based pricing
3. Beware of defaulting to ‘# of users’ as this doesn’t necessarily correlate with value
4. The value metric can be augmented with feature requirement price targeting (discussed below)

Optimal pricing is not based on the value metric alone 

Returning to the Zapier example, The Team vs Company plans can be set to offer identical task limits (the value metric), but produce different pricing based on the included feature, such as user count, support level, shared connections, data retention – tailored to customer requirements.

Price Targeting

Ideally businesses would charge every customer the maximum price they’re willing to pay. However, this would require months of negotiations isn’t possible for startups (although enterprise sales teams do try). But price targeting enables a crude version of this.  

A simple example might be a merchant at a market who quotes a higher price to someone wearing an expensive Rolex. Since software providers can’t ask if you are wearing a Rolex, they must find other proxy variables to understand a customer’s willingness to pay (WTP).  

Price targeting identifies different customer segments that are willing to pay different amounts for an identical or similar product (ideally without impacting other groups), to extract maximum value. Examples include student discounts and own-brand staple items:

Price targeting is everywhere in SaaS when you know what to look for

Suddenly everything on a pricing page makes sense! Enterprises are willing to pay more than startups for software, so what is the ‘Rolex signal’ for enterprise customers? Well, they want things like single sign-on, complex user permissions, dedicated support managers and compliance features.

Customer segmentation

Now we know we are looking for high willingness to pay customers, how do we know what ‘Rolex’ to look out for and what features to offer?  

Constructing tiers and packaging requires customer research and segmentation. For Zapier, that likely will have been the result of extensive customer research to produce something like this:

You can see clearly how the different packages cater to each of the customer segments and allow all of them to access the same fundamental product with vastly different prices.  

By way of comparison, Zapier in 2016 had NO clear user segments identified and their pricing page, below, looks like a lot of the pricing pages in early-stage companies: “there’s a free plan for people to trial the product, there’s a paid plan for users that are using some of the more advanced features, then there’s a more expensive plan for customers that need multiple users on a single account.”

How do you build an understanding of your customer segments?

Customer interviews and, for large numbers of customers, surveys are vital for understanding willingness to pay and customer requirements. For a great example of what this looks like you can see this walked through example with Xolo’s Mikko Teerenhovi.

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Tier Packages

Tier bundles should be based on WTP and popularity

There are four types of features: “Junk”, “Core”, “Differentiable” and “Add-ons”.

All the ‘Rolex’ features (meaningful to most customers in any one segment) used to construct pricing tiers should sit in the “Differentiable” quadrant (e.g. dedicated customer support, multi-user accounts, high usage limits, etc.).  

Meanwhile the “Add-ons” quadrant is for offerings that don’t have a sufficiently large segment to justify a pricing tier (e.g. custom integrations) and should be charged as one offs or bolt-on add on packages. The “Core” quadrant is for features that most customers want or need but aren’t willing to pay (much) for which should be included in every plan. Finally, the “Junk”, low WTP features that you shouldn’t build, or if you’ve built them, then don’t list on the pricing page at all.

Can you just have one tier?

Having one tier implies that your customers are largely all the same and have the same needs and willingness to pay. It also means you will have no upsell potential or downsell tools (retention offers) in the future, so it’s very rarely optimal.

Examples of tier types

The pricing tiers used by software companies can vary. There’s no right answer, but usually they must suit how customers would like to pay for products. For examples, Stripe charges a % of transaction value because they handle the payment flow so can deduct this easily without ever requesting funds, while AWS and Monday.com couldn’t do this.

• ‍Pure value metric based: Flat transaction rate, scales very well whether the customer is a small or very large business‍
• Value metric based with a volume discount: As you use more, you get a volume discount. This works well for customers of all sizes and the volume discount helps you stay competitive
• ‍Tiers: Monthly contracts with limits, making your pricing more predictable and simpler for billing and quotes, as well as giving a minimum contract value to ensure customers pay enough to justify the cost to serve‍
• Feature-based tiers: Any combination of value metrics and features packaged into tiers, as mentioned above‍
• Pre-paid credits: this works for anything with pass through costs that the company will have to pay in advance. Popular for market research businesses that reward survey participants before they get paid by their customer‍
• Multiple variables: Of course you can combine multiple variables.

What about GenAI applications?

GenAI is impacting all kinds of software products, but the principles for pricing are exactly the same with only minor differences, most notably, the cost of running the models or LLM queries to serve customers.

Most software companies have not had variable compute cost to serve each client, other than negligible cloud costs, for quite some time. However, the cost per million tokens is dropping exponentially and will likely become negligible for most businesses.

In cases where that cost is not (yet) negligible, the GenAI boom has meant usage caps are more commonly included in pricing tiers to prevent customers from becoming too unprofitable (e.g. starter plan: 50 queries per day).  

This may correlate with product value, but cases where the cap doesn’t correlate with value (and is included to prevent costs exploding) are examples cost-based pricing overriding value-based. Where there is cost-based pricing it’s often a signal that there’s some level of commodification, so it’s important to check how differentiated the GenAI element is.

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Shaping Go-to-market (GTM)

Annual contract value (ACV) dictates what GTM efforts you can justify

In the early stages, it’s okay to get feedback and handhold customer through the sales process, even if it’s just to secure a £2k/year client.

However, this approach doesn’t scale – you can’t sustain low-value and high-touch sales long-term. The key is evolving your GTM strategy as you grow and making sure the company isn't unsustainable.

Technically, ACV here should be “ACV assuming >75% Gross Margin” which would account for businesses that have significant technical or service costs per incremental client.  

Stated in different terms, this is a measure of a company’s efficiency and the speed it can scale – how quickly are you able to recycle cash generated from sales back into the top of the funnel and is a huge predicter of success. In the chart below, the further above the line you can get the better.

If your ACV doesn’t justify the GTM effort, it is worth revisiting the sales process to understand if it can be shortened or are there features that can push your ACV upwards. Without addressing this misalignment, you risk investing resources into something that won’t work/scale. The further above the line you can get the better!

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Summary

How to develop a well constructed pricing and packaging for your startup

1. Consider the best value metric(s) (simple to understand, price correlates with value a customer, charging schedule aligns with customer expectation, value generated is 10x the price of the product)
2. Define user groups / segments to understand their different characteristics, feature requirements and WTP
3. Construct different pricing tiers that target the different customer segments with different pricing levels
4. Bundle features appropriately (Differentiable, Add-on and Core)
5. Ensure pricing levels are sufficient to justify GTM and service efforts required