Introduction

It is no exaggeration to say that pricing can make or break a business.

Price too low, and a business leaves money on the table (or worse, risk operating at a loss). Price too high, and customers will walk away.

Setting prices isn’t necessarily that complicated. For many businesses – a grocery store, for example – pricing is a simple mix of factors such as input price, quality of the product, level of competition, and demand.

But for SaaS vendors with complex products, sometimes with near-zero marginal cost, pricing becomes a much tougher decision. Companies often take a simplistic approach instead, which comes down to guesstimating and trial-and-error.

Yet product pricing is a powerful lever that has the capacity to boost profitability, sales revenue – and, done right, boost customer satisfaction.

Pricing is therefore a core competency for any SaaS business.

In practice, that competency can be found lacking as product teams find it challenging to effectively pull the pricing lever. Pricing methodologies can help.

One commonly used methodology is value-based pricing, but implementing value-based pricing is much easier said than done.

In this guide we explain why value-based pricing remains the strategy of choice for many SaaS vendors, and address the challenges behind value-based pricing.

We also outline several essential strategies that will help product teams implement value-based pricing to successfully drive profit maximization.

Mechanics

SaaS vendors have a choice of suitable pricing methodologies, including dynamic pricing, competition-based pricing and penetration pricing. Nonetheless, value-based pricing is one of the more commonly adopted methods.

Companies that use value-based pricing set product prices based (primarily) on the customer’s perceived value of the product. That’s in contrast to, say, the cost of delivering the service, or the prices set by market competition.

Value-based pricing is customer-focused and involves setting prices that customers are willing to pay based on the benefits and outcomes they expect to gain from using a software product.

It is granular too. With value-based pricing a single product can be divided up into tiers with increasingly generous features. Just think about it: we’ve all signed up using SaaS pricing pages with good, better, best options. Each incremental group of features carry increased value for the customer, and a price jump that benefits the vendor.

Just like any other methodology that supports a fact-based decision, value-based pricing relies on several “input variables” or factors. Knowing what these factors are helps us to understand where the challenges lie in setting value-based pricing. It also helps us understand what we can do to make value-based pricing effective.

To set prices using the value-based-pricing methodology, a business needs quantitative or qualitative data to answer the following questions:

• Perceived value: The foundation of value-based pricing is the value that customers perceive, e.g. the problems your product solves, the efficiency gains it offers, or the revenue boosts it delivers.
• Value drivers: What is driving this value? These drivers could include time savings, cost reductions, or revenue enhancements.
• Economic value estimation: Perceived value is one thing, but companies also need to gauge what economic value a product provides to customers, compared to the next best alternative.
• Willingness to pay: Perceived and real value may be there, but the customer’s perception matters just as much. Vendors must determine what value the customer places on the outcomes they receive from a product and what price they are willing to pay for these outcomes.
• Customer segmentation: Different customer segments may perceive the value of a product differently. Tailoring your pricing strategy to different segments enables revenue maximization and also supports customer satisfaction.
• Competitor pricing: While value-based pricing focuses on customer value, understanding competitor pricing provides a useful reference point, especially for new market entrants.

It is, clearly, a large volume of information that companies need to collect, understand, and monitor. It’s a mammoth task when undertaken on an occasional basis. But, of course, most SaaS vendors operate in a fluid business landscape – which means pricing requires constant review.

Continuously collecting the data that support pricing decisions in a dynamic SaaS business environment is extremely challenging without a structured, automated approach.

Key Factors

Just like any other methodology that supports a fact-based decision, value-based pricing relies on “input variables” or factors. Knowing what these factors are helps us to understand where the challenges lie in setting value-based pricing. It also helps us understand what we can do to make value-based pricing effective.

To set prices using the value-based-pricing methodology, a business needs quantitative or qualitative data to answer the following questions:

• Perceived value: The foundation of value-based pricing is the subjective value that customers perceive when they consider a product, based on their individual perspectives or needs. What need does a product fulfill, or what problem does it solve? Is there an elevated brand reputation, or an emotional connection to support perceived value?
• Value drivers: Beyond perceived value, vendors need to delve into more detail about the customer’s thinking. What are the objective factors that support perceived value? In solving a problem, value drivers could include time savings, cost reductions, or revenue enhancements. For a physical product, it may include characteristics such as durability and performance.
• Economic value estimation: The customer may perceive value, and this value is driven by a range of factors. But what does it boil down to in dollar terms for the customer? Vendors need to gauge what economic value a product provides to their customers, and also compare it to the next best alternative.
• Willingness to pay: Like perceived value, willingness to pay is subjective. Customers may perceive value, and may be aware of the economic benefits of a product – but they may or may not make rational decisions about their willingness to pay for the product. Vendors must determine both what value the customer places on the outcomes they receive from a product, and also what price the customer is willing to pay for these outcomes.
• Customer segmentation: Different customer segments may perceive the value of a product differently, and may have differing willingness to pay. Tailoring a pricing strategy to different segments enables revenue maximization and also supports customer satisfaction.
• Competitor pricing: While value-based pricing focuses on customer value, understanding competitor pricing provides a useful reference point, especially for new market entrants.

It boils down to a large volume of information that companies need to collect, understand, and monitor – and it’s a mammoth task which most SaaS product owners undertake on an occasional basis, at most.

But, of course, most SaaS vendors operate in a fluid business landscape – which means pricing requires constant review through a process that’s embedded into everyday operations.

Continuously collecting the data that support pricing decisions in a dynamic SaaS business environment is extremely challenging without a structured, automated approach.

Execution

Given the complexity of the value-based pricing methodology it is no surprise that the companies that succeed with value-based pricing rely on an established framework. This value-based pricing framework has four steps that support pricing success:

• Gradual introduction: For established businesses value-based pricing should be introduced slowly - starting with a small and preferably new segment of clients to identify issues and gather unfiltered feedback.
• Segment and package: Start by segmenting the customer base and packaging services to match each segment's perceived value and willingness to pay. Offer a selection of packages for a broader appeal, and allow opportunities for upselling.
• Set price points: Determine the optimal price for each segment based on internal research and analysis. It's a trial-and-error process that requires constant refinement, continuously incorporating customer feedback.
• Maintain communication: Essential for the success of value-based pricing, staying in touch with customers helps gauge the effectiveness of a pricing strategy and adjust as needed.

Again, the theory makes a lot of sense. It is not difficult to see how the steps above, following the mechanics of value-based pricing, will lead to optimal pricing. Customers are happy, because they perceive high value for what they pay for, while the SaaS vendor maximizes profits.

We know that value-based pricing works and we know how it works. But, for some reason, value-based pricing is rarely implemented consistently and effectively.

Challenges

The rationale for value-based pricing is clear, and the mechanics are not hard to understand, but SaaS businesses find mastering frequent, effective updates to value-based pricing tough.

Much of the difficulty lies around segmentation, packaging and – unsurprisingly – around setting price points. Most software companies spend just a couple of hours in aggregate on pricing decisions. That’s far too little and – worse, few companies review pricing at regular intervals. Even fewer companies embed pricing throughout their product decision making.

Then there’s the advanced pricing tools that also go unutilized. From strategically expanding through one-time premium features, to experimenting continuously with pricing models that balance revenue growth and customer retention.

The net result

• Pricing is inaccurate and does not reflect perceived value
• SaaS vendors express limited granularity in pricing
• Any value alignment that is attained simply drifts over time

Broadly speaking, the challenges around value-based pricing reflect a typical business problem: too little in terms of resources are applied to too large a task – a task that’s rarely given the needed priority.

How can we break this challenge down into components? We think that the challenges around value-based pricing can be broken up into four core areas:

Personas

SaaS vendors know that marketing personas matter for targeting, product development and marketing spend. But many are not aware that personas are just as important when it comes to value-based pricing. Developing personas are, however, relatively complex. By comparison, cost-based pricing is simple – cost facts are readily available.

Companies must build a profile of who their customers are, their needs, and willingness to pay. Constructing personas is a core competency for pricing – just as much as it is for other marketing activities. Yet companies can struggle with a lack of information to map personas to pricing – and often make little effort finding that information. Extensive market research and data analysis is the way to go, but amounts to manual work that is resource intensive. The dynamic nature of the market also means that personas will evolve, meaning ongoing analysis and adjustment of personas.

Expansion

Implementing one-time in-app transactions for ad hoc usage of premium features at a higher unit price is a strategic move to expand revenue. It entices users to experience the value of advanced features, potentially leading to subscription upgrades.

Balancing the pricing for these transactions can help achieve net-negative churn, as revenue from upgrades and additional purchases outweighs losses from downgrades and churn.

Dynamically applying value-based pricing on expansion options is virtually impossible without automation.

Packaging

Value-based pricing is more complex than setting mere price points and is not a one-size-fits-all exercise. Every price point is specific to an audience segment. Crafting the right pricing packages is surprisingly complex, as SaaS businesses balance offering too many options (confusing customers) and offering too few (missing diverse customer needs).

Deciding on package features and tier structures requires a long-term engagement to build a deep understanding of usage patterns and value drivers – over and above an understanding of personas. The level of analysis can be overwhelming in the absence of an analytical toolset.

Experiments

Experimentation is crucial to optimize value-based pricing, but it poses risks including customer backlash and revenue instability. Running A/B tests on pricing can be ethically and logistically challenging, and interpreting the results in order to make informed decisions demands sophisticated analytical capabilities.

SaaS vendors often do not have the internal analytical or marketing know-how to experiment consistently or successfully, which robs them of the knowledge to package and price optimally – and there’s a huge fear of getting it wrong.

Solutions

Getting value-based pricing right, consistently, is not dissimilar to making any other methodology work. It requires discipline, planning, and automated tools. Value-based pricing is simply too fussy, too granular, and too continuous in nature to attempt to address manually.

SaaS vendors need to find a way to “automate” or at least simplify the many steps involved in setting prices using the value-based pricing model. Steps that can help include:

Effectively managing personas and packaging

SaaS vendors must design and implement a comprehensive, repeatable approach to develop detailed buyer personas and segment the market based on customer needs, behaviors, and value perception. Personas must become a core competency in pricing – from demographics through to psychographic information.

Generative AI provides a kick-start to persona development by getting companies past the “blank page” dilemma. Data analytics provide another key source – including real-time insights, such as a regular look at competitor pricing pages to infer signals around willingness to pay, which can in turn be mapped to personas.

It is also important to use automation to support frequent, finely grained adjustment to personas that keep personas continuously updated. That ensures that persona definitions and market segments evolve with rapidly changing customer profiles and market dynamics.

Dynamic pricing

Embedded pricing as a core competency means pricing is not reactive and that pricing is not reviewed on an ad-hoc, occasional basis. Instead, it means updating pricing as frequently as is healthy for a business – and goes beyond pricing to also include product features and product packaging.

SaaS vendors need to build a dynamic pricing model that leverages real-time data insights to adjust pricing packages and tiers according to customer value perceptions and usage behaviors. That includes versioning and grandfathering to avoid alienating long-time customers.

Vendors can buy, or develop a tool in-house that uses analytics such as machine learning models to inform pricing decisions, ensuring that they reflect current market conditions, competitive landscapes, and customer willingness to pay.

This approach enables flexibility in pricing adjustments to maximize revenue while maintaining customer satisfaction.

Expansion revenue optimization

SaaS vendors should develop strategies for maximizing revenue opportunities beyond the initial checkout step. More value can be captured, and there’s more creativity in setting pricing plans.

An expansion revenue strategy goes beyond the initial sign-up to focus on up-selling and cross-selling premium features or higher subscription tiers. That includes accomplishing net negative churn - ensuring that unavoidable churn never exceeds one-time transactions plus subscription upgrades.

However, it also includes a thorough investigation of willingness to pay – because it ties so closely into charging the right price – the maximum price. That includes tying willingness to pay into finely-grained product packaging.

Vendors should facilitate easy access to premium offerings and encourage customers to enhance their product experience. That could be through an analytics SDK that drives in-app pricing. This strategy should also include customer engagement and retention tactics to build loyalty and encourage exploration of additional services or features.

Data-driven experimentation

Instilling a culture of pricing experimentation that normalizes A/B testing is key. Companies need to run A/B tests on pricing just as they do with outbound emails and landing pages etc. Integrate automation into price testing, and use a powerful data analysis tool to interpret the results.

Next, use experimentation platforms or custom-built tools to test pricing adjustments, new features, or market positioning, analyzing their impact before wider rollout.

This evidence-based approach allows for more informed decision-making, reducing risks associated with pricing, product changes and willingness to pay. That said, SaaS vendors also need tools to manage communications for customers that subscribed to plans that didn’t make the grade through testing – even if it means two month’s discount to help the adjustment.

Agile market intelligence

Maintain a proactive stance on market intelligence, continuously monitoring market trends, competitor actions, and customer feedback to swiftly adapt pricing and product strategies.

It includes real-time data collection. For example spotting changes on competitor pricing pages as soon as these happen, or noting down additional features or product categories. This approach supports agile responses to market opportunities and challenges, keeping the company competitive and aligned with customer expectations.

Adopting these strategies allows companies to flexibly apply the principles of value-based pricing – within the context of limited resources.

This framework supports the goal of embedding value-based pricing into everyday operations so that pricing becomes central to growth and customer satisfaction.

In Action

SaaS vendors that get value-based pricing right enjoy the benefit of maximizing revenue potential and customer satisfaction. They achieve this by tailoring prices to each market segment based on perceived value. In summary, companies that effectively deploy value-based pricing:

• Ensures no revenue opportunity is missed
• Expands their market reach
• Increases profitability without added costs
• Enhances market insight through research
• Improves product quality by focusing on customer needs
• Strengthens customer relationships through active listening and by driving value

It’s not just theory – there are many practical examples.

AppleBroad appeal

A simple but classic example of value-based pricing, Apple's strategy revolves around building a loyal customer base through a seamless tech ecosystem and prioritizing ease of use and design. This delivers real (and perceived value), and the company's pricing reflects that value - and not the production cost of individual devices.

McKinsey

Consulting services from firms like McKinsey & Company are priced based on the perceived value of their expertise, reputation, and the potential return on investment for their clients, rather than just the time spent by consultants - with McKinsey's billing rates running at the top end for consultancy work.

SquadCastIn-depth example

SquadCast Studios, Inc. is an example of a SaaS business that successfully value-based embedded pricing into their operations to see a significant increase in revenue, up from $120k ARR to $3.4m ARR. Not only did revenue increase, but SquadCast’s churn rate nearly halved.

The company achieved this success because value-based pricing aligned its pricing with customer value perception.

When customers feel that they are receiving a fair price for the value they are receiving, they are more likely to continue using the product.

By offering different pricing tiers based on usage and value, customers are encouraged to stay with the product and continue using it to its full potential.

SquadCast is an excellent example of the potential benefits of value-based pricing for SaaS businesses, but it doesn’t take long to find other examples, some of which are household names.

Not only did revenue increase, but SquadCast’s churn rate nearly halved.

Conclusion

Value-based pricing drives both revenue and customer satisfaction. It is an established methodology that is proven n practice, with many instances where SaaS vendors used value-based pricing to great effect. Nonetheless, in the absence of strategy, motivation and a capable toolset the implementation of value-based pricing quickly loses momentum.

And that momentum matters. With the SaaS market projected to reach $720 billion by 2027, SaaS businesses must pull the pricing lever to get the most out of the market growth. But the reality is that product teams are often stretched thin and are more inclined to prioritize other aspects of the product roadmap, while losing focus of pricing.

Help is available. Teams can take a more structured and more automated approach, systematically handling each step of the value-based pricing.

Working systematically to build personas – and building pricing on top of the results is the first step. Companies should also focus on dynamically building and adjusting pricing models, in response to both customer feedback and market intelligence.

But it’s arguably the need for automated, data-driven tools for each of these aspects that is critical, because it reduces the burden on the teams tasked with setting pricing.

We think that the companies that find the right combination of tools (or indeed a toolset) and combine it with a motivated

Introducing Price Lever

Multi-step, multi-faceted, cross-functional… and frequently changing. Setting pricing was never going to be easy – as much as value-based pricing provides a powerful methodology.

At Price Lever, we realized that SaaS vendors need a comprehensive toolset to support the value-based pricing process. A toolset that embeds pricing into any SaaS business in a way that delivers the needed pricing competency in a pick-up-and-play package – shrinking the learning curve.

As experienced founders in the SaaS space, the team behind Price Lever knows what it is like to have to frequently adjust product pricing – but faced just the same difficulties and made the same mistakes around setting product pricing as so many other businesses.

That’s why Price Lever developed a SaaS solution for a comprehensive, integrated approach that leverages our knowledge of value-based pricing, cutting-edge methodologies – and futuristic technology. Price Lever includes five integrated core components:

1. Persona Builder
2. Dynamic Packaging
3. Revenue Management
4. Test Suite
5. Real-time Insights

Price Lever integrates deeply into your value-based pricing methodology. It starts with an easy-to-use console app, with an API to plug into your software solution alongside a complete Software Development Kit (SDK) specifically designed to streamline the pricing process. We call this new category Embedded Pricing.

It includes a comprehensive toolset engineered to assist product teams in efficiently managing various aspects of value-based pricing.

Persona Builder

AI-powered tool that automates the creation of buyer personas, tailoring benefits and setting the features that align to personas. With Price Lever it is now easy to accurately identify and customize persona types which are responsive to dynamic customer needs and behaviors.

Dynamic Packaging

Don’t spend weeks and weeks fiddling with pricing, Price Lever’s dashboard allows product teams to swiftly integrate Stripe and create pricing packages. By leveraging data insights, Price Lever suggests optimal pricing tiers and package features that align with customer value perceptions and usage patterns.

Revenue Management

Get a direct grip on pricing-based revenue management, as Price Lever’s SDK directly integrates with vendor websites to price-manage one-time in-app transactions for premium features, allowing businesses to capture additional revenue opportunities and incentivize customers to explore higher subscription tiers.

Test Suite

Take the effort out of experimentation with our robust, automated tools for A/B testing of pricing. It includes an analytics toolset that helps support data-backed decisions on pricing adjustments to help product designers understand the impact of changes before full-scale implementation. Testing also offers communication and migration tools for users that ended up on pricing plans that didn’t make the cut.

Real-time Insights

Price Lever delivers continuous monitoring – starting with cost of goods sold, to ensure prices never fall below COGS. We also provide insights into product engagement to understand where “premium features” lie. Monitoring also covers competitor pages to spot pricing changes – identifying key signals around willingness to pay, and identifying new features offered by competitors.

Price Lever takes every step of the value pricing mechanism and applies intelligent automation to take away the friction, effort and uncertainty in setting value-based pricing.