
Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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Join companies like Zoom, DocuSign, and Twilio using our systematic pricing approach to increase revenue by 12-40% year-over-year.
Effective pricing strategy is the cornerstone of sustainable growth for tax management applications, directly impacting customer acquisition, retention, and long-term revenue performance. In this highly regulated and compliance-driven sector, pricing strategy requires a delicate balance between value perception and operational realities.
Tax management software faces unique pricing challenges due to the complex regulatory environment it operates within. Unlike general SaaS applications, tax management solutions must address multi-jurisdictional requirements, frequent regulatory updates, and high-stakes compliance risks. This complexity makes it difficult to establish standard pricing metrics that accurately reflect the value delivered.
Traditional per-seat licensing models often fail in tax applications because they don't align with how value is actually created—through risk reduction and compliance assurance rather than user activity. According to research, rigid per-seat licensing has led to customer churn as tax teams vary in size and interaction intensity with the platforms [3].
Tax management applications struggle with balancing transaction-based pricing (reflecting actual usage) versus value-based pricing (reflecting risk mitigation). This industry has seen flat-rate pricing models fail to accommodate varied customer sizes or usage patterns, leading to customer dissatisfaction and perceptions of unfair pricing [3][4].
The rise of AI capabilities in tax software adds another layer of complexity. Underpricing AI features has led to undervaluation and impacted margins due to the high cost of AI development and operation. Yet, pricing these features too high risks limiting adoption of potentially transformative capabilities.
Tax management applications serve diverse customer segments with dramatically different needs:
Successful pricing models must accommodate these varying needs without creating overly complex structures that confuse the market. As the research indicates, a one-size-fits-all approach misses opportunities for differentiation in SMB versus enterprise segments.
The tax software industry is undergoing a significant shift toward hybrid usage-tiered pricing models that allocate costs based on transactions or volume plus AI activity metrics [4][5]. This shift requires sophisticated usage tracking capabilities and customer education about the new model.
Companies like Avalara, Vertex, and TaxJar have all adopted tiered models with various approaches to incorporating AI capabilities—either bundled in higher tiers or as separate add-ons. This reflects the industry's recognition that different customer segments value AI capabilities differently and are willing to pay accordingly.
Monetizely brings specialized expertise in transforming pricing models for complex software applications, including those in regulatory and compliance-driven spaces. Our approach to tax management applications focuses on aligning pricing with both value delivery and market expectations.
While we don't exclusively focus on tax management software, our experience with similar technical platforms provides valuable cross-industry insights. For instance, we helped a $10 million ARR SaaS company transition from an ad-hoc pricing model to a strategic approach that aligned with their go-to-market strategy, resulting in reduced sales friction and improved monetization of strategic features.
For tax management applications, Monetizely employs a comprehensive approach:
Pricing Diagnostic: We identify opportunities for pricing model improvement through comprehensive financial analysis, stakeholder interviews, and sales data evaluation—with special attention to the unique compliance and regulatory aspects of tax software.
Customer Segmentation & Needs Mapping: We develop detailed segmentation specific to tax management software users, mapping needs across SMB, mid-market, and enterprise customers with attention to compliance requirements.
Usage and Value-Based Model Development: Our team specializes in implementing sophisticated usage-based pricing with platform fee guardrails, similar to our work with a $3.95B Digital Communication SaaS leader where we implemented usage-based pricing while preventing potential revenue reduction.
Pricing Research: We employ multiple methodologies to validate pricing approaches:
Monetizely offers tax management software companies two primary service models:
By leveraging our proven methodologies and cross-industry experience, Monetizely helps tax management software companies develop pricing strategies that capture the full value of their compliance expertise, technological capabilities, and ongoing regulatory investments.
[1] https://www.invespcro.com/blog/saas-pricing/
[2] https://www.textmagic.com/blog/saas-pricing-models/
[3] https://www.invespcro.com/blog/saas-pricing/
[4] https://www.subscriptionflow.com/2023/12/saas-pricing-trends-to-boost-sales-revenue/
[5] https://fungies.io/saas-pricing-models-and-strategies-how-to-price-a-saas-product/
Join companies like Zoom, DocuSign, and Twilio using our systematic pricing approach to increase revenue by 12-40% year-over-year.
1
None of the other premier consultants have actually implemented complex pricing within companies like Twilio and Zoom. This requires operational systems understanding, not just strategy.
In addition, other consultants often "over egg the pudding", they know customers will buy approaches as long as they look/feel scientific, yet we have multiple customers who have spent more >$100k each on conjoint analysis which did not help them at all. We are careful with where we ask you to spend your money.
2
Willingness to pay is context-dependent and works best when analyzed alongside packaging and pricing metrics. We use structured surveys like Van Westendorp, Max Diff, Conjoint Analysis as well as in-person research interviews to gather actionable data.
3
The cost of milk or a McDonald's burger inflates. However, SaaS prices almost always deflate and requires both adjustment of product packages as well as innovation to remain relevant.
Additionally, AI adoption will drive a shift from user-based pricing to more usage/consumption based models to accommodate the very high costs of serving these products. Expect to see deflation over time here as well as the the cost of serving AI products drops by multiples every month.
4
We want to monitor discounting % per package, usage of features within the packages, upsell rate of features to see whether we have a good pricing motion or whether it needs adjusting.
5
The Monetizely team has over 28 years of collective experience in software pricing, having previously worked with industry leaders like Twilio, Zoom and DocuSign, ensuring expert guidance in SaaS pricing strategies.
6
We recommend doing a better job on the pricing testing phase and to mitigate risk roll out the pricing in a phased manner.
For 80-90% of cases, we do not recommend A/B testing as that creates too much market confusion and overhead (in certain cases, doing an advance roll out in a different geo can work).
7
Competitive information is helpful but only a small piece of the picture. Competitors are in different stages of growth. Their product functionality is also different.
We recently had a client where sales teams pushed for lower pricing to compete with current rivals, but the company’s strategic vision aimed to evolve into a new category, making the competitive pricing data less relevant.
8
To kickstart your SaaS pricing optimization, consider consulting with the experts at Monetizely. You can also deepen your understanding by reading our book "Price to Scale" and enrolling in "The Art of SaaS Pricing and Monetization" course on Maven. These resources are crafted to equip you with the necessary skills and knowledge to refine your pricing strategy effectively.