In a recent YouTube video titled "How should you price a new SaaS product feature? Ask Monetizely," Akhil Gupta, founder of Monetizely, provides a comprehensive framework for SaaS executives facing the common challenge of pricing new product features. The video offers a systematic approach to making feature pricing decisions with confidence, drawing from Monetizely's expertise in SaaS pricing strategies.
The Critical Decision: Package Integration vs. Add-On
When introducing a new feature, the first crucial decision is whether to include it in an existing package or sell it as an add-on. Akhil presents a decision matrix based on two key factors:
"This comes down to two key factors that create a decision matrix. Number one, customer demand. How many customers want these features? Number two, willingness to pay, how much extra would they pay for it," explains Gupta.
This 2×2 matrix creates four distinct scenarios that guide your pricing strategy:
1. High Demand, Low Willingness to Pay
When many customers want the feature but aren't willing to pay extra for it, the optimal strategy is integration into your main product lineup. These features strengthen your core offering and improve overall value perception without separate monetization.
2. High Demand, High Willingness to Pay
This represents the ideal scenario for tier differentiation. As Akhil notes, "Use these features to differentiate your premium tiers, driving upsells and increasing revenue per user." These capabilities become powerful motivators for customers to upgrade to higher-priced plans.
3. Low Demand, High Willingness to Pay
When a smaller customer segment highly values a specific capability, targeted add-ons make sense. Akhil advises, "Create a targeted add-on. A smaller subset of customers values this capability and will happily pay well for it." This approach maximizes revenue without forcing unwanted costs onto your broader customer base.
4. Low Demand, Low Willingness to Pay
In this scenario, Akhil recommends caution: "Reconsider developing this feature or delay monetization until you have proven more value." These features may not justify immediate development resources or could benefit from further refinement before monetization.
Three Primary Approaches to Add-On Pricing
If you determine an add-on approach is best, Akhil outlines three primary pricing models:
1. Fixed Price
This straightforward approach sets a single price point for all customers. However, Akhil cautions about scalability issues: "Simple, but doesn't really scale with customer size. It might seem expensive to smaller customers and be too cheap for enterprises."
2. Percentage of Base Fees
This model scales naturally with customer size, typically ranging from 5-20% of the base subscription. Akhil illustrates: "If a customer pays you $50,000 for your base product, a 10% add-on would cost them $5,000." This approach ensures proportional pricing based on customer value.
3. Usage-Based Pricing
This approach links costs directly to consumption metrics. As Akhil explains, "Your add-on charges per user, per interaction, or another consumption metric directly tying cost to value." This creates a fair value exchange as customers pay based on their actual usage.
Setting Appropriate Price Points
For determining actual price points, Akhil suggests establishing clear boundaries:
"Your upper bound should typically be 10 to 20% of the ROI your new feature delivers. Let's say if you save a customer $100,000 annually, they might pay $10,000 to $20,000 easily. Your lower bound, on the other hand, should cover your COGS or match competitive alternative prices."
This approach ensures your pricing captures a fair portion of the value created while remaining competitive and covering costs.
Real-World Example: AI Analytics Dashboard
To illustrate the framework, Akhil provides a practical example:
"Let's say you're adding an AI analytics dashboard to your support platform. Around 30% of your customers are very interested, which you can say is moderate demand and would happily pay up to 15% more. So you can see high willingness to pay. This is perfect add-on territory since the value comes from insights rather than usage volume. A percentage of base fee makes sense here."
He continues by explaining the ROI calculations: "If it saves support teams about 50,000 in annual value, pricing it at 10% of the base subscription captures fair value while still delivering a 10x ROI to the customers."
Balancing Value Capture with Adoption
Akhil concludes with an important reminder about the dual objectives of feature pricing: "Remember, Feature pricing balances capturing value with encouraging adoption. Use this framework to make strategic decisions that support sustainable growth."
This framework is just one of many approaches covered in Monetizely's book "Price to Scale," which includes case studies from Oracle, Gainsight, and Citrix. The comprehensive guide dives deeper into add-on pricing strategies with real-world applications.
By applying this systematic approach to feature pricing, SaaS executives can make more confident decisions that maximize revenue while ensuring customer value and driving sustainable growth.