In the recent video "7 Factors for Selecting Your SaaS Pricing Metric" from the channel "AI, SaaS & Agentic Pricing with Monetizely," a SaaS pricing expert shares a comprehensive framework for developing effective pricing strategies that work for both customers and businesses. The speaker draws from extensive experience working with numerous companies to identify the key considerations when selecting your pricing metric.
Finding the Balance Between Customer and Business Needs
The right pricing metric isn't just about maximizing revenue; it's about creating alignment between what customers value and what works for your business model. The speaker breaks this down into seven critical factors—three focused on customer perspectives and four addressing business considerations.
1. Customer Risk Perception
Early-stage companies often face skepticism from potential buyers who view them as risky investments. To overcome this hurdle, many startups implement creative pricing models.
"Early stage companies many times people don't take a bet on and that's why they move to something like a usage based pricing you say pay for what you use if you like it keep it," the speaker explains.
This approach reduces the perceived risk for customers who might otherwise hesitate to commit to an unproven solution. Performance-based pricing can serve a similar function, where the customer only pays when they see results: "Ads only when we convert you make money then we will get the revenue."
2. Mental Anchors
Industry norms create powerful pricing anchors that can severely limit your revenue potential if you don't recognize and address them. The speaker illustrates this with a compelling example:
"Historically customer service software is sold on per agent basis… their customers clients don't think any differently they're always going to pay per agent so that limits the ticket size for their software."
In contrast, a company called Helpshift took a different approach:
"Helpshift was making customer service chat software for gaming applications and was selling to product managers of companies like super cell so product manager said okay uh my metric can be 100,000 ma per 100,000 ma not by per agent so the same thing that was being sold for 20,000 was now being selling for $2 million."
By changing the mental anchor from "per agent" to "per monthly active user," they transformed a $20,000 deal into a $2 million opportunity—simply by aligning with a metric that made sense to their specific customer base.
3. Value Alignment
Your pricing structure must fundamentally align with the value your customers receive. If customers are paying more without seeing corresponding benefits, they'll quickly become dissatisfied.
"Customer needs to feel that as they win as they win they will pay you more not if they're not winning," the speaker emphasizes.
The example of Mixpanel demonstrates this principle in action:
"They always for product analytics charge on a per event basis but as they were going to more Fortune 100 Fortune 500 companies the companies were saying that hey our events are going up our bills are going up but we are not winning and we are not making more money."
Mixpanel adjusted their pricing from per-event to monthly tracked users, creating better alignment between customer success and pricing.
What Works for Your Business
The remaining factors shift focus to business considerations that ensure your pricing model is sustainable and practical to implement.
4. Consumption Patterns
Not all software is used in the same way, and usage patterns should influence your pricing model.
"What sort of product do you have does anybody even use your product? Because if they think your product is important they may not use it but still value it and it will be a sticky product like a lot of ERP softwares… we need this but we may not use it like how much compliance software are you actually going to use?"
For products that are critical but used infrequently, user-based pricing might make more sense than usage-based models.
5. Cost Structure
Your internal cost structure must be considered when designing pricing models, particularly for resource-intensive technologies.
"In AI there is so much development cost but there is so much cost to serve these models… if you do user based pricing this is why now none of the AI players especially the Enterprise players are not offering per user."
The speaker points out that traditional SaaS applications might have gross margins of 96-97%, making them more flexible with pricing models. However, AI companies face significant variable costs that often necessitate usage-based pricing to maintain profitability.
6. Competitive Action
Market dynamics force companies to adapt their pricing in response to competitors' actions.
"If one competitor comes in with a new metric that is getting adoption then you may have no room," the speaker warns. "If they are offering more innovative pricing then you may have just no option you just may have to move to something else or offer another alternative."
7. Implementation Constraints
Perhaps the most overlooked factor is the practical reality of implementing new pricing models, especially in larger organizations.
"Almost every interview I've done with pricing leaders at larger companies and my own experiences engineering doesn't care about pricing they will never put it on the road map," the speaker shares. "We had our GM of the business unit advocate for a pricing change and Engineering still did not listen."
Even with strong business cases, technical debt and competing priorities can make pricing changes difficult to implement. This practical constraint should be factored into pricing decisions, especially for companies that need to move quickly.
Creating Your Balanced Approach
The speaker concludes with practical advice for teams evaluating their pricing metrics:
"Make candidate lists if you are in the process of figuring out your pricing metric and then check across all of this and take a call of what you think works. Sometimes people just think about the customer sometimes just people just think about themselves so make a balanced decision of what aligns the value."
By considering all seven factors—customer risk perception, mental anchors, value alignment, consumption patterns, cost structure, competitive action, and implementation constraints—SaaS companies can develop pricing models that simultaneously satisfy customer expectations and support business objectives.
The right pricing metric isn't universal but depends on your specific customers, product, market position, and internal capabilities. Taking a holistic approach to this decision can dramatically improve both customer satisfaction and revenue potential.