In the video "SaaS Pricing Strategy: Data-Driven Decisions That Work" by Monetizely, a pricing expert walks through the essential data inputs required to make informed SaaS pricing decisions. The presenter outlines a methodical approach to gathering and analyzing different types of data before implementing pricing changes.
The Four Key Data Sources for SaaS Pricing Decisions
Pricing is one of the most strategic decisions a SaaS company makes, directly impacting both acquisition and revenue. But how do you ensure your pricing strategy is based on facts rather than gut feelings? According to the expert from Monetizely, you need four specific types of data inputs.
1. Competitive Comparison: Your Starting Point
Most pricing discussions begin with looking at what others are doing. As the presenter explains:
"Starting from the left is competitive comparison. That's usually where some hypothesis starts because we see that our competition or somebody else on the market adopts a certain packaging, certain price points, somebody launched a lowcost price point or a bundle."
Competitive analysis provides a benchmark and often triggers the initial hypothesis for a pricing change. This makes sense – pricing never happens in a vacuum, and customers will inevitably compare your offering against alternatives.
2. Transactional and Usage Data: What Your Current Customers Tell You
The next critical input comes from your existing customer base:
"Then the next step would be getting deeper into the data that we already have. So that's what I mean the transactional data on what the customers are currently purchasing. Do they choose the monthly plan or the annual plan? Do they go to the lowest lower cost options or they buy the more premium? And then feature level usage."
This data helps you understand actual purchase patterns and feature adoption. Are customers gravitating toward specific tiers? Which features see the highest adoption? This information can reveal opportunities for better packaging or pricing alignment.
3. External Research: The Critical Perspective You're Missing
The presenter makes a crucial distinction that many SaaS companies overlook:
"I really want to kind of highlight here is that the behavior of current customers and people who are already in the system is not necessarily representative of the behavior of prospects who are not yet familiar with the product."
This insight is fundamental to effective pricing. Current customer behavior doesn't predict prospect behavior because:
- Existing customers made purchase decisions based on different perceptions than what they ended up actually using
- Prospects have different knowledge levels and needs than current customers
The presenter emphasizes the need for external research:
"So it's important to understand that the data that we have on customers is not the same as the data on prospects. And that what the next step the green element of kind of qualitative and quantitative research is about is reaching out to source some data from the outside from what we do not see in our transactional or product usage databases."
This external perspective combines both qualitative research (to be covered by Ajit, another expert mentioned) and quantitative research that helps validate hypotheses with data from outside your current customer base.
4. Real-World Testing: Validating Your Pricing Strategy
The final step is to test your new pricing in real market conditions:
"That's when the last step would be testing it on kind of a living organism. So either we put it online on an AB test fashion and we see what the response is or we do some kind of a staged launch where we make it available only to a subset of sales reps and see what the reaction is and how it behaves in a real environment."
This approach allows you to gather actual market feedback before a full rollout. The two recommended methods are:
- A/B testing on your website
- A staged launch with a subset of your sales team
Implementing a Data-Driven Pricing Process
What makes this approach powerful is its comprehensive nature. Rather than relying solely on competitor benchmarking (which most companies do), this framework incorporates multiple data sources that provide a 360-degree view of pricing opportunities.
The process acknowledges that pricing is both an art and a science. While data informs decisions, testing validates assumptions before full implementation.
Beyond Copying Competitors
Many SaaS companies fall into the trap of simply mirroring competitor pricing. This framework suggests starting with competitive analysis but then diving much deeper through internal data, external research, and real-world testing.
This methodical approach reduces risk while maximizing the chance of finding optimal price points and packaging that resonate with your target market. By understanding both current customer behavior and prospect perceptions, you can design pricing that works for acquisition and retention.
For SaaS executives looking to optimize their pricing strategy, following this data-driven process can lead to more confident decisions and better market outcomes. The key is recognizing that multiple data inputs are needed – no single source tells the complete story.