A Smarter Way to B2B Enterprise SaaS Pricing Research: Monetizely Insights

SaaS Pricing

A More Effective Approach To B2B Enterprise SaaS Pricing Research

Jan 31, 2025

traditional SaaS pricing methods vs. Monetizely's in-depth interview-driven approach

Today, there are a host of pricing consulting firms doing comprehensive survey based approaches for a lot of B2B SaaS products. The techniques these firms use are very much the traditional analytics tools that have worked in the past such as MaxDiff, Conjoint and Van Westendorp surveys.

But many of the traditional approaches for pricing research breakdown in complex enterprise settings. At Monetizely, we have now served multiple clients who invested in $100k+ research studies (conjoint) with some very well known pricing research vendors and come out frustrated from the experience, feeling like they got further confused and were not left with a clear/workable pricing and packaging lineup.

The thing is that pricing and packaging for B2B enterprise SaaS products is unique. Unlike consumer products or straightforward SaaS tools, enterprise solutions are highly complex, with domain-specific features, and often require detailed explanations in a survey based method before users can understand, appreciate and then accurately assess value.

Let’s understand the limitations of these (standard to B2C) approaches in the B2B setting, and what we advocate for instead.

Feature Names Alone Don’t Mean Much

Traditional pricing research methods like Conjoint Analysis and MaxDiff work well when respondents can make trade-offs between clear and universally understood attributes. For example, a consumer might easily choose between a smartphone with a better camera or a longer battery life. However, enterprise SaaS buyers face a different challenge:

Features often require extensive explanation. “AI-Driven Sentiment Analysis” or “Predictive Analytics” are just words on a slide unless properly contextualized for the respondent.
The value of features depends on the company’s size, industry, and workflow. What’s critical for one firm might be irrelevant for another.
Many decisions aren’t made at an individual level. Enterprise purchases often involve multiple stakeholders across finance, IT, and operations.

Take Medallia, a leading B2B enterprise SaaS platform for experience management. The company offers a range of powerful capabilities, such as:

AI-Enabled Speech and Text Analytics – Extracts insights from customer conversations.
Journey Orchestration – Maps and analyzes customer journeys across touchpoints.
Role-Based Dashboards – Provides customized analytics for different teams.
Real-Time Alerts & Closed-Loop Feedback – Automates follow-ups for service teams.

If you simply listed these features on a survey and asked prospective customers (who are not previously exposed to the category) to rank them, you'd get highly unreliable data.

Without understanding how these features work, when they are needed, or how they integrate into an enterprise’s workflow, respondents can’t make informed trade-offs.

The Complexity of B2B Buying: It’s Not Just About Price

Another major issue with relying solely on surveys is that B2B buying approaches are highly complex. Pricing research isn’t just about finding an ideal price point—it’s about understanding why buyers assign value to a product and how they make purchasing decisions.

Who is the real buyer? Many SaaS products are used by one group (e.g., customer support teams) but purchased by a senior leader or a committee of leaders. If you only test pricing with users, you might be speaking to the wrong persona.
What drives the buying process? In enterprise sales, purchases often involve multiple layers—budget approvals, compliance checks, and proof-of-concept trials. Understanding pricing without understanding the sales motion and how budgets will be allocated leads to data that is either biased or not actionable.
How does pricing affect the go-to-market strategy? A product priced at $50,000/year might be a “low-touch” SaaS purchase for some companies, but for others, it may require a lengthy enterprise sales cycle. The qualitative "why" behind pricing decisions helps determine whether the sales model should be product-led, inbound-driven, or heavily reliant on account-based selling.

For example, Medallia's customers often include marketing, customer experience, and operations teams—all of whom may value different parts of the platform. A CFO evaluating Medallia may care most about cost efficiency and ROI (a more competitive set centric approach), while a CX leader may prioritize NPS (Net Promoter Score). Understanding why each persona values the platform is just as critical as knowing how much they’d pay for it.

Monetizely’s Solution: In-Person Research That Blends Methods

Because of this complexity, pricing and packaging research for enterprise SaaS must be conducted through in-depth, in-person interviews where packaging structures and feature sets can be fully explained. This approach enables respondents to engage with the offering in a way that reflects how real purchasing decisions are made.

Key Elements of Our Approach

Context-Driven Feature Evaluation
Respondents are first asked about their broader pain points—what problems they are solving and what obstacles they face. This forces a discussion around real business needs before jumping into pricing questions.

Iterative Package Selection
Participants are presented with different product tiers (e.g., Pro, Elite, Platinum, Enterprise) and asked to select the most suitable package.

They then react to pricing once it's revealed—allowing us to capture how price sensitivity shifts based on perceived value.

Van Westendorp Pricing Sensitivity Analysis - with Reasons
By asking structured pricing questions such as:
- "At what price would this be too expensive?"
- "At what price would it be too cheap?"

We can understand both the price tolerance and perceived value of each package.

A Medallia customer, for example, might say:

“For a full experience management suite with AI analytics, I’d spend $100,000 per year.”
“If it’s just feedback collection and reporting, I wouldn’t go beyond $30,000.”

Feature Prioritization Using MaxDiff Approach
Instead of assuming which features matter most, we directly ask:
- "What feature can you not live without?"
- "If we removed one feature, which would have the least impact?"

This is especially useful for platforms like Medallia, where different industries may weigh features differently. For instance, a hospitality brand may prioritize real-time guest feedback, while a B2B firm may care more about predictive analytics.

Why This Approach Works

By integrating qualitative insights with structured pricing methodologies, we bridge the gap between theoretical price modeling and real-world decision-making. Unlike survey-based approaches that assume too much knowledge on the respondent’s part, this method allows for:

Deeper insights into customer needs – We uncover pain points that directly inform packaging design.
More reliable price sensitivity analysis – Pricing data is grounded in real purchase behavior, not just hypothetical rankings.
Better-informed pricing decisions – Instead of relying on incomplete survey responses, we get a nuanced understanding of what drives purchasing decisions.
Stronger GTM strategy alignment – Understanding why a persona values certain features informs sales messaging and the overall sales process.

How Many Interviews Do You Need?

One common question in B2B pricing research is: How many interviews are enough to generate reliable insights?

Unlike survey-based methods that require hundreds of responses to achieve statistical significance, qualitative B2B pricing research requires far fewer data points to reach strong, directional conclusions.

Why ~20 Interviews Per Product Is a Strong Benchmark

B2B Markets Are Niche & Decision-Makers Are Highly Informed
- In enterprise SaaS, buyers are not random consumers—they are domain experts making considered decisions. A well-run interview provides rich insights into their pain points, priorities, and price sensitivity.
- When interviewing senior buyers (CFOs, CTOs, heads of procurement), you don’t need hundreds of responses—each interview provides a deep understanding of a real-world purchase process.
Patterns Emerge Quickly
- In most B2B pricing studies, after 12-15 interviews, clear themes start to appear. You begin hearing the same objections, value drivers, and pricing anchors repeatedly.
- By 20 interviews, you typically reach diminishing returns—where new interviews mostly confirm existing insights rather than introducing novel findings.

While ~20 interviews are sufficient for most B2B enterprise SaaS studies, more interviews may be required if:

You're testing pricing across very different industries (e.g., healthcare vs. financial services).
Your product is new to the market and lacks historical sales data.
You are testing many customer segments at the same time.

Insights from an In-Person Study

The inputs from the in-person research are aggregated and a results deck/summary is then created,

A well-structured pricing research results deck distills key insights into pricing strategy, packaging, buyer behavior, and sales motion. It typically answers questions like: Which pricing models resonate best? Who holds budget authority? How do customers perceive feature value? Findings often reveal whether buyers prefer flat-rate vs. usage-based pricing, subscription tiers vs. à la carte options, or simple vs. complex bundling structures.

Beyond just numbers, the results deck explains why customers assign value to different pricing models and how they make purchasing decisions. It identifies who the real buyer is, which stakeholders influence approval, and what pricing objections must be overcome in sales conversations. It also highlights pricing sensitivity ranges, showing where customers see high vs. low perceived value, helping refine price points accordingly.

Finally, the deck translates insights into actionable next steps—such as recommended pricing structures, persona-based sales strategies, and messaging adjustments to improve conversion.

Unlike survey-only research, this approach captures the full context of pricing decisions, helping companies build pricing strategies that align with real customer behavior.

For example, if Medallia were testing new AI-driven customer experience analytics, a 20-interview study might reveal:

Pricing for AI insights should be usage-based, not seat-based.
Financial services firms see higher ROI, justifying premium pricing.
The ideal package design for Financial Services (or other segments).
The range of Willingness To Pay per package.
CFOs hesitate at six-figure deals unless they see quantifiable efficiency gains.
The optimal sales motion requires a strong proof-of-concept phase.

Free: Copy Our Template

We freely offer a template that you can copy and use for your own research.

Slides are here: Pricing Feedback Deck + Reporting Sample.pptx

This includes detailed in-person research slides as well as examples of analysis/results slides.

When to Use Each Approach?

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Conclusion

Enterprise SaaS pricing isn’t just about numbers—it’s about perception, value, and fit. If you’re trying to price your SaaS product using only survey-based methodologies, you’re likely getting misleading data.

By taking an interview-driven approach that incorporates elements of Van Westendorp, MaxDiff, and Conjoint Analysis in a structured way, you can gain actionable insights that lead to smarter pricing and packaging decisions.