Introduction
When a technology business approaches us about pricing, the presenting symptom is rarely the root cause. A sales leader might say “we need to reduce discounting.” A product executive might observe “customers aren’t upgrading.” A CFO might note “our middle tier is underperforming.” All of these statements can be true simultaneously—and all of them can be symptoms of a deeper structural problem in how the commercial model is designed.
This case study documents an engagement with a technology business operating in a mature, competitive market. Drawing on customer interviews, usage analytics, conjoint analysis, and competitive benchmarking, we diagnosed a commercial architecture problem: the company had built a strong product with genuine technical advantages over established competitors, yet their commercial model wasn’t capturing the value they were creating. Their middle tier—the “Better” option in a classic Good-Better-Best structure—was chronically underperforming, capturing roughly a quarter of customers and less than a third of total revenue. Year-over-year growth in that tier had essentially stagnated, while their premium tier was growing several times faster.
The gap between product strength and commercial performance is one of the most common—and most expensive—problems we see in B2B software. This engagement illustrates how rigorous value quantification, competitor-anchored positioning, and behaviorally-informed packaging design can unlock revenue that’s already sitting in the customer base.
The Challenge
The client’s situation was textbook “good product, leaky commercial model.” They had built something genuinely differentiated: faster deployment times than entrenched competitors, a simpler licensing structure, and embedded capabilities that rivals charged extra for. Customer satisfaction scores were strong. Technical evaluations went well. Yet the commercial outcomes didn’t match.
Three interconnected problems emerged during our diagnostic phase.
First, the middle tier lacked clear differentiation. Feature overlap between the entry-level and mid-tier offerings created confusion. Customers couldn’t articulate why they should pay more, because the value gap wasn’t visible in the packaging. Usage analytics from the client’s substantial daily user base confirmed that the features most capable of driving willingness-to-pay were being under-leveraged as tier differentiators. AI adoption was minimal among entry-level customers but widespread among premium customers. That’s not a feature problem; it’s a packaging problem.
Second, price deltas weren’t doing their job. The percentage gap between tiers didn’t create sufficient psychological distance to justify the upgrade decision. Customers perceived the middle tier as “slightly better” rather than “meaningfully different.” Net Promoter Scores told the story: a significant gap between mid-tier and premium customers indicated that perceived value wasn’t scaling with price.
Third, migration customers were converting at lower rates than the overall base. Customers moving from competitor platforms—exactly the segment where the client had the strongest competitive advantages—were converting from entry-level to mid-tier at rates well below the overall average. The commercial model wasn’t capitalising on the switching moment.
The underlying issue wasn’t the product. It was that the commercial architecture had been designed around internal logic (what features exist) rather than customer value logic (what outcomes customers pay for).
Our Approach
We deployed a Total Economic Value (TEV) framework to rebuild the commercial model from first principles. TEV quantifies the complete value a solution delivers relative to the customer’s next best alternative—not just the list price, but the total cost of ownership and the differentiation value on top of it.
Phase 1: Competitive Value Anchoring
We began by establishing rigorous reference values against the two primary competitor categories: entrenched enterprise incumbents and emerging alternatives. For each, we constructed detailed multi-year total cost of ownership models incorporating licensing, implementation, support, and integration costs.
The analysis revealed that the client delivered substantial TCO savings versus enterprise incumbents driven by simpler licensing, faster deployment, and embedded capabilities that competitors charged separately for. Against emerging alternatives, the client commanded a justified premium based on enterprise-grade functionality, offline capabilities, and native AI integration.
This wasn’t positioning spin—it was documented, quantifiable advantage. But the commercial model wasn’t communicating it.
Phase 2: Willingness-to-Pay Analysis and Anchor Feature Identification
We conducted conjoint analysis and MaxDiff scaling across the customer base to identify which capabilities drove the highest willingness-to-pay uplift.
These features were present in the product but poorly allocated across tiers. The mid-tier didn’t have exclusive claim to the capabilities that customers valued most. We recommended reserving these anchor features as mid-tier and premium-tier exclusives, creating genuine upgrade incentives rather than marginal feature additions.
Phase 3: Price Delta Restructuring
We redesigned the price architecture to create meaningful psychological distance between tiers. The optimised structure established significant price gaps between entry and mid-tier (capturing only a portion of the quantified differentiation value, leaving meaningful customer surplus), and a further gap between mid-tier and premium—aligned with industry benchmarks for comparable software categories.
The principle: price deltas should reflect value gaps, not cost-plus margins. When customers can see and feel the difference between tiers, upgrade friction decreases.
Phase 4: Migration and Conversion Optimisation
For competitor migration customers—the segment with the lowest conversion rates despite the strongest competitive positioning—we designed a structured migration programme. This included extended trial periods with full access to anchor features, first-year incentives, migration toolkits, and TCO calculators demonstrating the substantial savings versus incumbents.
The insight was behavioural: migration customers need to experience the value gap, not just hear about it. Restricting AI access during trials was suppressing conversion. When prospects had full access to differentiating capabilities, trial abandonment rates drop meaningfully, and conversion pathways strengthen.
Phase 5: Discount Governance Framework
Finally, we implemented structured discount governance to protect the value-based pricing architecture. The framework established clear discount categories with eligibility criteria and approval thresholds, a maximum combined discount ceiling, stackable volume and contract discounts up to defined limits, and executive approval requirements for competitive pricing scenarios.
The goal wasn’t to eliminate discounting—it was to make discounting intentional rather than reflexive.
The Results
The engagement delivered a complete commercial model redesign with implementation beginning immediately. While full revenue impact will compound over subsequent years, the projected outcomes based on the restructured model are significant.
Middle-tier adoption target: meaningful increase within 24 months. The clearer value differentiation and anchor feature positioning creates a genuine upgrade pathway that didn’t exist before.
Conversion rate targets: substantial improvement at 12 months, with continued gains at 24 months. Standardised trials with full AI access address the primary friction point in the conversion funnel.
Migration customer conversion: targeting parity with overall base. The structured migration programme and TCO demonstration tools give sales teams the ammunition to close customers who are already predisposed to switch.
Margin protection: healthy gross margins maintained across all tiers even at maximum discount thresholds, consistent with or above industry averages.
Beyond the quantitative targets, the engagement delivered strategic clarity. The commercial model now reflects the product’s actual value proposition. Sales teams have defensible price points anchored in documented TCO advantages. Marketing can articulate tier differences in terms of customer outcomes, not feature lists. And the executive team has a governance framework that prevents margin erosion while preserving competitive flexibility.
Key Takeaways
1. Packaging is a strategic decision, not an administrative one. Most B2B software companies design packages around internal product organisation—what features exist, what the engineering team built. Value-based packaging starts with customer outcomes and works backward. The question isn’t “what features go in each tier?” It’s “what value gap justifies each upgrade?”
2. Price deltas should create psychological distance. A modest price increase for marginally more features doesn’t motivate upgrade behaviour. Customers need to perceive tiers as meaningfully different categories, not incremental improvements. The price gaps we recommended weren’t arbitrary—they were calibrated to research on willingness-to-pay and competitive benchmarks.
3. Anchor features should be reserved, not distributed. High-value capabilities lose their commercial power when they’re available across all tiers. Identifying which features drive the highest willingness-to-pay uplift—and gating them appropriately—is one of the highest-leverage pricing decisions a software company can make.
4. Migration moments are conversion opportunities. Customers switching from competitors have already overcome the highest barrier: the decision to change. If your commercial model doesn’t capitalise on that moment with structured programmes, competitive proof points, and full access to differentiating capabilities, you’re leaving revenue on the table.
5. Discount governance enables value pricing. Value-based pricing without discount governance is an aspiration, not a strategy. Clear rules about what discounts are permissible, under what conditions, with what approvals, allow sales teams to hold price confidently while preserving flexibility for genuinely strategic situations.
The gap between product value and revenue capture is one of the most expensive problems in B2B software—and one of the most fixable. If your middle tier is underperforming, your migration customers aren’t converting, or your sales team reaches for discounts before they reach for value arguments, the commercial model is likely the constraint.
We help technology businesses restructure their commercial architecture to capture the value they’re already creating. If this case study resonates with challenges you’re facing, a 30-minute diagnostic conversation can identify whether a similar approach would unlock trapped revenue in your business.
Reach out to us via email: info@quantidegrowth.com
References
• QGP Total Economic Value (TEV) Framework
• QGP Good-Better-Best Packaging Optimisation Methodology
• Conjoint Analysis and MaxDiff Willingness-to-Pay Research
• Customer Feature Usage Analytics
