Start with willingness‑to‑pay interviews and historical win/loss analysis. Find the bands where customers hesitate—and why. Most teams set prices based on competitors or costs, not customer value. That's backwards. Start with what customers are actually willing to pay. Conduct willingness-to-pay interviews. Ask prospects: 'If this solution solved your problem completely, what would it be worth to you?' Don't ask what they'd pay—ask what it's worth. There's a difference. What they'd pay is constrained by budget. What it's worth reflects value. Use different price points in interviews. 'Would you pay $100? $500? $1,000? $5,000?' Find the bands where hesitation increases. That's where price sensitivity lives. But don't stop at interviews. Analyze historical win/loss data. When did deals close? When did they stall? What prices were accepted? What prices were rejected? Look for patterns. Maybe deals stall at $10,000. Maybe they close easily below $5,000. Maybe discount requests spike above certain thresholds. This data tells you where pricing friction exists. Combine interview insights with win/loss data, and you'll find the price bands that work and the ones that don't. You'll understand why customers hesitate. You'll know where to test. This is how you price based on value, not guesswork.

Test fences before price: limits, usage tiers, and feature gating. Good fences let high‑value users self‑select into higher plans. Most teams test price first. They raise prices and hope customers pay more. Sometimes it works, sometimes it doesn't. But there's a better way: test fences before price. Fences are the boundaries between plans: usage limits, feature gates, support tiers. Good fences let customers self-select into the right plan. High-volume users naturally choose higher plans. Power users naturally choose feature-rich plans. Companies that need support naturally choose support-heavy plans. Test different fence configurations. Maybe you limit API calls: 1,000/month on basic, 10,000/month on pro, unlimited on enterprise. Maybe you gate features: basic gets core features, pro gets advanced features, enterprise gets everything. Maybe you tier support: basic gets email, pro gets priority, enterprise gets dedicated. Test these fences first. See how customers respond. See which fences create natural segmentation. Then, once fences are working, test price. If customers are self-selecting correctly, price increases become easier. They're already choosing higher plans based on value. Price just reflects that value. But if fences don't work, price won't help. Customers won't pay more for plans they don't need. Test fences first, price second. That's how you build pricing that works.

Use anchoring and good/better/best to frame choices. The middle should be the hero; your 'best' sets the high anchor. Most teams present pricing as a list: Plan A, Plan B, Plan C. But how customers perceive price depends on how you frame it. Use anchoring: show the highest price first. This sets a high anchor. Everything else looks reasonable by comparison. If you show $1,000/month first, then $500/month looks cheap. If you show $500/month first, then $1,000/month looks expensive. The order matters. Use good/better/best framing: three options, with the middle as the hero. The 'good' option is the baseline—it solves the core problem. The 'better' option is the hero—it's what most customers should choose. The 'best' option sets the high anchor—it's for power users or enterprises. Position the middle option as the smart choice. 'Most customers choose Pro' or 'Recommended' or 'Best Value.' This creates social proof and guides decisions. But make sure the middle option actually is the best choice for most customers. Don't manipulate—optimize. The goal is to help customers choose the right plan, not trick them into paying more. Good anchoring and framing make pricing clearer, not more confusing. They help customers make better decisions. They increase average deal size without feeling pushy. Use them wisely.

Bundle outcomes, not features. Buyers pay for speed, certainty, and support, not toggles. Most pricing pages list features: 'Plan A includes X, Y, Z features. Plan B includes X, Y, Z, A, B features.' This is feature-focused pricing. It's what you're selling, not what buyers are buying. Instead, bundle outcomes. What outcomes do buyers want? Speed? Certainty? Support? Scale? Bundle around those. 'Starter: Get started quickly with core automation. Pro: Scale with confidence and priority support. Enterprise: Move fast with dedicated success management.' See the difference? Features are listed, but outcomes are emphasized. Buyers don't pay for features—they pay for what features enable. They pay for speed: 'Automate workflows in days, not months.' They pay for certainty: 'Guaranteed uptime and SLA.' They pay for support: 'Dedicated success manager.' They pay for scale: 'Unlimited workflows and users.' Frame pricing around outcomes, and buyers understand value. They see what they're getting, not just what you're selling. They can justify the investment. They can compare plans based on what matters to them. Feature lists are still important—they show what's included. But lead with outcomes. Bundle around value, not functionality. That's how you price based on what buyers actually care about.

Run geography or segment‑based tests to minimize risk. Track deal cycle, discount rate, expansion, and churn, not just ACV. Most teams test pricing by raising prices for everyone and hoping it works. That's risky. If it fails, you've damaged relationships and lost revenue. Instead, run controlled tests. Test pricing by geography: raise prices in one region, keep them the same in another. Test by segment: raise prices for new customers, keep them for existing. Test by product: raise prices for one product line, keep them for another. This minimizes risk. If the test fails, you've only affected a subset of customers. If it succeeds, you can roll it out more broadly. But don't just track average contract value (ACV). That's a lagging indicator. Track the full picture: deal cycle (does it take longer to close?), discount rate (are you discounting more?), expansion (are customers upgrading?), churn (are customers leaving?). These metrics tell you if pricing changes are working. If deal cycle increases but ACV stays the same, that's a problem. If discount rate spikes, that's a problem. If churn increases, that's a big problem. But if ACV increases and everything else stays stable, that's success. Track the full picture, not just one metric. Run controlled tests, not all-or-nothing changes. This is how you optimize pricing without breaking your business.

Document learnings in a pricing playbook and set a quarterly review. Pricing calcifies if you don't keep learning. Most teams set pricing once and forget about it. They assume it's right. They assume it will always work. But pricing is dynamic. Markets change. Competitors change. Customer needs change. Your product changes. Pricing should change too. Document your pricing decisions in a playbook. What did you test? What worked? What didn't? Why? What did you learn? This creates institutional knowledge. It prevents repeating mistakes. It enables faster decisions. But don't just document—review. Set a quarterly pricing review. Look at your metrics: deal cycle, discount rate, expansion, churn, win rate. Look at market changes: competitor pricing, customer feedback, market conditions. Look at product changes: new features, improved value, expanded use cases. Then decide: should pricing change? Should you test something? Should you adjust fences? Should you reposition plans? Pricing isn't set-and-forget. It's an ongoing optimization. But it's easy to let it calcify. It's easy to assume current pricing is fine. It's easy to avoid the hard conversations. Don't let that happen. Set a quarterly review. Make it a ritual. Keep pricing fresh. Keep learning. Keep optimizing. That's how you maximize revenue. That's how you stay competitive. That's how you price based on reality, not assumptions.