Pricing Models: How to Choose the Right Model for Your Business

Why Your Pricing Model Is More Important Than Your Pricing

Most founders obsess over whether to charge $99 or $149. That's backwards. Your pricing model-how you structure the exchange of value for money-matters way more than the number itself.

I've launched and sold 5+ SaaS companies. The ones that scaled fastest weren't always the best products. They had the right pricing model for their market. Get this wrong and you'll fight for every customer. Get it right and your revenue compounds.

The difference between a usage-based model and a flat subscription can mean 3-5x different customer lifetime values. Same product, same market, completely different economics.

The 8 Pricing Models That Actually Matter

There are dozens of pricing models if you want to get academic about it. But in practice, almost every successful B2B company uses one of these eight. I've personally used all of them.

1. Flat-Rate Subscription

One price, unlimited usage. The simplest model to understand and sell. Customers know exactly what they're paying each month.

I use this for ScraperCity's B2B database-unlimited leads for one flat rate. No metering, no overage fees, no surprises. It works because customers want predictability when building lead lists, and I want recurring revenue without usage-based churn triggers.

The downside? You leave money on the table with power users. But you also reduce friction and increase retention because customers never worry about hitting limits.

Best for: Products where usage doesn't correlate with value, or where metering would create anxiety that hurts adoption.

2. Tiered Pricing

Multiple packages at different price points. Good, Better, Best. This is what most SaaS companies default to, and for good reason-it segments your market automatically.

The key is making sure each tier serves a genuinely different customer segment, not just arbitrary feature gates. When I see a tier structure that gates basic functionality behind higher tiers, I know the founder is optimizing for extraction instead of value.

Your tiers should be based on capacity (users, contacts, volume) or use case (solo vs. team vs. enterprise), not on withholding features that everyone needs.

Best for: Markets with clear customer segments that have different budgets and needs. Also effective when you need to establish a pricing ladder that grows with customer success.

3. Usage-Based Pricing

Customers pay for what they use. Credits, API calls, emails sent, minutes consumed. This model aligns your revenue directly with customer value-when they win, you win.

I've seen usage-based pricing work incredibly well for infrastructure products where consumption scales with customer growth. Tools like Smartlead charge based on email volume sent, which makes sense because if you're sending more emails, you're probably closing more deals.

The data backs this up. Companies using usage-based pricing average about 10 percentage points higher in net dollar retention than subscription-only companies. The best usage-based companies can grow nearly twice as fast as pure subscription businesses because expansion revenue is built into the model.

The danger is unpredictable bills. If customers can't forecast their costs, they'll either use your product less or churn to a competitor with flat pricing. You need transparent usage tracking and alerts before customers hit expensive thresholds.

I've watched this play out in real-time. One infrastructure client implemented usage-based pricing without proper spend alerts. Their best customers started optimizing consumption instead of expanding usage because they got hit with surprise bills. Revenue growth stalled until they added consumption dashboards and proactive notifications.

Best for: Infrastructure, APIs, and products where value scales linearly with usage. Works well in markets where customers are sophisticated enough to manage consumption.

4. Per-User Pricing

Charge per seat. Simple, predictable, and scales with team size. This is the default for collaboration tools and CRMs.

The math is straightforward: more users = more value to the organization = higher willingness to pay. Close CRM uses this model effectively because sales teams naturally grow as companies scale.

The problem is it penalizes companies for adding users, which can slow adoption. I've watched teams share logins or limit rollout because per-seat costs add up fast. Some companies solve this with guest users or view-only seats, but then you're back to complex tiering.

Best for: Collaboration tools, CRMs, and products where each user gets independent value. Less effective if you need viral adoption or if usage is concentrated among a few power users.

5. Freemium

Free tier with paid upgrades. This isn't really a pricing model-it's an acquisition model combined with one of the other structures. But it's common enough to address separately.

Freemium works when your free users either convert at high enough rates or create value for paid users through network effects. It fails when free users consume resources without path to monetization.

I've tested freemium exactly once and killed it within six months. The conversion rate was 2%, and free users generated support costs that exceeded their conversion value. Your math might be different, especially if you have genuine network effects or near-zero marginal costs.

Best for: Products with network effects, viral mechanics, or extremely low marginal costs. Not recommended for service-like products or where support costs scale with users.

6. Performance-Based Pricing

You get paid when customers get results. Revenue share, cost-per-acquisition, percentage of sales generated. This is the ultimate risk-reversal.

I use this model for my coaching program-you succeed, I succeed. It works because customers trust you're incentivized for their outcomes, not just their payments.

The operational complexity is high. You need systems to track results, attribute value, and reconcile payments. It only works if you can reliably deliver measurable outcomes and customers trust your tracking.

Best for: Agencies, coaching, lead generation, advertising-anything where results are measurable and you're confident in your ability to deliver them consistently.

7. Value-Based Pricing

Price based on the value delivered, not your costs. If your product saves a company $500K annually, you charge $100K, not $5K just because that covers your costs.

This isn't a structure like the others-it's a philosophy that informs how you set prices within any model. But it's worth calling out because most founders underprice by 3-10x.

I learned this the hard way. My first SaaS was priced at $49/month because that felt reasonable. Customers were using it to close deals worth $50K+. I should have been charging $500+ monthly. By the time I figured this out, I'd trained the market to expect cheap pricing.

Best for: Products that deliver quantifiable ROI, especially in B2B where buyers can justify spend based on return. Requires strong sales conversations to establish value before discussing price.

8. Hybrid Models

Combine multiple approaches. Base subscription plus usage fees. Freemium with per-user paid tiers. Flat rate up to a limit, then usage-based. This is where most sophisticated companies end up.

Hybrid models let you capture value from different customer behaviors. The trade-off is complexity-both for you and customers. Make sure the added revenue justifies the operational overhead.

For example, you might offer tiered packages based on team size, but add usage fees for premium features like phone lookups or email verification. This gives predictability with upside.

The data shows hybrid models are becoming the norm. Among SaaS companies monetizing AI features, 25% use pure usage-based pricing while 22% use hybrid strategies. About 46% of SaaS companies now incorporate usage-based pricing in some form, often combined with subscription components.

Best for: Mature products with diverse customer segments and multiple value drivers. Not recommended for early-stage companies still figuring out product-market fit.

How to Choose Your Pricing Model (The Framework I Use)

Stop asking what your competitors charge. That's useful data, but it's not a strategy. Instead, answer these four questions:

1. How do customers measure value? If they care about outcomes (meetings booked, revenue generated), consider performance-based pricing. If they care about capacity (team size, contact limits), use tiered or per-user models. If they care about predictability, go flat-rate.

When I'm helping founders work through this, this is always the first question. The answer tells you 80% of what you need to know about pricing structure.

2. What drives your costs? If your costs scale with usage (API calls, data storage, compute), you need to capture that through usage-based pricing or clear tier limits. If your costs are mostly fixed, flat-rate lets you maximize profit from heavy users.

3. How sophisticated are your buyers? Enterprise buyers can handle complex hybrid models with overages and add-ons. SMB buyers want simple, predictable pricing. Don't make a dental practice decode your consumption-based pricing calculator.

4. What behavior do you want to encourage? Per-user pricing discourages adding seats. Usage-based pricing makes people careful about consumption. Flat-rate encourages maximum adoption. Your pricing model shapes how customers use your product.

The AI Pricing Revolution Happening Right Now

If you're pricing any product with AI features, you need to understand what's happening in the market. The shift is massive and it's affecting pricing across the board.

Credit-based pricing has exploded. Out of 500 companies tracked in industry indexes, 79 now offer a credit model, up from 35 at the end of the previous year-that's 126% growth in one year. Major players like Figma, HubSpot, and Salesforce have all added credit-based pricing.

Here's why: AI features have variable, unpredictable costs. Credits give customers the predictability of a license while giving vendors a usage component to protect margins. They sit between charging for access and charging for outcomes.

But here's the problem-customers are getting tired of complexity. The pendulum swung toward credits and usage-based models, but it's already swinging back toward simplicity and predictability. The more credit models flood the marketplace, the more customers want to return to straightforward pricing.

Some companies are bundling AI into existing plans with price increases. Others are using credit limits within subscription tiers. I'm watching this closely because the companies that nail the simplicity-while-capturing-value balance will dominate.

If you're adding AI features, don't just copy what everyone else is doing. Test both bundled pricing and credit-based approaches with real customers before committing to one.

The Psychology Behind Pricing That Converts

Your pricing model matters, but so does how you present it. Small changes in pricing psychology can increase conversion rates by 5-24% without changing the actual price.

Charm pricing works. Prices ending in .99 convert an average of 24% better than round numbers. Your brain processes $9.99 as significantly cheaper than $10, even though it's a penny difference. I use this on entry-tier products but avoid it on premium offerings where round numbers signal quality.

Anchoring is powerful. When customers see a higher price first, subsequent lower prices appear more attractive-sometimes increasing conversions by up to 35%. This is why good-better-best pricing works. The enterprise tier makes the professional tier look reasonable.

I structure my pricing pages with the highest tier on the left specifically to create this anchor effect. It's a small change that consistently improves conversion rates across different products I've tested.

Value-based language matters. Pricing communication that emphasizes value over cost can increase conversion rates by up to 27%. Instead of listing features, explain what problems each tier solves. Instead of "10,000 contacts," say "reach your entire target market."

Price presentation affects perception. Smaller price text can reduce price sensitivity. Removing dollar signs makes prices feel less "expensive." I've tested both extensively-the effects are real but subtle. Don't overthink this until you've got the model and structure right.

Common Mistakes That Kill Revenue

I've made all of these mistakes myself, some multiple times.

Copying competitors blindly. Your competitor might have different costs, customer segments, or strategic priorities. I've seen founders adopt usage-based pricing because competitors use it, then struggle with churn because their product didn't justify the unpredictable costs.

Underpricing to win customers. Every dollar you leave on the table is gone forever. You can't easily raise prices on existing customers, and you've trained your market to expect low prices. If you're not losing 20-30% of prospects to price objections, you're probably too cheap.

I learned this by watching conversion rates. When I raised prices 40% on a SaaS product, conversion rate only dropped 8%. Net revenue went up 28%. I'd been leaving money on the table for years.

Creating too many tiers. More than 4-5 tiers creates decision paralysis. Customers spend time comparing options instead of buying. I've tested this extensively-three tiers usually outperform five, even when the five-tier structure seems more sophisticated.

Gating essential features. Your lowest tier should deliver complete value for its use case. If customers hit arbitrary feature limits that force upgrades before they've gotten value, they'll churn instead of upgrading. Save higher tiers for scale and advanced use cases, not basic functionality.

Ignoring payment friction. Every click, form field, and approval step costs you conversions. Your pricing model should minimize friction for your target segment. If you're selling to enterprises, they can handle complexity. If you're selling to solo founders, they need one-click purchase.

Not testing psychological elements. A/B test your price endings, tier names, and value propositions. Small changes compound. I've seen a simple change from "Professional" to "Growth" on a tier name increase conversions by 11% because it better matched buyer psychology.

Testing and Iterating Your Model

Your first pricing model won't be perfect. Mine never are. But you can systematically improve it.

Track expansion revenue separately. How many customers upgrade tiers? How quickly? If expansion is slow, your tiers might not align with customer growth. If it's too fast, you might be leaving money on the table with underpriced entry tiers.

I look at time-to-upgrade as a key metric. If most customers upgrade within 30 days, the entry tier is probably too limited. If very few upgrade within 6 months, the next tier might be overpriced or poorly positioned.

Monitor usage patterns. Are customers hitting limits? Are they using 10% of capacity or 90%? This tells you whether your tiers are sized correctly and whether flat-rate vs. usage-based makes more sense.

For ScraperCity's Maps scraper, I initially capped exports at 1,000 businesses per month on the base tier. Usage data showed 60% of customers hit that limit in week one. I was creating artificial friction. Raising it to 5,000 reduced early churn by 23%.

Survey churned customers. Not just about features-specifically about pricing structure. I've discovered major pricing model problems from churn surveys that I'd never have identified from usage data alone.

One survey revealed that 40% of churned customers left because they couldn't predict their monthly costs on our usage-based model. That led to a hybrid model with a base subscription plus usage fees, which reduced churn by 18%.

Test pricing with new customers. You can A/B test pricing models with new customer cohorts before rolling out changes to existing customers. I've done this multiple times to validate major pricing changes before committing.

When testing, make sure you have statistical significance. You need at least 100 conversions per variant, ideally more. Don't make decisions based on 20 purchases-the noise will mislead you.

Dynamic Pricing: When and How to Use It

Dynamic pricing adjusts prices automatically based on market conditions, demand, inventory, or other factors. It's powerful but complex.

Most B2B SaaS companies shouldn't use dynamic pricing. Your customers need predictability. But there are exceptions where it makes sense.

Event-based pricing works well. If you sell to event planners or seasonal businesses, prices can adjust based on calendar events and demand patterns. I've seen this work effectively for tools that serve industries with clear seasonal peaks.

Inventory-based pricing works for marketplace businesses. If you're brokering finite resources (hotel rooms, consulting hours, event tickets), dynamic pricing based on availability makes sense.

Competitive pricing works in commoditized markets. If you're selling products where competitors change prices frequently and customers compare prices obsessively, automated competitive pricing can protect margin and maintain market position.

If you're considering dynamic pricing, invest in the right tools. Manual price updates via spreadsheets don't work at scale. You need software that integrates with your stack and updates prices in real-time based on rules you define.

Cost-Based vs. Competitor-Based vs. Value-Based

These aren't pricing models-they're pricing strategies that inform how you set prices within your chosen model. Understanding the difference matters.

Cost-based pricing starts with your costs and adds a markup. Simple but limiting. Your SaaS costs almost nothing to serve additional customers, so cost-based pricing leaves massive money on the table. I only use this as a floor-never pay below costs-but never as a ceiling.

Competitor-based pricing sets prices relative to competitors. Useful for context but dangerous as a primary strategy. Your competitors might be wrong about their pricing. They might have different costs or strategic goals. I use competitor data as one input, not the deciding factor.

Value-based pricing sets prices based on value delivered to customers. This is the right approach for most B2B products. If your software saves customers $100K annually, you can charge $30K and still deliver 3x ROI. The ceiling becomes their alternative cost, not your internal costs.

In practice, I use all three as inputs. Costs set my floor. Competitors provide market context. Value sets my ceiling. Then I price somewhere between competitors and value ceiling based on how differentiated my product is.

Pricing Models by Business Type

Different businesses need different approaches. Here's what I've seen work across the companies I've built and advised.

For SaaS companies: Start with tiered subscriptions. It's the easiest to sell and forecast. Add usage-based components later once you understand consumption patterns and can justify the complexity.

For agencies: Retainer pricing (flat monthly fee) works better than hourly for both you and clients. Clients get predictability, you get recurring revenue. Add performance bonuses on top for alignment. I cover this extensively in the 7-Figure Agency Blueprint.

For consulting: Value-based project fees beat hourly rates. If you help a client generate $1M in new revenue, charge $100K-$200K for the project, not $10K based on your hours. The discovery call framework helps you uncover this value before pricing.

For productized services: Flat-rate subscriptions with clear scope. Customers want to know exactly what they get for their monthly fee. Don't nickel-and-dime with usage fees unless scale genuinely changes your costs.

For marketplaces: Percentage of transaction value works because it aligns your revenue with customer success. Start with percentage-based, consider adding subscription tiers once you have data on transaction patterns.

For lead generation: Either pay-per-lead or retainer with delivery commitments. I've used both. Pay-per-lead is easier to sell but harder to scale profitably. Retainer with volume commitments gives you revenue predictability while maintaining customer trust.

The Role of Contract Structure

Your pricing model and contract terms work together. Getting both right matters.

Annual contracts reduce churn but increase sales friction. I use annual contracts for products with longer sales cycles and implementation periods. The discount for annual payment (usually 15-20%) is worth it for the cash flow and reduced churn.

Monthly contracts make trials easier and reduce buyer hesitation. I default to monthly for products with quick time-to-value and low implementation friction.

Multi-year contracts work for enterprise deals where switching costs are high. Don't push for multi-year contracts in SMB markets-it triggers buyer resistance and increases legal review cycles.

The agency contract template includes payment terms and structures for different pricing models-particularly useful if you're doing performance-based or hybrid pricing where payment terms get complex.

Pricing for Different Market Segments

Your pricing model might need to differ by segment. Here's what I've learned serving both SMB and enterprise markets.

SMB customers want simplicity. One or two clear tiers, monthly billing, credit card payment, no contracts. They'll pay premium prices for products that solve real problems, but they won't navigate complex pricing structures.

For SMB, I use flat-rate or simple tiered subscriptions. No usage-based complexity. No custom pricing. The self-service buying experience matters more than pricing optimization.

Mid-market customers want flexibility. They'll handle moderate complexity if it gives them control. Tiered pricing with some usage components works well. Annual contracts with discounts convert better than monthly.

Enterprise customers want customization. Custom pricing, volume discounts, multi-year contracts, complex usage-based components-they have procurement teams to handle it. This is where hybrid models with sophisticated usage tracking make sense.

Don't use the same pricing model across all segments. Segment-specific pricing pages and packages improve conversion and reduce friction.

Preparing for Pricing Changes

You will need to change your pricing. Market conditions change, costs change, your product evolves. How you handle pricing changes matters as much as the changes themselves.

Grandfather existing customers. Pricing changes without protection for legacy customers trigger 10-15% churn spikes. Give existing customers 12-24 months at their current price, or offer permanent grandfathering for early adopters.

I've done both. Permanent grandfathering rewards early customers and reduces backlash. Time-limited grandfathering (12-24 months) gives you the benefit of unified pricing eventually while still respecting existing customers.

Pair price increases with value additions. When raising prices, launch new features simultaneously. Companies that pair price increases with exclusive new features achieve 26% higher gross retention rates than those that just raise prices.

Communicate early and clearly. Give customers 60-90 days notice before pricing changes. Explain why prices are changing. Be transparent about value delivered. I've found that clear communication reduces churn more than any specific pricing protection strategy.

Test new pricing on new customers first. Don't roll out major pricing changes to your entire base at once. Test with new customers for 90 days, validate the economics work, then roll out to existing customers with proper notice and grandfathering.

Resources for Implementation

Once you've chosen your pricing model, execution matters. A few resources that have been useful for me and the founders I work with:

If you're building lead lists to test your pricing with outbound sales, the email finder tool makes it simple to find contact info for prospects in your target segments without juggling multiple data sources.

For agencies specifically, I put together the 7-Figure Agency Blueprint that includes pricing strategy templates I've used across multiple companies. It covers how to structure your own agency pricing based on your delivery model.

The agency contract template includes payment terms and structures for different pricing models-particularly useful if you're doing performance-based or hybrid pricing where payment terms get complex.

What Actually Matters

Your pricing model should do three things: capture the value you create, align incentives between you and customers, and stay simple enough that customers can make decisions quickly.

Everything else is optimization. Start with a model that makes sense for how customers measure value, test it with real buyers, and iterate based on actual behavior-not theoretical concerns.

I've watched founders spend months building perfect pricing calculators for models their customers didn't want. I've also watched founders 3x revenue in a quarter by simplifying from five tiers to three. Execution beats theory every time.

The market is shifting toward more complex hybrid models as AI features become standard. But complexity for complexity's sake loses deals. The winners will be companies that find the right balance between capturing value and maintaining simplicity.

Pick a model that matches how your customers think about value. Ship it fast. Learn from real purchase behavior. Iterate monthly, not yearly. Your first pricing model won't be your last, and that's exactly how it should be.

The goal isn't perfect pricing-it's pricing that's good enough to close deals today while giving you data to improve tomorrow. Stop overthinking and start testing.