Model any pricing structure
Flat-fee, tiered, per-unit, hybrid, and pay-as-you-go add-ons on one engine.
Product and growth teams control pricing directly through configuration.
Cohort response can reveal where pricing headroom exists and what to test next. Chargebee brings that context into the pricing controls product and growth teams use to launch experiments, measure revenue impact, and keep improving each decision.
Flat-fee, tiered, per-unit, hybrid, and pay-as-you-go add-ons on one engine.
Create and change plans, bundles, and prices directly in the UI.
A/B test price points, packaging, and coupons against control groups.
Launch new pricing while existing subscribers stay on the terms they have.
Three roles share one pricing layer.
Configure price and packaging directly in the UI.
Test price points and offers against control groups, measured in revenue.
Move pricing logic out of the codebase and check entitlements by API.
Build any pricing model, launch it through configuration, experiment to lift revenue, and roll it out while protecting your base.
Your pricing should match the value you deliver.
Model plans and SKUs tied to features and quantity. Run a freemium tier, or charge metered components on consumption. Align price to the metric that matters: users, features, storage, bandwidth, or files.
Set flexible billing periods, from daily and weekly cycles to multi-year commitments. Combine subscription fees with pay-as-you-go add-ons and credits on a single subscriber account.
Pricing changes belong with your growth and product teams.
Create plans, bundles, and offers through the UI. Changes go live in minutes, ready for the next experiment.
Chargebee's entitlement engine separates what subscribers pay from what they access. You attach features to plans, set access rules, and update packaging as configuration. Your app checks feature IDs against Chargebee, freeing engineers to build product while your team owns pricing.
Cohort response reveals where pricing has room to move. Cohort response shows where the room to move is.
A/B test price points, packaging, coupons, and plan layouts inside a visual pricing table editor. Target new and returning visitors separately, and run control groups and holdouts to prove causal lift.
Build meaningful cohorts from subscription signals such as plan, tenure, usage, and payment history, then compare how each responds to price. Put the next test in market through the same pricing controls, measure the revenue impact, and use each result to inform the next decision.
New pricing and renewal pricing are two separate moments.
Change pricing for the customers you choose, when you choose. Existing subscribers stay on the terms they signed up for until you decide otherwise. You can move on price without unsettling the base you already have.
Renewal is the moment to revisit price. Tenure, current price, and renewal response provide context for where pricing may have room to move. Renewal Price Optimization gives your team the controls to test those changes across existing subscribers.
Phase the rollout, measure impact as you go, and manage price sensitivity with trials, free units, discounts, and coupons.
Pricing experiments compound when every change ships in configuration.
"We needed a system that allowed our business to take control of pricing rather than it being an engineering problem."
Pricing had to flex by category, country, subscription tier, and add-on, and every change ran through engineering.
New tiers and add-ons now launch in weeks rather than quarters, with features that took six weeks of engineering deploying in one.
Revising prices meant editing every plan by hand, which limited how often the team could test.
A 20% increase in acquisition revenue from pricing experiments that could not previously be run.
Multi-product customers sat on separate subscriptions, invoices, and renewal dates, blocking a move to a hybrid model.
Shifted from seat-based to hybrid monetization, with packaging managed centrally through Entitlements.
Everything needed to model, launch, test, and deploy pricing.
Tiered, flat-fee, bundled, hybrid, and pay-as-you-go add-ons on one engine.
Plan and SKU modeling, entitlement gating, free-to-paid conversion, and upsell bundles.
Flexible billing periods, phased rollouts, and proration control.
Pricing tables, A/B testing, Renewal Price Optimization, and signal-driven cohort targeting.
Product and growth teams do. Plans, bundles, prices, and entitlement rules are configured in the UI, so pricing changes do not require an engineering release.
Plans, bundles, and prices are created and changed through the UI and go live in minutes, ready for the next experiment.
Yes. You test price points, packaging, coupons, and plan layouts in a visual pricing table editor, with control groups and holdouts to prove causal lift. New and returning visitors can be targeted separately.
Every pricing experiment creates a new signal. Compare response across plan, tenure, usage, and payment history to see where the next opportunity may sit. Each result adds context for the next pricing decision, turning disconnected tests into a continuous learning system. Chargebee calls the approach Subscriber Intelligence.
Flat-fee, tiered, per-unit, usage-based, hybrid, and freemium models, plus pay-as-you-go add-ons and credits on one engine. Billing periods range from daily cycles to multi-year commitments.
New pricing applies to the customers you choose. Existing subscribers stay on the terms they signed up for, so you can test and launch new pricing without changing your current base.
Yes. Renewal Price Optimization lets you adjust the price at which existing subscriptions renew. Pricing keeps pace with the value you deliver, rather than staying fixed at whatever a subscriber first signed up for.
No. Engineering handles the initial integration, then your app checks feature IDs against Chargebee. After that, pricing and packaging changes are configuration, not code.
Start free, or see pricing experiments run live in a demo.
Start free →G2 Leader, Summer 2026 · 6,500+ customers · SOC 2 Type II