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Monetisation

SaaS price increase software that estimates revenue and churn before you raise prices

Before a SaaS price increase, you need two numbers: the extra monthly recurring revenue (MRR) and the extra churn. Monetisation reads your pricing page and, once connected, Stripe through a read-only key, picks the plan where an increase pays most, and estimates a low, expected and high range net of assumed extra churn. You measure the change on new customers first. Your first three findings take about a minute, with no card.

No card, no account Public pages only Every estimate shows its method

SaaS price increase software that estimates revenue and churn before you raise prices

Who needs SaaS price increase software

You know the product deserves a higher price. The harder question is whether customers agree enough for the increase to pay. For a SaaS founder, head of growth or finance lead, the decision needs a revenue case and a way to check it after launch.

Monetisation fits US SaaS businesses at roughly 20,000 to 2 million USD ARR that have recurring revenue to examine and a price change to make. The trigger often looks familiar:

  • Prices stay unchanged since launch while the product keeps adding value.
  • A rival raises prices and your team wonders whether the market accepts more.
  • AI or infrastructure costs rise faster than revenue per account.
  • The board asks why average revenue per account (ARPA) stays flat.

None of these proves that every plan needs an increase. A low entry price may still bring in the right buyers, while the plan carrying most revenue has room to move. Start with the plan that matters financially. If discounts or packaging might be the real issue, a SaaS pricing audit helps you compare those opportunities before choosing the increase.

Opportunities, ranked by expected value Example
Pricing Increase Team plan price 12 percent 400 accounts sit on Team at $49 and usage has grown since launch.
Estimate, per month +$1,470 $550 to $2,260
Method: Plan revenue times a 6 to 15 percent increase, minus 3 to 4 percent assumed extra churn at the new price.
Example card with illustrative figures. Your audit computes them from your own data, as estimates, not a guarantee of results.

What the tool estimates before you raise prices

Monetisation connects the price customers see with the revenue they actually produce. With Stripe connected, it selects the plan with the most MRR and models an increase against that revenue base. This makes the first test specific enough to evaluate.

Input Where it comes from Why it matters
Plan accounts and MRR Stripe through a restricted read-only key Establishes the revenue base and accounts exposed to the change
Current price Your pricing page and Stripe plan data Shows the advertised price alongside what the plan earns
Yearly share Stripe billing data Helps you distinguish monthly exposure from customers awaiting renewal
Discount depth Stripe coupons and billing data Explains why a higher list price may produce less extra revenue than expected
Churn baseline Stripe subscription history Provides the existing trend against which to measure additional losses
Competitor prices Competitor watch on Growth and Scale Adds market context for the price you want to test

Competitor context informs your judgment. It is not a direct multiplier in the price increase formula. The competitor price tracker helps you watch that context as rival offers change.

The output is a low, expected and high monthly revenue estimate after assumed extra churn. Those churn assumptions describe scenarios, not a prediction of exactly who cancels. Public-page findings use assumptions with low confidence; connecting Stripe replaces the revenue base with your own billing data. Read how the estimates are calculated to inspect the method before relying on a range.

A worked example of a Team plan increase

This is an illustrative example, not a customer result. Suppose a Team plan has 400 accounts paying 49 USD a month without discounts. Its MRR is 400 times 49 USD, or 19,600 USD.

A 12 percent increase brings the price to 54.88 USD, about 55 USD. With every account retained, that adds 2,352 USD MRR. The expected scenario assumes an extra 4 percent of those accounts leave because of the increase. That is 16 accounts, each worth 54.88 USD at the new price.

The arithmetic is 2,352 minus (16 times 54.88), giving 1,473.92 USD net extra MRR, or about 1,474 USD. Using the unrounded price keeps the estimate consistent from beginning to end.

Scenario Price increase Assumed extra churn Added MRR before churn Revenue lost at new price Net extra MRR
Low 6 percent 3 percent 1,176.00 USD 623.28 USD 552.72 USD
Expected 12 percent 4 percent 2,352.00 USD 878.08 USD 1,473.92 USD
High 15 percent 3 percent 2,940.00 USD 676.20 USD 2,263.80 USD

These are the engine's scenario pairings. They show the monthly effect if the modeled plan revenue moves to the higher price. A rollout limited to new customers realizes that effect gradually as new subscriptions enter; it does not immediately add the full estimate to your existing book.

How much extra churn the increase can absorb

Break-even extra churn equals the increase divided by one plus the increase. For 12 percent, that is 0.12 / 1.12, or about 10.7 percent of the plan's accounts. At that point the retained accounts at the higher price produce the original MRR.

This is a revenue boundary, not a target. It excludes operating costs, acquisition costs and future expansion. Losing valuable accounts may hurt beyond their current subscription revenue, even while the monthly arithmetic stays positive.

Revenue report with bar charts, a calculator and a laptop on a finance desk
Revenue report with bar charts, a calculator and a laptop on a finance desk

How to roll out a SaaS price increase safely

The opportunity comes with a playbook, and you run the change as an experiment with a baseline. You control the Stripe edits and customer communication. Monetisation helps you decide what to test and assess what happens.

  1. Choose the plan and record the baseline. Review the plan carrying the most MRR, its current churn and the proposed increase. Decide what result justifies continuing before changing the price.
  2. Start with new customers. Create the new price in Stripe and watch conversion for 14 days, as the playbook recommends. Check whether the higher revenue per new account compensates for any reduction in buyers. Existing subscribers stay on their current price during this first test.
  3. Plan the existing customer transition. Give existing customers 60 days of notice before their price changes, subject to their contract terms. Include the amount, effective billing date and practical options in your message. Explain the value added in terms customers recognize.
  4. Choose a grandfathering policy. Keep the old price for a stated period or move customers at renewal. Both give customers time to adjust. Set the policy before sending notice so your team can answer consistently.
  5. Consider a yearly offer before the change. Customers who already expect to stay may prefer a yearly commitment. Review annual plan pricing alongside the increase, and account for the discount when judging the revenue effect.
  6. Review the result before expanding. Track the plan's churn against the baseline and read the experiment verdict. A win supports continuing, while flat, loss or not enough data calls for a closer look at the result and exposure.

Fourteen days is an initial conversion check, not proof of long-term retention. The existing customer rollout needs its own observation period as renewals occur. Keep the two groups distinct when interpreting the result.

How to measure the result against a baseline

A higher MRR total after launch does not establish that the increase works. New sales, normal cancellations and a changing plan mix can move revenue at the same time. Measurement needs a dated change and a comparison.

Billing changes use a dated intervention

For a price change you make in Stripe, Monetisation measures the intervention against the baseline trend. Record when the new price takes effect, then examine the revenue movement alongside churn for the affected plan. This helps separate the existing trajectory from the movement following your decision.

That comparison has limits. If you change discounts, acquisition channels and packaging at the same time, attributing the result to price becomes harder. Keep the initial test focused and document what changes.

Pricing page variants use a holdout

On Growth and Scale, the snippet serves pricing page variants with a holdout group. The holdout supplies a comparison for visitor conversion while the variant presents the changed offer. This is a different measurement approach from tracking a billing intervention against a historical trend.

Experiments return a verdict of win, flat, loss or not enough data, with the lift and its interval. Treat the last verdict as unresolved evidence. A quiet period with few purchases does not establish that a higher price preserves conversion.

Experiment result, 28 days, holdout control Example
Team plan at $55 for new customers Primary metric: Revenue per visitor Win Existing customers keep their price until the 60 day notice ends.
+7.4% Interval +1.8% to +12.9% -20%0+20%
Example verdict with illustrative figures. Every test reports lift with an interval and a plain verdict.

How software compares with spreadsheets and consultants

A spreadsheet is a sensible place to check arithmetic. Its weakness is keeping assumptions, exports and results current. Monetisation makes that recurring work part of the product, while a consultant adds research that billing history cannot supply.

Factor Spreadsheet Monetisation Pricing consultant
Cost Cheap if your team builds it From 49 USD a month billed yearly, 99 monthly Quoted per project
Time Depends on exports and manual upkeep First three public-page findings in about a minute Depends on research and project scope
Data used Manual exports and guesses about customer response Public pages and read-only Stripe, with competitor watch on Growth and Scale Billing data plus interviews and willingness to pay surveys
Measurement Your team builds and maintains the comparison Baseline measurement, plus page variants with holdout on Growth and Scale Depends on the engagement and implementation
Best for Checking a simple scenario Recurring pricing decisions with estimates and measured results Full repositioning or limited pricing history

Consultants win when you need willingness to pay surveys, buyer interviews or a new value proposition. With no pricing history, those conversations may teach you more than billing analysis. Compare pricing consultants if your decision reaches beyond a price increase. For ongoing tests on an established subscription business, software keeps the estimate and result together.

Choose a plan for your pricing work

Plan Price billed yearly Price billed monthly Full audits per month Experiments running at once
Starter 49 USD a month 99 USD a month 4 3
Growth 199 USD a month 399 USD a month 20 15
Scale 599 USD a month 1,199 USD a month 80 60

All plans include read-only Stripe, opportunities with estimates and experiments for measuring billing changes against a baseline. Growth and Scale include competitor watch and pricing page variants with holdout. Choose based on how much pricing work you run at once and whether you need those comparisons.

Check your increase before committing to it

Enter your website in the form at the top of this page to get your first three findings in about a minute, no card. Connect Stripe on a paid plan to ground the opportunity in your own recurring revenue. Then follow the playbook, test new customers first and measure the result before changing existing subscriptions.

For the broader process of finding and testing revenue opportunities, see pricing optimization software.

Questions

How much should a SaaS company raise prices?

Raise prices by an amount your product value and retention can support, then test it on new customers first. Monetisation models increases of 6 to 15 percent against your plan revenue, subtracting assumed extra churn. Use the expected result and downside case to choose a test, rather than applying the same increase across every plan.

What is the average SaaS price increase?

There is no single verified benchmark for the average SaaS price increase. Many SaaS increases land between 5 and 20 percent, but that span is not a measured market average. The right size depends on how far price sits below value and competitors. Monetisation models 6 to 15 percent ranges on your own data.

How do you raise SaaS prices without losing customers?

You cannot guarantee that nobody leaves, but you can limit exposure by testing new customers first. Watch conversion, explain the value added, and give existing customers advance notice. Monetisation supplies a rollout playbook and measures the change against a baseline, so you can compare the extra revenue with the churn that follows.

Should you grandfather existing customers when raising prices?

Grandfather existing customers when a transition period protects trust or honors an earlier commitment. Keeping their old price temporarily or moving them at renewal gives them time to decide. Set a clear end date and compare the delayed revenue with retention risk. Permanent grandfathering leaves a price gap that becomes harder to manage later.

How much notice should you give before a SaaS price increase?

Give existing customers 30 to 60 days of notice in common cases, and longer if their contracts require it. The Monetisation playbook uses 60 days. Check renewal terms before choosing an effective date, explain the new amount and billing date clearly, and give customers time to review their plan or consider yearly billing.

Does Monetisation change my prices in Stripe?

No, Monetisation does not change your prices in Stripe because its connectors are read-only. You create the new price in your own Stripe account and decide which customers receive it. Monetisation supplies the opportunity estimate and playbook, then measures the dated billing change against the baseline trend to help you judge the result.

See what your own site is leaving on the table

A sample audit reads your public pages and returns the first three opportunities with estimates and methods. About a minute, no card.

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