Pricing optimization software that shows the method behind every number

Why pricing is the lever most teams leave alone

Most companies set a price at launch, adjust it once or twice, and then spend the next few years on acquisition. Acquisition gets the budget because it is easy to see. Pricing gets ignored because nobody owns it and every change feels risky.

Yet price is the input with the most direct line to revenue. A new customer brings one subscription. A better price lifts every subscription you already have, plus every one you sign from now on. The difficulty is not knowing that pricing matters. It is knowing which change to make, how large the gain is likely to be, and how to tell afterwards whether it worked.

That is the gap Monetisation fills. It looks at what customers actually pay, not what the pricing page says they pay, and turns the difference into a short list of specific changes with an estimate for each.

What Monetisation looks at

When you connect Stripe with a restricted read-only key, Monetisation builds a revenue model from your billing history. It normalises MRR and ARR, then breaks revenue down by plan, billing interval, discount and cohort. Add your website and it reads the public pricing page, the plan names, the feature lists and the paywall, if there is one.

From those two views it looks for patterns like these:

• Plan mix that bunches at the bottom. If 80 percent of paying accounts sit on the cheapest plan while using features close to the next tier, the gap between plans is probably too wide or the entry plan too generous.
• Prices unchanged for a long time. A list price that has not moved in years while the product grew is a common sign of room to raise it for new customers.
• Discounts that became the price. When most new subscriptions carry a coupon, the real price is the discounted one. This pattern is known as discount leakage.
• A weak annual offer. Few annual subscribers, or an annual discount that is either too small to tempt or too large to pay off. Our guide to annual plan pricing covers the arithmetic.
• Heavy users on flat plans. When a small share of accounts drives most of the usage, a usage component or overage often captures value that flat pricing gives away.

Each pattern becomes an opportunity card with an estimated monthly impact, a confidence level, effort, risk and the method behind the number.

How an estimate is built

Every opportunity shows a range, not a single figure, because pricing changes carry real uncertainty. The method is written out so you can disagree with it.

Take a hypothetical SaaS with 400 customers on a Team plan at 49 USD per month. Monetisation suggests a 10 percent increase for new customers only, with existing customers kept on their current price.

The figures look small for one month. They compound: after a year of sign-ups at the new price the expected case adds about 1,020 USD of MRR, before churn. The card shows that compounding too, and states the assumption about conversion so you can change it.

The full method, including how confidence is set and what changes when more data is connected, is on the page about how estimates work.

From recommendation to measured result

An estimate is a starting point. The useful number is the one you measure after the change. Every opportunity has a "Run experiment" button that turns it into an experiment card with a hypothesis, a metric, a baseline period and a test window.

There are three ways to run it:

1. Pricing page variants with a holdout. On Growth and Scale, a small JavaScript snippet shows a variant of your pricing page or paywall to part of your traffic and keeps a holdout group on the original. Conversion and revenue per visitor are compared between the groups.
2. A change you make in your own billing. You create the new price or annual plan in Stripe yourself. Monetisation records the date and compares the period after against the baseline trend before.
3. A playbook. For changes that are not a price, such as a new plan name or a retention offer, you get a checklist and a measurement window.

Results show lift, an interval and a verdict: win, flat, loss or not enough data. Losses are shown with the same prominence as wins, because a loss is information you paid for.

What pricing optimization software is not

Some tools sold under this name are built for manufacturers and distributors managing thousands of SKUs and quote approvals. Others are dynamic pricing engines that change prices on their own every hour. Monetisation is neither.

It is built for businesses that sell subscriptions, memberships, usage or digital products and that want to decide pricing changes themselves, with data. It does not write to your billing account. It does not set prices on its own. It shows you where the money is, how sure the estimate is, and what happened when you acted.

Who it suits

The product is self-service and priced for teams that do not have a pricing department.

• Founders of SaaS products who set prices once and suspect they are low. See SaaS pricing optimization for the typical first findings.
• Growth teams who run acquisition tests and want the same discipline on pricing.
• Companies with several brands or products that need one place to compare pricing across them, on Scale.

Pricing work also sits inside a wider question about every revenue stream you have. If ads, affiliate links or sponsorship are part of the picture, our page on revenue optimization software explains how Monetisation compares them.

Plans and what they include for pricing work

Monthly billing is also available at 99, 399 and 1,199 USD. Growth adds competitor pricing watch for up to 10 pages and the discount leakage monitor. Every plan is a paid subscription; the entry point is a one-time sample audit.

Start with a sample audit

Enter your website address on the homepage, choose your business type and you get a result page in about a minute. It shows the first three opportunities with their estimate ranges and a map of your revenue streams. No card is needed for the sample. Run a sample audit, or see pricing to compare plans.

Questions about data handling are answered on the security page, and anything else goes to [email protected].