Skip to content
OneKitly

Lead-to-customer rate calculator

Compute what share of your leads become paying customers.

The Lead-to-customer rate calculator turns Customers won, Total leads into Lead-to-customer rate, instantly and for free. For instance, with Customers won = 30 and Total leads = 300 it returns Lead-to-customer rate = 10%.

How to use it

  1. Enter your values: Customers won, Total leads.
  2. Read the result instantly: Lead-to-customer rate.

Frequently asked questions

What does the Lead-to-customer rate calculator actually compute?

It takes Customers won and Total leads and derives Lead-to-customer rate from them. The calculation is live as you type, so the result updates on every change.

What information do I need to provide?

2 values: Customers won and Total leads. Nothing else is required — no account, no file upload.

Can you show a worked example?

With Customers won = 30 and Total leads = 300, the calculator returns Lead-to-customer rate = 10%. Those figures come from running this exact tool, so you can reproduce them by entering the same values.

When would I actually use this?

Before and after a campaign: turning a target into a daily budget, comparing two channels on the same basis, and deciding whether the return justifies continuing.

What is the most common mistake?

Judging ROAS without subtracting the cost of goods. A 3× return on ad spend is a loss whenever the margin is under a third — the ratio says nothing about profit on its own.

What is the difference between the Lead-to-customer rate calculator and the Cost per lead (CPL) calculator?

This one returns Lead-to-customer rate; the Cost per lead (CPL) calculator returns Cost per lead. That is the whole difference — open the one whose figure you need.

Is there a tool for the next step?

Cart abandonment rate calculator is the closest one after this: Compute your shopping cart abandonment rate from carts created and completed.

What else is worth having open alongside it?

Product return rate calculator and Bounce rate calculator — they come up in the same task often enough to be worth a second tab.

Where do the figures come from, and how current are they?

The formulas are the industry-standard ones every ad platform uses; the inputs come from your own reporting. Platforms differ in attribution window and in what counts as a conversion, so figures rarely reconcile exactly between them.

Further reading

All guides
ExplainerThe Lead-to-Customer Rate, and Why It Is Not One NumberThe overall rate is the product of the stage rates, which makes a percentage gain anywhere worth the same percentage overall — and a ten-point gain worth wildly different amounts depending on where you put it. Plus the lag that makes a growing business look worse than it is.ExplainerCost per Lead, and the Funnel Arithmetic Behind ItCPL is spend divided by leads, and alone it means almost nothing, because a lead is whatever you decided to call one. Worked here: a channel with twice the CPL producing half the CAC, and the redefinition that moves CPL fivefold without moving CAC at all.ExplainerReturn Rate: The Number That Decides Whether Your Ecommerce WorksA returned order is not a cancelled sale, it is a sale that cost you money. Here is the return rate at which returns eat the entire contribution of the orders that stayed sold, for three product profiles and five margin levels — plus what bracketing does to your order count.ExplainerCart Abandonment: The Metric and the Money Behind ItAbandonment rate is one minus completed over created — and the figure quoted everywhere is an average across wildly different shops. The useful work is turning a percentage point of checkout completion into money, then discounting it for returns.How-toHow to Calculate NPS: The Formula, a Worked Score, and What It HidesPercentage of promoters minus percentage of detractors. Passives sit in the denominator and nowhere else, the result runs from −100 to +100, and it is not a percentage despite looking like one.ExplainerARPU and the Averages That Hide Your BusinessAverage revenue per user is a mean over a distribution with no middle, divided by a denominator nobody defines. Here is the same month of revenue read five ways, and two opposite businesses landing on exactly the same ARPU.