AI Marketing ROI Calculator

What this calculator answers

This page answers one narrow question: given what you expect an AI marketing investment to save and to add, what is it worth per month and when does it pay back? It does not tell you whether your inputs are right. That is a separate job, covered step by step in Calculating AI Marketing Returns.

The calculator counts two kinds of value and nothing else:

1. • Time removed. Hours of marketing work that no longer need doing, priced at what an hour of that work really costs you.
2. • Extra customers. Additional qualified leads per month, converted at your real lead-to-customer rate and valued at the gross profit a new customer brings.

Brand lift, faster decisions and better morale are real, but they are left out on purpose. If an investment only pays back when you add soft benefits, you should know that before you sign anything.

Calculator

Marketing return calculator

Estimate the monthly return of a marketing investment from time it removes and customers it adds.

Monthly investment (£)One-off setup cost (£)Hours of work removed per monthLoaded cost per hour (£)Salary plus employer costs, divided by working hours.Extra qualified leads per monthLead-to-customer rate (%)Gross profit per new customer (£)

The starting figures are illustrative round numbers, not AfM prices or client results. Replace them with yours.

Monthly value

£4,200

£1,200 of time plus £3,000 of gross profit from new customers

Net monthly return

£1,200

Monthly value minus the monthly investment

Return on investment

40%

Net monthly return divided by the monthly investment

Payback on setup

1.7 months

Setup cost divided by net monthly return, when the return is positive

Assumptions

• Time removed is only worth money if the hours are redeployed to useful work or a cost is avoided.
• Extra leads must be incremental: leads you would have won anyway do not count.
• Gross profit, not revenue, is used for new customers.

How the numbers are combined

The formulas are deliberately plain so you can check them on paper:

• • Monthly value = hours removed × loaded cost per hour + extra qualified leads × lead-to-customer rate × gross profit per new customer
• • Net monthly return = monthly value minus monthly investment
• • ROI = net monthly return ÷ monthly investment
• • Payback = one-off setup cost ÷ net monthly return, shown only when the net return is positive

Two choices in that design matter. First, value is counted in the month the customer is won, so gross profit per new customer should be a figure you are confident of within a sensible horizon, such as the first twelve months. Using lifetime value here flatters the result. Second, payback uses the net monthly figure, so an investment that only breaks even month to month never pays back its setup, and the calculator says so rather than inventing a date.

Worked example

Illustrative example. The figures are round and hypothetical, chosen to show the arithmetic, not taken from any client.

A professional services firm is considering a managed AI-assisted marketing service. Its assumptions:

• • Monthly investment: £3,000
• • One-off setup cost: £2,000
• • Hours of work removed per month: 40 (drafting, reporting and list preparation the team currently does by hand)
• • Loaded cost per hour: £30
• • Extra qualified leads per month: 6
• • Lead-to-customer rate: 20%
• • Gross profit per new customer (first twelve months): £2,500

Step 1, value of time removed. 40 hours × £30 = £1,200 per month.

Step 2, value of extra customers. 6 leads × 20% = 1.2 new customers per month. 1.2 × £2,500 = £3,000 per month.

Step 3, monthly value. £1,200 + £3,000 = £4,200.

Step 4, net monthly return. £4,200 minus £3,000 = £1,200.

Step 5, ROI. £1,200 ÷ £3,000 = 0.40, so 40% a month on the monthly spend.

Step 6, payback. £2,000 ÷ £1,200 = 1.67 months, a little over seven weeks.

Enter these seven figures in the calculator above and it returns the same monthly value, net return and ROI; it rounds payback to one decimal place, so it shows 1.7 months.

On paper that is a clear yes. The next section shows why you should not stop there.

Which inputs decide the answer

Change one input at a time and the example tells you where the risk sits.

Sensitivity of the worked example (illustrative figures)

Scenario	Monthly value	Net monthly return	Payback
Base case as above	£4,200	£1,200	1.67 months
Extra leads halve to 3	£1,200 + £1,500 = £2,700	minus £300	Never at these inputs
Freed hours not redeployed (count as £0)	£0 + £3,000 = £3,000	£0	Never at these inputs
Close rate falls to 10%	£1,200 + £1,500 = £2,700	minus £300	Never at these inputs
Loaded cost rises to £40 per hour	£1,600 + £3,000 = £4,600	£1,600	1.25 months

The pattern is typical of this kind of model. The customer term is usually larger than the time term, so the lead estimate and the close rate carry most of the weight. Halving the lead estimate turns a comfortable return into a monthly loss. Meanwhile a higher hourly cost helps only modestly.

That tells you where to spend your scepticism. Before trusting a result, ask of the largest term: what evidence do I have that this many extra qualified leads will arrive, and would they have arrived anyway? The difference between those two is covered in How to Measure ROI of AI Marketing Automation.

Filling in the inputs without fooling yourself

Where each input should come from

Input	Good source	Common mistake
Monthly investment	The full recurring cost: service fee, subscriptions, usage charges and internal oversight time	Counting only the software subscription
One-off setup	Onboarding, tracking fixes, integration and the internal hours to brief it	Leaving out your own team's setup time
Hours removed	A timed sample of the task today multiplied by monthly volume	Using a vendor's headline percentage
Loaded cost per hour	Salary plus employer on-costs divided by productive hours	Using salary ÷ 2,080 hours
Extra qualified leads	A test, a holdout or a conservative share of current volume	Assuming every new lead is extra
Lead-to-customer rate	Your CRM over the last two or three quarters	Using the best month
Gross profit per customer	Revenue minus direct delivery cost over a fixed horizon	Using revenue, or lifetime value

If you are costing a single automated workflow rather than a whole service, set extra leads to zero and read AI Marketing Automation ROI, which works through the volume at which automation breaks even. For B2B businesses where a deal closes months after the lead arrives, AI for B2B Marketing ROI shows how to value pipeline before revenue lands.

Reading the result

• • Negative net return at conservative inputs: the case rests on optimism. Either narrow the scope to the part with clear time savings, or run a small test to earn a better lead estimate.
• • Positive, but payback beyond twelve months: the setup cost is doing the damage. Ask whether it can be staged.
• • Positive with payback inside a quarter even when leads are halved: a robust case. The next risk is execution, not arithmetic.

Whatever the result, write the inputs down next to the answer. A figure without its assumptions cannot be checked later, and checking later is the point.

FAQ

Why does the calculator ignore brand awareness and other soft benefits?

Because they are hard to price honestly and easy to inflate. Leaving them out means a positive result stands on countable value alone; you can still weigh soft benefits separately when you decide.

Should I use lifetime value for gross profit per new customer?

Not in this calculator. It counts value in the month the customer is won, so lifetime value would pull years of profit into one month. Use gross profit over a horizon you trust, such as the first twelve months.

What if my ROI is positive but payback shows nothing?

That cannot happen with these formulas: payback appears whenever net monthly return is above zero. If payback is blank, net return is zero or negative, so the monthly value does not yet cover the monthly cost.

Is 40% monthly ROI in the example a typical result?

No claim is made about typical results. The example uses hypothetical round numbers to show the arithmetic, and the sensitivity table shows how quickly that figure disappears when the lead estimate is halved.