ROI calculator
Model the upside before you change the workflow.
Use your own lead volume, close rate, deal size, and manual workload to estimate what a modest conversion improvement and less manual execution could mean for the business — with every assumption stated rather than buried in the model.
Your current funnel
Use your current operating numbers. The model applies a conservative 15% conversion lift and 30% reduction in manual hours to illustrate potential—not a guarantee.
Modeled impact
What better conversion and less manual work could mean.
Additional monthly revenue
$7,500
Estimated annual impact
$90,000
Additional customers / month
1.5
Hours saved / month
12
Illustrative model only. Actual results depend on traffic quality, sales process, offer, pricing, adoption, and execution.
What this computes
Two effects, kept apart on purpose.
The calculator estimates two things and does not add them into a single headline figure. The first is revenue: your lead volume multiplied by the close rate you enter, moved by the conversion improvement you choose, priced at your own average deal size. The second is time: the hours you say go into repeated manual execution, converted at a fully-loaded cost.
They are separated because they are not equally knowable. A conversion forecast assumes your funnel keeps behaving as it has, which is an assumption about the future. Hours spent on a repeated task is something you can count this week and count again next quarter. Blending them produces one confident-looking number whose reliability is that of its weakest half.
Everything here is arithmetic on your inputs. There is no benchmark, no industry average, and no implied claim about what typical customers achieve — a model that supplies its own optimistic assumptions is a pitch wearing a spreadsheet.
- Inputs
- Yours only
- Benchmarks used
- None
- Result type
- Gross, not net
- Best used
- Before the change
Where the numbers come from
An estimate is only as good as the step that captured the baseline.
The problem
Most ROI models are unfalsifiable by design.
The standard vendor calculator supplies its own improvement percentage, applies it to numbers the reader half-remembers, and reports a figure with two decimal places. Nothing in that chain can be checked later, which is precisely what makes it comfortable to publish.
The failure is not optimism, it is irreproducibility. If nobody recorded the starting state, there is no reading afterwards that can confirm or refute the estimate — so the estimate never gets tested and the next one is built the same way.
The fix is unglamorous: capture the baseline before the change, state the assumption explicitly, and re-run the same arithmetic against measured values later. That makes the number arguable, which is the only property that makes it useful in a decision.
You're likely here because
- The improvement percentage was supplied by the vendor
- Nobody recorded what the metric was before the change
- Two teams compute the same figure differently
How to use it
From an estimate to a defensible number.
The order matters. A baseline captured after the change is an estimate of the past, and should be labelled as one.
Step 01
Record the inputs
Write down lead volume, close rate, deal size, and manual hours as they are today, with the date. This is the step that cannot be done retrospectively without guessing, and the one most often skipped.
Step 02
Choose a conservative delta
Enter the smallest conversion improvement that would still justify the change. If the case only works at an ambitious input, the model has told you something important.
Step 03
Separate the two results
Treat the revenue figure as a forecast and the hours figure as a countable observation. Report them apart so a soft number does not borrow confidence from a firm one.
Step 04
Subtract the platform cost
The output is gross. Net it against your plan cost before comparing to anything, and discard any case that only clears the bar before that subtraction.
Step 05
Re-measure on a cadence
Re-run the identical calculation on a fixed interval against measured values. A trend against stable definitions is evidence; a single favourable reading is an anecdote.
Limitations
What this calculator does not do.
- It does not predict your results. Every figure is arithmetic on inputs you supplied, and it inherits whatever error those inputs carry.
- It does not model ramp time. Improvements that take a quarter to appear are shown as though they applied immediately, which overstates the first-period figure.
- It does not account for the cost of change — migration effort, retraining, or the period where a team runs both the old process and the new one.
- It does not distinguish leads by source or quality, so a volume increase that arrives at a worse close rate will read as a straight gain.
- It reports gross impact. Subtract your plan cost, and any implementation cost, before treating the result as a return.
FAQ
Questions about the model.
Is this a projection of what UbiGrowth will deliver?
No. It is arithmetic on numbers you supply. The calculator multiplies your own lead volume, close rate, and deal size by a conversion improvement you choose, and converts the hours you say are spent on manual work into a cost. It contains no benchmark, no industry average, and no claim about typical results.
What conversion improvement should I enter?
Enter the smallest improvement you would still consider worth the change. A model that only works at an optimistic input is not a decision aid — it is a sales argument. If the case holds at a conservative number, the number you actually get will be a pleasant surprise rather than a required condition.
Why does the calculator ask for manual hours separately?
Because the two effects have different reliability. Revenue from conversion improvement is a forecast and depends on your funnel behaving as it has. Hours removed from a repeated manual task is closer to an observation — you can count the task today and count it again afterwards. Keeping them separate stops a soft number from borrowing confidence from a firm one.
How do I turn this estimate into evidence?
Record the inputs before you change anything. That is the baseline, and it is the step that cannot be reconstructed afterwards without guessing. Re-run the same calculation against measured values on a fixed interval, and the output becomes a trend you can defend instead of a single favourable reading.
Does the estimate account for the cost of the platform?
The calculator reports gross impact, not net. Subtract your own plan cost from the result — the pricing page states what each tier costs — and treat anything that only clears the bar before that subtraction as not clearing it.
Start with ARIA
An estimate is a starting point. Ask ARIA for the evidence.
Tell ARIA which workflow you modelled. It can run the change against real work and return a result you can measure the same way twice.
- ARIA acts only through the systems and permissions you connect.
- Connections use scoped credentials you can change or revoke.
- Actions are recorded, and consequential ones can require approval.
Start here
An estimate is a starting point, not the evidence.
Capture the baseline, run the change against a real workflow, and measure the same way twice. Try ARIA costs nothing and gives you something concrete to measure against.