Revenue Reverse-Engineer

What the Revenue Reverse-Engineer Does

The revenue reverse-engineer turns a revenue goal into required funnel throughput.

It answers leadership questions like:

• How many deals do we need per month to hit the goal?

• Given our conversion rates, how many calls does that require?

• How much traffic is required to generate that many leads?

• What monthly ad budget would be needed at our CPC?

• If we improve conversion rates, how much budget do we save?

• Do we have the sales capacity to handle the optimized volume?

This tool is designed to reduce planning ambiguity.

Who This Tool Is For

The revenue reverse-engineer is useful for:

• CEOs and founders setting growth targets

• COOs translating targets into execution plans

• CMOs planning acquisition budgets based on funnel realities

• sales leaders planning capacity and hiring

• teams deciding whether to invest in funnel optimisation or media spend

It’s especially helpful if:

• targets are set annually but execution planning is monthly

• marketing budget is increasing without predictable returns

• hiring decisions are made without call volume math

• your funnel has known leaks but the cost of leakage isn’t quantified

How the Calculator Works

The tool starts with four core inputs:

• annual revenue goal

• average deal value

• cost per click (CPC)

• funnel conversion rates

It converts annual revenue into monthly revenue and monthly deals needed.

Then it reverse-engineers required throughput from the bottom up:

Deals needed → calls needed → leads needed → traffic needed → budget needed

You can input:

• baseline funnel rates (current reality)

• optimized funnel rates (target system)

This produces side-by-side comparisons for budget, traffic, and capacity.

What Inputs to Use (So Results Are Reliable)

A reverse-engineer tool is only as useful as the inputs.

Use realistic averages

Use a 60–90 day average for:

• landing page conversion rate

• lead-to-call rate

• close rate

Avoid using your best month.

Keep deal value consistent

If your deal value varies widely, use:

• average closed-won value over the last 90 days
  or

• a conservative midpoint for planning

Use blended CPC

If you have multiple channels, use:

• blended CPC (weighted average), not a single campaign CPC

Treat optimized rates as “achievable, not aspirational”

Optimized rates should reflect improvements you can actually implement:

• offer clarity

• speed-to-lead

• nurture system

• sales process consistency

• proof and objection handling

Baseline vs Optimized Scenario Planning

The revenue reverse-engineer is most useful when you compare scenarios.

Baseline scenario

Shows what it costs to hit the goal if nothing improves.

This often reveals:

• unrealistic traffic requirements

• excessive ad budget

• unsustainable call volume

• hidden staffing needs

Optimized scenario

Shows what changes if you fix conversion leaks.

This often reveals:

• lower budget needed

• lower traffic required

• same revenue with less waste

• improved ROAS

• different staffing requirements

The gap between baseline and optimized is the value of system improvement.

How to Interpret the Outputs

The tool produces a few core outputs. Here is how leaders should read them.

1) Monthly Ad Budget Required

If baseline budget is very high, that’s a signal:
Your funnel is doing expensive work.

If optimized budget drops significantly, that indicates:
Funnel improvement is a direct cost-saving lever.

2) Monthly Traffic Required

Traffic required becomes unrealistic when conversion is low.

If traffic required looks extreme, the answer is usually not “buy more traffic.”
The answer is to fix conversion constraints.

3) Sales Staffing Requirement

Capacity is often the hidden constraint.

If optimized calls increase meaningfully, you may need:

• additional reps

• improved qualification

• better nurturing to reduce low-intent calls

The tool makes that visible.

4) Efficiency Savings

Savings quantify what funnel leaks cost annually.

This helps leadership choose:
Funnel optimisation vs increased media spend.

5) Target ROAS

ROAS is a directional signal:
Are you creating enough revenue relative to spend?

It’s not a guarantee, but it’s useful for comparing scenarios.

Common Mistakes When Reverse-Engineering Revenue

Mistake 1: Treating the output as a promise

This is not a forecast.
It is a planning model.

Mistake 2: Ignoring capacity constraints

If sales can’t handle the volume, improving the funnel creates a new bottleneck.

Mistake 3: Optimizing only one rate in isolation

In real systems:

• improving landing page conversion changes lead quality

• improving lead-to-call changes call intent

• improving close rate may require better qualification upstream

Use the tool to test tradeoffs, then design the system.

Mistake 4: Using aspirational optimized rates

If the optimized rates require a full rebuild, the planning becomes fragile.

Use achievable targets.

Mistake 5: Forgetting about sales cycle timing

The tool is throughput-based, not cycle-based.

If your sales cycle is long, you’ll need:

• pipeline timing planning

• lag awareness in targets

Example Scenarios

Scenario 1: Leadership wants to hit $1M with paid traffic

Baseline shows:

• high traffic required

• high monthly budget

• call volume that requires more reps

Optimized shows:

• lower traffic required

• lower budget required

• higher ROAS

• reps needed becomes manageable

Leadership decision:
Fix funnel conversion before scaling spend.

Scenario 2: Sales team wants more leads

Baseline shows:

• leads aren’t the constraint

• call-to-deal is weak

• increasing leads increases wasted effort

Optimized shows:

• improving close rate reduces traffic and budget requirements

• hiring and sales enablement become higher leverage than ads

Leadership decision:
Fix sales conversion and qualification first.

If This Sounds Like You (Diagnostic Checklist)

The revenue reverse-engineer is useful if:

• you have a revenue goal but no operational plan

• marketing spend is increasing without clarity on required conversion

• sales is overloaded or underutilised

• hiring decisions are made without call volume math

• your funnel leaks are known but not quantified

• leaders disagree on whether to invest in ads or optimisation

• targets feel unrealistic once execution begins

How I Think About This (From Real Work)

When teams miss targets, it’s often not because they aimed too high.

It’s because they never translated targets into system requirements.

What I typically see:

• annual goals set without funnel math

• marketing asked to “get more leads” without conversion clarity

• sales capacity ignored until late

• budget decisions made without understanding leakage

• improvement efforts scattered across too many initiatives

What I prioritize:

• establish baseline rates honestly

• convert the goal into required throughput

• compare baseline vs optimized

• quantify the cost of leakage

• align staffing and operating cadence to the scenario

What good looks like:

• targets become operationally real

• leaders can see tradeoffs clearly

• investment decisions become calmer

• funnel work is prioritised by leverage

• capacity constraints are addressed before they break delivery