Commercial Site Selection Owner Income: $185k Pay, Month 21 Breakeven
You’re selling complex location advice, so owner income depends on project flow, analyst leverage, data costs, travel, and how much cash stays in the firm This estimate covers a US commercial site selection service with $859k first-year revenue, $185k modeled owner-level pay, and breakeven in month 21, before taxes, debt service, and personal expenses
Owner income$185kNet margin-71% to 24%Revenue for target pay$0.8MBusiness difficultyHard
Want the six income drivers?
1
Engagement Fee
$179K-$407K
Bigger project packages raise revenue per client, so each win adds more take-home income.
2
Lead Flow
$120K-$220K
More marketing spend and lower CAC bring in more qualified deals, which feeds the top line.
3
Close Rate
21 mo
Faster closes get you past breakeven sooner and reduce the cash drag on owner income.
4
Delivery Capacity
1-6 FTE
More analyst and data science capacity lets you handle more work without hitting a service bottleneck.
5
Research Cost
20%-27%
Lower direct research spend keeps more gross profit from each project.
6
Advisory Revenue
Separate
Recurring advisory work adds extra income, but the model does not isolate retainers.
Want to test your owner pay?
Owner income calculator
Estimate owner take-home and target-pay gap from revenue, margin, costs, reserves, and target pay.
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Planning note: This is a researched planning estimate only, not guaranteed salary, tax advice, or owner distribution advice.
How do you check owner income in the Commercial Site Selection Service model?
When can a site selection business owner pay themselves?
A Commercial Site Selection Service owner can pay themselves from launch only if startup capital, signed work, or cash reserves cover the planned $185,000 managing director salary; for planning the full model, see How To Write A Business Plan For Commercial Site Selection Service?. The risk is cash timing: EBITDA is -$607,000 in year 1, -$71,000 in year 2, and breakeven does not arrive until month 21.
Safe Pay Triggers
Fund $185,000 salary from launch
Protect runway through month 21
Use signed client work first
Hold reserve for delivery delays
Cash Timing Risks
Watch sales cycle length
Track proposal conversion weekly
Bill early project milestones
Cut pay if onboarding slips
Can a site selection consulting business scale?
Yes — a Commercial Site Selection Service can scale, but owner income only improves if analyst leverage lifts completed projects faster than payroll and quality-control costs. In the model, geospatial analysts grow from 2 to 6 FTEs and senior data scientists from 1 to 3 FTEs, while revenue rises from $859k to $435M and EBITDA from -$607k to $1,028M.
Why it can scale
Solo expert keeps delivery simple
Team handles larger searches
Labor studies need more analyst hours
Incentive work adds billable depth
What limits scale
Management complexity rises fast
QC costs can outrun volume
Payroll must stay below project growth
Leverage must improve per lead
What margins and costs change site selection owner income most?
Owner income in a Commercial Site Selection Service moves most when you cut the 27% direct and variable cost stack, especially project travel (10%) and data subscriptions (8%). If you’re mapping the launch path, How To Launch Commercial Site Selection Service? helps with the setup logic. By the mature year, those costs fall to 20%, which lifts gross margin to 80%; fixed overhead still runs $24k/month, so capacity control matters.
Biggest margin levers
27% direct and variable costs at start
10% project travel hits income hard
8% data subscriptions are a fixed drag
20% mature cost rate lifts margin to 80%
Income risks to watch
$24k/month fixed overhead must be covered
Payroll rises from $715k to $1495M
Proposal time cuts capacity but is not direct cost
Founder selling time also reduces delivery capacity
Key Takeaways
Average engagement fee drives the fastest revenue lift.
Qualified pipeline matters more than raw traffic.
Long sales cycles delay cash and owner pay.
Hiring too early can erase margin fast.
Compare lean, base, and high owner-income scenarios
Owner income scenarios
Owner income moves with project mix, billable hours, and payroll. The first year is loss-making, then margin and volume improve by Year 3 and beyond.
Low, base, and high cases for planning owner pay.
Scenario
Low CaseLow Case
Base CaseBase Case
High CaseHigh Case
Launch model
This is the funded lean case, with first-year revenue at $859k and a deep EBITDA loss.
This is the modeled middle case, with Year 3 revenue at $2.508M and near-breakeven profit.
This is the mature-case upside, with Year 5 revenue at $4.35M and strong EBITDA.
Typical setup
The mix is still early, with about 48 projects, about $18k average package value, 73% gross margin, $715k payroll, and $120k marketing.
The mix shifts toward site selection at 70%, with about 93 projects, about $27k average package value, 77% gross margin, and $42k EBITDA.
The business is scaled, with about 107 projects, about $41k average package value, 80% gross margin, and $1.03M EBITDA.
Cost drivers
Heavy payroll
$120k marketing
negative EBITDA
early project ramp
fixed office and software load
Higher site selection mix
larger billable hours
tighter fixed-cost spread
stable referral commissions
modest EBITDA
More projects
higher package value
80% gross margin
stronger utilization
scalable overhead
Owner income rangeBefore owner reserves
$0 - $185kFunded downside
$0 - $42kMain plan case
$0 - $1.03MUpside case
Best fit
Use this to test cash needs if growth is slow and the owner can only draw a salary when funding covers the loss.
Use this as the main planning case for budgeting, hiring, and lender talks.
Use this to test the upside if project volume, pricing, and margin all hold.
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Planning note: Scenario ranges are researched planning assumptions, not guaranteed earnings, salary promises, tax advice, or distributions.
Commercial Site Selection Service Core Six Income Drivers
Average Engagement Fee
Average Engagement Fee
The average engagement fee is the fastest revenue lever here because each client pulls in specialized research, site scoring, labor analysis, and incentive support. In the source model, a first-year package is about $179k and a mature-year package is about $407k, based on service mix, hours, and hourly prices. Bigger scopes, like multi-state searches and labor-heavy studies, lift owner income fast.
Here’s the catch: underpricing custom work turns expert labor into low-margin delivery. If the fee does not cover the team’s billable hours plus 27% first-year direct costs and $24k/month overhead, take-home pay shrinks even when revenue looks healthy. Higher fees help the owner pay themselves sooner and keep cash for slow sales cycles.
Raise Fee Size Without Blowing Up Margin
Price from scope, not just time. Track three inputs on every proposal: research depth, states covered, and incentive work. Those inputs change the labor hours, and labor drives the fee. If a project adds multi-state search, complex facility needs, or negotiation, the fee should move up with it.
One clean rule: more scope = more fee. Watch realized fee per engagement, billable hours per project, and gross margin after direct costs. If mature-year delivery still carries 20% direct costs, any discount on custom research hits owner draw first.
Track fee per project by scope
Price extra states as added work
Charge separately for incentive support
Review hours before discounting
Delivery Capacity And Analyst Leverage
Delivery Capacity And Analyst Leverage
When the team completes more projects without hurting research quality, owner take-home rises because each analyst spreads payroll across more billed work. In this model, staffing grows from 2 to 6 geospatial analysts and 1 to 3 senior data scientists, while billable hours per active customer rise from 45 to 55 per month, a 22% lift in hours per client.
The risk is timing. Standardized research, templates, and review steps protect margin, but the source model shows payroll rising from $715k to $1,495M; if hiring runs ahead of signed demand, that cost swing can wipe out profit and shrink owner draws. Track projects per analyst, billable hours, and rework together.
Scale Capacity Without Breaking Margin
Measure projects completed per analyst, billable hours per active customer, and rework time. Use templates for market scans, site scoring, and incentive analysis so senior staff spend time on exceptions, not repeat work. If hours per client stay near 45-55 and review quality holds, you can grow revenue faster than headcount.
Hire after signed demand.
Standardize every review step.
Watch payroll per billed hour.
One clean rule: do not add analysts until the next projects are already sold.
Qualified Client Pipeline
Qualified Client Pipeline
Owner income here depends on qualified demand, not raw traffic. This model assumes $120,000 in first-year marketing, rising to $220,000, with CAC spanning $15,000 to $125,000. If leads are operators, developers, brokers, economic development groups, and corporate expansion teams, proposals convert faster and cash turns sooner. If not, marketing can burn cash before signed projects arrive.
Here’s the quick math: more qualified leads lift proposal volume, then higher proposal conversion improves revenue timing and owner draw. The key inputs are lead source mix, proposal count, close rate, and sales cycle length. One clean rule: better-fit leads beat more leads.
Track Lead Quality, Not Just Volume
Track leads by source, then measure how many become proposals and signed projects. That tells you which channels support income, instead of just adding busy work. If broad marketing is pushing spend toward the $220,000 level without more signed work, trim it and push on referral-heavy sources that fit site selection.
Test each channel against proposal conversion, not clicks. Budget should follow sources that bring operator, developer, broker, and expansion-team leads with real project intent. That protects gross margin, keeps fixed overhead from outrunning cash, and helps the owner pay themselves from collected fees, not hope.
Close Rate And Sales Cycle
Close Rate and Sales Cycle
When proposals take a long time to close, the pipeline can look full while cash stays stuck. For this model, the key inputs are proposal count, close rate, and average sales cycle — the days from proposal to signed work. A lower close rate means fewer projects booked, less annual revenue, and less owner cash available for pay or draws.
The timing risk is real here: the model’s month 21 breakeven shows how slow wins can force the owner to wait on distributions. Until repeat referrals and signed retainers are steady, cash reserves matter more than raw pipeline size.
Track Win Rate and Days to Close
Measure proposals sent, signed deals, and days to close every month. Here’s the quick math: expected projects = proposals × close rate. If close time stretches, forecast cash on the signed date, not the proposal date, so you do not overpay the owner or staff before money lands.
Split win rate by client type.
Track close days by proposal size.
Set follow-up dates on every bid.
Keep reserves for slow closes.
Direct Costs And Overhead
Direct Costs and Overhead
Direct costs are the spend tied to each site search: data, cloud, travel, and referral commissions. In year one, they run at 27% of revenue; in mature years, 20%. That means every $100k of revenue leaves only $73k or $80k before fixed overhead and the owner’s pay.
Fixed overhead is $24k per month for office, insurance, legal, accounting, GIS software, CRM, and telecom. For example, at $100k monthly revenue, year-one direct costs are $27k and overhead is $24k, so $49k remains for everything else. More travel-heavy and research-heavy work pushes this line up fast.
Track Cost Per Project
Measure direct cost as a share of revenue and by project. Separate data, cloud, travel, and referral commissions so you can see which job type is dragging margin.
Track direct cost percentage monthly.
Break travel out by project.
Watch data and cloud usage.
Price custom research higher.
Keep scope tight, plan travel early, and match the data stack to the client need. Do not cut research quality too far, because weaker analysis can hurt referrals and repeat work, and that can reduce owner income more than the savings help.
Recurring Advisory Revenue
Recurring Advisory Revenue
Recurring advisory revenue means monthly or quarterly retainers for ongoing work like portfolio expansion planning, market monitoring, labor-market updates, and incentive advisory. For a site selection firm, this can smooth owner pay because it reduces reliance on one-off project timing and helps cash arrive in smaller, steadier chunks. It also makes forecasting cleaner, since repeat clients are easier to plan around.
The key input is retainer count Ă— monthly fee Ă— retention months. The model does not isolate retainer revenue, so it should sit as a separate line in the calculator. The catch is simple: not every project becomes a retainer, especially when a client expands rarely, so this revenue is less certain than project fees.
Track Retained Clients, Not Just New Leads
Measure how many project clients convert to retainers, what they pay, and how long they stay. Keep one clean metric: retainer revenue as a share of total revenue. That tells you how much of owner income is protected from project gaps. Repeat clients can also lower effective CAC, since you spend less to win the next dollar from the same account.
Retainer count
Monthly fee
Retention months
Renewal rate
Hours included
Client expansion cadence
Test whether ongoing advisory work still covers labor and overhead. With fixed overhead at $24k per month and mature direct costs near 20%, even small retainers can protect cash flow if delivery stays light. If a retainer needs too many analyst hours, it starts to act like a project, and owner draw gets squeezed.
