Marketing agencies 01
2,300
Advertising agency locations
The possible opening
Keep client approvals and deadlines in one place.
The catch: Asana already advertises agency workflows. We’d need a reason to switch. [2]
GTM strategy / B2B software / Interactive case study
Who should we
sell to next?
Three promising customer groups. One small launch budget. Where would you start?
The setup is hypothetical. The market counts are real. I built this independent case study to explore a launch decision. There’s no company sales data or completed customer test behind it.
01 / Set the scene
A useful product.
Too many directions.
Imagine a software company that helps teams manage client projects. It already has tasks, timelines, client approvals, workload planning, and status dashboards.
It can’t do everything. Billing, time tracking, and IT support tickets aren’t built yet. I’d look for customers it can help with the product it has today.
Scope: U.S. business locations with 10 through 49 employees. The industry categories below are rough matches for each customer group.
02 / Size up the options
Bigger isn’t the whole story.
Consulting has the largest location count here. Agencies look like a closer match for the assumed product.
Consulting firms 02
7,395
Management consulting locations
The possible opening
See project progress and team workload across clients.
The catch: Teamwork also connects time and billing. Our assumed product doesn’t. [3]
IT service companies 03
6,667
Computer systems design locations
The possible opening
Coordinate client implementation projects.
The catch: Jira Service Management covers requests and incidents. Our product doesn’t replace that. [4]
Source: 2023 U.S. Census County Business Patterns. These are employer locations, not unique companies, qualified leads, or software buyers. [1]
03 / Make the tradeoff
What matters most to you?
Change the priorities. Then challenge the assumptions below. Higher scores mean a stronger match to your choices, not a higher chance of success.
More locations in the selected category.
More of the proposed needs covered today.
Higher assumed monthly subscription revenue.
Weights automatically scale to 100%. Set all three to zero to clear the ranking.
Your scenario Score / 100
First segment to test
Marketing agencies
Show the assumptions. Change my mind.
These product-fit scores and prices are case assumptions. Vendor pages informed the proposed needs, but don’t prove what customers need or will pay.
| Customer group | Needs covered, out of 5 | Monthly revenue per account |
|---|---|---|
| Marketing agencies | $ | |
| Consulting firms | $ | |
| IT service companies | $ |
Use whole numbers from 0 to 5 for coverage and $0 to $10,000 for monthly value. Revenue excludes acquisition costs, service costs, and churn.
Why 5, 3, and 2?
- Agencies, 5/5: timelines, approvals, workload, client visibility, status reporting.
- Consulting, 3/5: timelines, workload, and client visibility are covered. Billable time and invoicing aren’t.
- IT, 2/5: project tasks and client visibility are covered. Ticket queues, incident response, and service-level rules aren’t.
Each proposed need counts equally. That’s a simplifying choice, not a customer survey. A different buyer or workflow could change the list entirely.
My read: test agencies first, but don’t get attached.
The default lead is only 3.6 points. Drop agency coverage from five needs to four and consulting moves ahead. This recommendation rests on a product-fit hypothesis we haven’t tested.
04 / Turn it into a launch test
Small test. Clear next step.
This plan follows my original agency hypothesis. Changing the ranking above doesn’t mean we’ve validated a different launch.
The first customer I’d look for
A U.S. advertising agency with 10 through 49 employees at a location, several active clients, and approvals that keep holding up delivery.
- Likely buyer
- Head of operations. Confirm in interviews.
- Buying trigger
- Missed approvals are pushing deadlines back.
- The message I’d test
- “Less chasing approvals. More getting work out the door.”
- How I’d reach them
- A carefully qualified account list, direct outreach, and agency operator communities where participation is welcome.
These are targeting hypotheses. Check the parent company, buying authority, existing tools, and willingness to switch before calling an account qualified.
What I’d do first
- Listen. Interview 10 agency operators and 5 consulting operators. Ask about the last delayed project and what they already tried.
- Show the workflow. Offer a focused demo using a real approval task, not a long feature tour.
- Run a 30-day pilot. Track real client invitations, completed approvals, time to first value, and hands-on onboarding effort.
- Check the economics. Count paid accounts, compare approval times with each team’s baseline, and review acquisition and support costs.
A proposed gate: at least 2 paying accounts and at least half of pilot accounts activated. Activated means they invite a client, add a real deliverable, and finish an approval within 7 days. Review payment after the full conversion window. These are directional test targets, not proof of repeatable demand.
05 / Pressure-test the plan
What would 100 accounts get us?
Try the launch math. Every rate below is an assumption, not a campaign result.
Expected values may include fractional customers. Annualized revenue means monthly revenue × 12, not first-year cash collected. This simple scenario doesn’t account for timing, churn, or costs.
The decision behind the dashboard
The next move is learning.
I’d use the score to choose where to investigate first. If agencies won’t switch or won’t pay, I’d test consulting next. A tidy ranking is useful only if it leads to a better question.
Where the numbers come from
Research reviewed October 14, 2026. Historical counts and scenario assumptions stay separate.
How I counted and scored the segments
I used the 2023 national Census file and kept the all-legal-forms row for each industry. I added the 10 to 19 and 20 to 49 employee location counts.
| Industry code | 10 to 19 | 20 to 49 | Total |
|---|---|---|---|
| 541810 · Advertising agencies | 1,300 | 1,000 | 2,300 |
| 541611 · Management consulting | 4,311 | 3,084 | 7,395 |
| 541512 · Systems design | 3,789 | 2,878 | 6,667 |
Size score = segment count ÷ largest count × 100. Fit score = needs covered ÷ 5 × 100. Value score = assumed account value ÷ largest assumed value × 100. The total is the weighted average of those three scores.
Default weights: 20% size, 60% fit, 20% value. Relative normalization means the scores apply only to these three choices. Zero prices give zero value scores; zero weights give no ranking. Scores within 0.05 points are shown as a tie.
What this analysis can’t tell us
Locations aren’t companies or buyers. The size range describes each location, not the whole company. Industry categories miss parts of each segment, and businesses without paid employees are excluded. Counts describe 2023, not today.
Competitor pages show advertised workflows. They don’t prove widespread demand, customer pain, market share, or willingness to pay. Product coverage and account value need validation. This case has no observed sales, acquisition cost, retention, or profitability data.
- Census: 2023 national CBP data (ZIP). Observed location counts. Definitions and coverage.
- Asana: agency workflows. Public product and competitor context.
- Teamwork: consulting workflows. Public product and competitor context.
- Atlassian: service management workflows. Public product and competitor context.