A data & ai layer for coaching and consulting ceos
You’re making $30M/year decisions on $300 reports.
Simplified Dashboards builds and operates the complete source-to-cash data layer — attribution, commissions, rep performance, and AI that acts on all of it — for coaching and consulting companies doing $10M–$50M/year. One team. Full ownership.
Current intake Q2 2026 · 2 of 3 slots open
§ 01 · The recognition test
- No. 01
Your ad agency says CAC is $800. Your finance team says it's $2,200.
Both have spreadsheets that prove it. Neither number includes refunds, chargebacks, and commissions actually paid. You don't know who is right. You make the call anyway.
- No. 02
You have forty closers. You know your top three. The rest is gut feel.
The data to rank them exists — it is in GHL, in Stripe, in your CRM. Nobody has joined the three. You manage on impressions rather than evidence.
- No. 03
Payroll closes on the 20th. Reps don't know what they earned until the month is half gone.
The numbers are right, usually. Your ops lead spends four days every cycle reconciling spreadsheets to make sure. Every month, someone disputes a number that was correct.
- No. 04
You spend $500K a month on paid acquisition. You cannot tell which channel is profitable after refunds.
You have GA4. You have GHL. You have attribution reports from two agencies. Each says something different. You spread the budget and hope.
If you recognized yourself in two or more — you are not behind. You have built fast enough to outgrow the system underneath. That is what we fix.
§ 02 · The layer that sees
A single trusted view of every number that matters.
We connect every source your business runs on — CRM, payment processor, ad platforms, commission rules — and build a view that updates daily, automatically. No exports. No reconciliation. No arguments about which number is right.
What it delivers
- Close rate by closer, by offer, by channel — after refunds
- Commission reports reps trust, delivered on the 1st
- CAC across every channel, net of refunds and fees
- Rep performance ranked on verified numbers, not manager impressions
- A single source of truth CFO, ops, and closers read at the same time
§ 03 · The layer that acts
Production AI agents that operate on the data we built.
Inbound and outbound voice agents that do not simply talk. They know your pipeline state, your rep availability, and your conversion benchmarks. They route, follow up, and escalate on real numbers.
What it does
- Inbound lead qualification and routing, 24/7
- Outbound follow-up that knows deal state before dialing
- No-show recovery that actually closes the loop
- Escalation driven by real close-rate data
- Agents that improve as the data underneath improves
§ 04 · The pipes
One query. Three systems. The number you can act on.
Every system generates numbers. None of them agree. We engineer the join logic that resolves them into one trusted view — source-to-cash, daily refresh, and we own the maintenance.
SELECT leads.source,
leads.setter,
contacts.closer,
payments.cash
FROM ghl_leads leads
JOIN close_contacts contacts ON leads.email = contacts.email
JOIN stripe_payments payments ON contacts.customer_id = payments.customer_id
WHERE payments.status = 'succeeded';These are not separate services. They are one operating system. The agent is only as good as the data it operates on.
§ 05 · The dashboard
Every number that matters.
In one view that updates daily.
Your closers, your channels, your cash collected — reconciled and current. This is what your morning briefing reads like when the data layer is built right.
Leads
3,659
+12.4% · wk/wk
Calls booked
278
+8.1% · wk/wk
Cash collected
$75,071
+22.6% · wk/wk
Revenue / lead
$20.51
+3.2% · wk/wk
Cash collected · last 12 weeks
$k
Pipeline · quarter to date
- Lead captured3,659
- Call booked1,420
- Call started982
- Showed up711
- Contract signed298
- Cash collected278
§ 06 · The stack
We connect every system your business runs on. If you have it, we speak it.
CRM
- GoHighLevel
- Close
- HubSpot
- Keap
- Kajabi
Payment
- Stripe
- GoCardless
Paid media
- Meta Ads
- Google Ads
- YouTube Ads
Analytics
- GA4
- Looker Studio
Automation
- Zapier
- n8n
Schedule
- Calendly
Communication
- Slack
Not on the list? We have almost certainly connected to it. Bring your stack — we will make it agree with itself.
§ 07 · The process
Four stages. One outcome:
a data layer you trust at 8am Monday.
Diagnostic call
Thirty minutes. We read your current data setup — what you have, what is breaking, and what decisions you are making blind. No pitch. No deck. A structured conversation that ends with a clear picture of what we would build, and what it would cost.
Architecture + build
We map your full source-to-cash data model, connect your systems, validate historical data, and build the core reporting layer. Commission rules. Attribution logic. Rep performance framework. Fixed scope, agreed before we start. No surprises.
Handover + retainer
We do not hand over a document and disappear. We train your team on what they are reading, then begin the retainer — ongoing data operations, model maintenance, new dashboards as your business changes, and commission processing every cycle.
Ongoing operations
We handle every change — new offer, new rep structure, new channel, new acquisition platform. You make the decisions. We keep the data clean, current, and trustworthy.
Most clients see first-month ROI before the build is complete. Commission clarity alone recovers more than the retainer — in overpayments reclassified and disputes resolved.
§ 08 · The results
Peak monthly revenue for a coaching company we have operated with for over five years.
Client retention. Every account we have opened is still active.
Commission cycle at a $30M/year coaching company, before us and after.
Combined revenue generated by the companies on our client roster.
Duplicate leads found in one client's pipeline and eliminated in two weeks.
Commission disputes in the twelve months after we rebuilt the payroll system.
Figures anonymized where contractual. References available on request.
Engagements · selected
Index of case studies→Work that speaks.
- 01
It took 20 days to calculate payroll. Reps didn't know what they earned until half the month was gone.
A $30M/year coaching company. Fifty reps. A commission system running on five spreadsheets and three people who all had to agree.
Commission cycle, days
20 → 1
Read → - 02
1 in 3 leads was a duplicate. Nobody knew.
When a third of your pipeline is phantom volume, your close rate is a lie. How we found it — and what changed after.
Phantom pipeline
33%
Read → - 03
50 sales reps. 50 Google Sheets. Zero idea who was winning.
From manager impressions to a live rep leaderboard in six days. Three underperformers identified and performance-managed inside a month.
Reps ranked to live
50 → 6d
Read →
On the record
“Time and again it has been proven that you guys have the most accurate data, that we can trust.”
— VP, Operations·Coaches100 — $15M/yr coaching company
“Now that we have better insight into next-day appointments, I'm running 2× daily promos. We ship marketing decisions weekly, not monthly.”
— Marketing Director·Coaches100
“Salman built us a unified data pipeline pointing into beautiful dashboards. The kind of partner who solves problems we didn't know existed.”
— John Coburn·Founder, SupportED
From the founder
Every client I have ever built for is still with me.
Fig. 03
Salman
Founder, Simplified Dashboards
Seven years in the engine room
I'm Salman. I've spent seven years building the data infrastructure that coaching and consulting companies run on.
I have sat in executive meetings where the CEO, the CFO, and the head of marketing all read different numbers for the same month — and all three were technically correct, because nobody had built the layer that unified them.
I have watched sales coaches wait three weeks to find out their commissions, because the CEO and finance could not agree on attribution, and nobody had built the system that settled it automatically.
I have seen $10M/month operators making decisions on instinct — not because they did not value data, but because the data was scattered across seven platforms and no one had time to reconcile it before the call.
I built Simplified Dashboards to solve that.
We helped one coaching company scale from $150K to $15M a month in monthly revenue. I was there from the beginning. I am still there now, five years later — because once the data layer is built and trusted, you do not replace the team that built it. You keep building.
Every client we have ever taken on is still with us. That is not a marketing line. It is the only proof I need.
If you run a $10M–$50M/year coaching or consulting business and you do not have a dedicated data team — this is for you.
— Salman · Founder
§ 09 · The investment
One offer. No tiers.
The number is on the page.
We take on 2–3 clients per quarter. Every engagement is full-service — we build, we operate, we own the result. There is one offer.
I · The build
Fixed-scope build, 2–4 months. Full data architecture, source-to-cash pipeline, commission system, rep performance framework, delivery of the core reporting layer. Scope is agreed before we begin. No surprises.
$35K – $60K
Fixed scope
II · Monthly retainer
Ongoing operations once the build is complete. Daily pipeline maintenance, monthly commission processing, new dashboards as the business changes, and model updates as you add offers, channels, or reps. Month-to-month after the initial three-month term.
$12K – $18K
per month
III · Year-one investment
Total first-year investment, build plus 8–10 months of retainer. For context: on $200K/month of paid acquisition, a 5% gain in attribution accuracy pays this back in under 60 days.
$180K – $250K
total, first year
For context · the real comparison
You’re not comparing us to a tool. You’re comparing us to the cost of not having this built.
| Line item | What it is | Annual |
|---|---|---|
| Your time | CEO hours on data reconciliation. ~200 hrs/yr × $1,000/hr opportunity value. | $200K / yr lost · recurring |
| Wrong attribution | Misallocated paid spend. At $500K/month ad spend, 15% wasted on unprofitable channels after refunds. | $900K / yr lost · recurring |
| In-house build | Senior data engineer + analyst + overhead. Hire, onboard, architect, ship. | ~$350K / yr live · month 7 |
| Simplified Dashboards | Full team, already operational, with the infrastructure already built for your business model. | $180K – $250K / yr live · week 2 |
| The first two rows compound every year you delay. The third and fourth are where the comparison actually lives. | ||
If the investment makes sense for where you are building, let us talk.
Common questions
Direct answers. No hedging.
If your question is not here, the call is the answer.
- Q.Do we need our data organized before we engage you?
- A.No. Disorganized data is the problem we are hired to solve. We have never walked into a clean environment. We have walked into GHL instances with 30% duplicate leads, Stripe accounts that do not reconcile with the CRM, commission spreadsheets that four people are manually editing, and SQL databases nobody has touched since the person who built them left. That is normal. We do the archeology.
- Q.How long before we see the numbers?
- A.Typically the first validated dashboard is live within 3–4 weeks of kickoff. Commission and rep performance visibility usually follows in weeks 5–8, depending on pay structure. Clients typically see their first actionable insight — a number they can make a decision on — within the first two weeks.
- Q.We already have a BI tool or a dashboard someone built in-house. Does that change anything?
- A.We have inherited every tool imaginable — Looker Studio, Tableau, Power BI, custom Google Sheets dashboards, in-house SQL queries nobody can explain. We assess what you have, keep what works, replace what does not, and build the layer underneath that makes all of it trustworthy. We do not delete and start over. We build on what makes sense and fix what does not.
- Q.Can we start with just one dashboard or a smaller scope?
- A.No. The minimum engagement is the build — because a dashboard without the data architecture underneath it is decoration. Building the pipeline correctly once is what makes everything that comes after reliable. A half-build is worse than nothing: it creates false confidence in bad data. We start with the foundation.
- Q.Do we need to assign someone to manage this?
- A.No. A point of contact for the first 60 days is helpful — someone who knows the business, the commission rules, the offer structure. After that, the system runs itself and we run it. Most clients check the dashboard in the morning and do not think about the infrastructure at all. That is the goal.
- Q.What is the difference between what you do and what a freelance data analyst does?
- A.A freelance analyst builds what you describe and hands it over. You own the maintenance, the updates, the breakages. We are the full function — we build, we maintain, we improve, and when your business changes, we update the model before you ask. The difference is accountability. We own the outcome, not just the deliverable.
- Q.You mentioned AI voice agents — is that a separate service?
- A.No. It is the same engagement. The data layer is the foundation; the agents operate on it. We do not sell the agents separately because agents without clean, structured data are unreliable. We will not build an agent on a data model we do not own and trust. If you are on the retainer, the agents are part of the roadmap.
- Q.How do you handle data privacy and client confidentiality?
- A.We sign NDAs at the start of every engagement. We operate on your infrastructure — not ours. Your data never lives in a shared environment. Access is scoped, documented, and revocable. We handle revenue, commission, and customer data for companies processing tens of millions of dollars. Confidentiality is not a checkbox for us.
§ 10 · The call
We take 2–3 clients a quarter.
If the timing is right —
No pitch deck. No discovery form. A structured 30 minutes — you talk, we listen, and we tell you honestly whether we can help.
Current intake Q2 2026 · 2 of 3 slots open