Masterclass Funnel Report

5,257 rows, 35 columns, 18 days. Paid ads bring people to a free webinar, a salesperson calls them, and we sell $4,000 to $7,000 coaching. So far $225,016 is recorded against it.

A column only fills if the person got that far. So counting blanks draws the funnel.

Nobody had to tell us what this business is. The column names did.

Q10. How long following Abu Lahya

We ask how long they have followed one named person. So we are a personal brand, and we believe warmth towards him predicts a sale. Otherwise we would not spend a survey question on it.

Capital available in next 30 days

We check whether the audience can actually pay before we pitch them. We only ask that because what we sell is expensive.

Program_Type
Course Only (4k) · Full Program (7k)

And here is how expensive. Our price list is sitting in a dropdown: $4,000 and $7,000.

Close_Lead_Status
22 values, one for each way a person can drop out

We close on the phone, not through a checkout. And we lose people often enough that every way of losing them has earned its own label: 212 could not afford it, 91 were disqualified by the closer, 33 never turned up, 29 wanted to think about it, 11 were afraid, 11 did not share a language with us, 8 had to ask a parent, and one had to ask their partner.

Q12 / Q13
free text, full of halal · deen · akhira · barakah

The same words keep coming back in what they write. Our audience is Muslim, and we frame the income as religiously permissible.

UTM Campaign
160 values. A UTM is just a tag stuck on a link so we can tell which ad sent someone to us.

We name every ad by when it launched, who made it, and what angle it used. So 14.05 | Imran | Dumbest Thing means it went live on 14 May, Imran made it, and the angle was the one we call Dumbest Thing. Read all 160 names and you have our whole advertising plan without ever opening the ad account.

Four things this file cannot tell you

The question	Why not
What did it cost?	No ad spend anywhere in the file. Cost per lead, cost per sale, return on ad spend. None of it. Channels can be ranked by what they return, never by what they cost.
Did they show up to the call?	No call events, only a flag for the stage someone sits in right now. We can see who booked a call, but never who actually turned up, so we cannot say what share of calls become sales.
When did a deal close?	There is no close date. So no time-to-sale, and no fair comparison between one cohort and the next.
Did they watch the webinar?	No attendance data. The webinar is the product, which makes this the biggest blind spot here.

▶ All 35 columns, with fill rates the full dictionary

Fill rate is the share of the 5,257 raw rows where a column has any value. Distinct counts unique non-empty values. That is the quickest way to tell a category from free text, and to catch a field like Q6 that is empty in every row.

5,107 people signed up and 62 bought. We lose 85% of them before a salesperson is ever involved, and then 85% again after the call is booked.

Every stage, and what it costs us to get through it

What one sale actually takes

There is a stage in the middle we cannot see

Waiting for a call	335
In follow up	17
Already closed	5
The other 11 stages	0

It says No for 57 of our 62 customers, who all had a call.
So it marks where someone stands, not what they did.
We count booked as waiting or bought. That is 414, and it is a floor.
Whether a call was actually held is recorded nowhere.
Which means the 85% lost after booking is no shows and lost pitches added together. We cannot separate them, and they need opposite fixes.

Both ends leak, and only one of them is a sales problem

Where we lose them	What it means
4,326 people, before any salesperson signed up, never reached the CRM	Eight and a half out of every ten people who register go no further. Nobody calls them, nobody disqualifies them, they simply never arrive. That is a marketing and qualification problem, and it is the single biggest number on this page.
367 people, inside the CRM reached a salesperson, never booked	Just under half of everyone who reaches the sales team never gets a call in the diary. This is where the triage reasons live, and the largest of them by far is that they cannot afford it.
352 people, after booking booked a call, never bought	The same 85% loss as the top of the funnel, but far more expensive, because a person has spent time on each one. Without a record of who actually turned up, we cannot say how much of this is no shows and how much is the pitch.

▶ How these numbers were built counting people, not rows

5,257 rows became 5,107 people

We matched on phone number, falling back to email, and kept the earliest sign up as the person. 135 rows were the same people twice. Where a duplicate carried an outcome we took the best one, so no sale or payment is lost in the merge.

$9,588 of cash was counted twice

Six of those duplicate pairs had a payment recorded on both rows. Add the raw column up and you get $225,016. Count people instead and it is $215,428. The difference is the same money, banked once.

16 rows removed

Eleven were our own staff on an @imaccelerator.com address, five were obvious test entries. None of them are customers and all of them would have flattered the rates.

The average person Instagram sends us has paid us $32.74. From Facebook, $5.55. From our own email list, $123.82, and that list is the smallest thing we run.

What one person from each channel has paid us

Facebook and Instagram are not one thing, and we should stop paying for them as if they were

	Instagram	Facebook	Both
People we paid to bring in	2,750	1,225	3,975
Money those people paid us	$90,037	$6,801	$96,838
Paid per personthe money divided by the people	$32.74	$5.55	$24.36
Share of the people1,225 of 3,975	69%	31%	100%
Share of the money$6,801 of $96,838	93%	7%	100%

5.9xwhat Instagram pays back per person, against Facebook

1 in 602Facebook Mobile Reels people who became a customer

$24.36the Meta average, true of neither platform

The same question, but by where the ad was shown

Two things to hold on to before acting on any of this

The catch	What it does to the ranking
There is no spend in this file	Everything above is what a channel gave back, never what it cost to get. If Facebook people are a tenth of the price of Instagram people, the ranking flips. We do not know, because nobody put the ad bill in the export. It is the single most valuable thing we could add.
The top row is not really a channel	No tracking at all returns $167 a person, more than anything else here. But 73% of them were already in our CRM before they signed up. Ads did not bring these people, we already had them. Counting them as a channel would credit the ad account for work the sales list did.

One row looks wrong, and it is telling us something

Still labelled Potential	$13,500
Left as a Deposit	$4,545
Bank Issues	$1,008
Asked for a refund	$1,000

Instagram organic shows no sales but $1,000 collected. That is one person who paid a deposit on the $7,000 programme and then asked for it back.
Across everything, 15 people have paid us $20,052 without ever being marked as customers.
That is 9% of all the cash we hold, sitting against people we do not count as having bought.
Two of them have paid $13,500 between them and are still filed under Potential. Either they are customers or that money is not ours yet, and nobody has decided which.

Our IT and tech ads brought 392 people and one sale. Our money and status ads brought four times more per person. The creative that fills the room is not the creative that fills the diary.

What angle the ad took

Who we called out in the ad

How the ad was made

Who made it

Seif, all of it webinar 3	278
Not named in the ad title	108
Lahya, the newest batch	22

These 408 people are held out of the chart above, not counted against anyone.
They signed up for the webinar on 24 May, and this file was pulled on the 25th.
Seif has no sales because Seif has had no time, and every one of his people is in that group.
Lahya is the opposite case. 312 people who have had their webinar, and one payment of $134. That one is real.

How much of this to believe

The problem	What it means for the ranking
We are ranking on very few sales	The whole file contains 62 customers. Split across angles, formats and audiences, most groups hold one or two. One extra sale moves a row several places. Read the zeros as real and the order of the middle as rough.
The names are not written to be read	There are four different naming conventions in use, and one launch tagged 16.06 in a May campaign, which puts 166 people in the wrong month. We parse 98.5% of them, and the rest is guesswork that one agreed naming rule would remove entirely.

Four things we are running that have never produced a sale

IT and tech call outs	392 people, 1 sale
Email screenshot ads	235 people, none
Video ads	122 people, none
Scam awareness hooks	117 people, none

Between them that is 866 people and one sale.
They are not failing to attract anyone. They attract plenty, and almost nobody buys.
The IT and tech call out is the clearest case: 392 people, more than almost any other angle, and $9.27 back from each of them.
We cannot say what these cost us, only that they returned close to nothing. Spend would settle it in an afternoon.

Four out of five people who told us have less than $1,000 they could put their hands on. The one in five who have more buy at 4.6 times the rate.

We ask everyone how much money they could put together in 30 days

The same people, split at a thousand dollars

	Has $1,000 or more	Has less than that	Everyone who answered
People	703	2,880	3,583
How many bought	26	23	49
Share of everyone703 and 2,880 of 3,583	20%	80%	100%
How often they buybought divided by people	3.70%	0.80%	1.37%

4.6xmore likely to buy if they have the money to hand

26of the 49 sales came from that one in five

80%of the people we bring in cannot afford this

How long they had been following him before they signed up

What they were doing when they signed up

What they do for a living

How much of this to believe

The problem	What it means
Not everyone answered	Only 3,583 of our 5,107 people gave us a capital figure. The survey was shortened partway through the campaign and dropped entirely for the last webinar, so these cuts describe the people who answered, not everybody.
They are telling us, not proving it	Every number on this page is self reported on a signup form, before anyone spoke to them. People understate savings, overstate intent, and click through questions to reach the webinar. Treat it as a strong signal, not a bank statement.

Our scoring tool ranks buyers better than chance. So does one question on the signup form, slightly better in fact, and it takes nobody any effort to read.

How good is a ranking, really

	Our lead score	The capital question	A coin flip
Picking who will buyout of any buyer and non buyer, how often it puts the buyer higher	68%	70%	50%
Picking who will book a call	59%		50%

68%the score is genuinely better than guessing

70%and one survey question is a shade better still

59%at picking who books a call it is nearly a coin flip

Split everyone with a score into ten equal groups

Score says yes, wallet says no

Grade D does not mean bad

Grade B	$67.29 each
Grade D	$43.80 each
Grade C	$18.04 each
Grade A	5 people, none bought

1,457 of the 1,568 D grades never took a survey. D is not a judgement, it is a blank.
D returns $43.80 a person. C, the grade above it, returns $18.04. Two and a half times less.
Grade A is five people and no sales. It is not a tier, it is a rounding error.
Anyone deprioritising D as low quality is skipping the group that outperforms the grade above it.

How much of this to believe

The problem	What it means
Only 3,539 people have a score at all	A score only exists where a survey was answered. Everything on this page describes the people who filled the form in, and the grade comparison is the one cut that includes everyone.
We are ranking on 62 sales	Each of the ten groups holds around 350 people and 0 to 13 sales. The top and bottom of the ranking are solid. The order of the middle is noise, and the empty fifth group is not a hole in the model, it is a small number.

781 people reached a salesperson. A third of them sit in a triage bucket, and between them those 272 people have never bought anything.

Where everyone in the CRM currently stands

Triage is the biggest thing in the pipeline and it has produced nothing

Could not afford it	186
Some other reason	55
Wrong time	22
We did not share a language	9

272 people, 138 of whom booked a call. Not one has bought.
Money is the reason for 186 of them, more than two thirds.
Of those 186, 124 told us on the form how much they could raise. Only 14 had a thousand dollars.
So we already knew. The answer was sitting on the signup form before anyone picked up the phone.

The gap between booking a call and having one

Unconfirmed	104 people, 1 sale
No show	29 people, none
Cancelled	27 people, none
Rescheduled	6 people, 1 sale

104 people are sitting on unconfirmed appointments. 89 of them booked. One bought.
Another 62 did not turn up, cancelled, or moved it.
That is 166 people, over a fifth of the whole CRM, stuck between saying yes to a call and actually being on one.

Almost every sale we have made is filed under Potential

People labelled Potential	106
How many of them bought	46
Cash sitting in that label	$162,718

46 of our 62 customers are still labelled Potential.
That single label holds $162,718, three quarters of everything we have collected.
Nobody updates the status after a sale. Which means the CRM cannot tell you who your customers are without joining it to the payment field.

How much of this to believe

The problem	What it means
These are positions, not histories	Every label here says where somebody stands today. Someone triaged for money in week one and sold in week three shows only the sale. So these counts understate how many people passed through each stage.
Nothing records what was said	We can see that 186 people were triaged for money and that 104 appointments are unconfirmed. We cannot see whether anyone chased them, when, or how often. Call activity would turn this page from a description into a diagnosis.

We have sold $338,000 of coaching. $195,376 of it has actually arrived. The other $142,624 is the largest number in this report and nothing here was built to watch it.

Sold, arrived, still owed

The cheaper product is the one that does not get paid

	Course Only, $4,000	Full Program, $7,000	Both
Deals closed	32	30	62
Value of those deals	$128,000	$210,000	$338,000
Money that arrived	$61,557	$133,818	$195,376
Share of it collectedarrived divided by sold	48%	64%	58%
Still owed to us	$66,443	$76,182	$142,624
Sold on a payment planof the deals closed	26 of 32	16 of 30	42 of 62

How the money actually arrives

A handful of people carry the quarter

Top 5 payers	16% of all cash
Top 10 payers	32%
Top 20 payers	57%
Everyone else, 57 people	43%

Twenty people out of 77 account for more than half of everything collected.
The biggest single payment is $7,000. The middle one is $2,000.
Normal for high ticket, and worth saying out loud: two refunds at the top end move the whole number. Three people have already asked, for $8,135.

What we cannot see about our own money

The gap	Why it matters
There is no currency field	Every figure is labelled USD, but our people are in the UK, Canada and across Europe. 23 of the 77 payments are not round numbers, which is what exchange rates and card fees look like. Every per country figure in this report is therefore approximate.
There is no payment schedule	We know $142,624 is owed. We do not know when any of it is due, how many instalments are left, or whether a single payment has already failed. The number cannot be aged, chased, or forecast.
Fifteen people have paid and are not customers	$20,052 sits against people nobody has marked as having bought. Deposits, part payments, and two people who paid $13,500 between them and are still labelled Potential. Until someone decides what counts as won, the revenue figure is a choice, not a fact.

Everything in this report came out of one export. Four missing pieces would answer more than all eight pages put together, and none of them need new tools.

What is missing, in the order it would help

What we would ask for	What it would let us finally answer
Ad spend, by campaign and day	Every number about channels and creative is what came back, never what it cost. With spend, the whole of pages 3 and 4 turns from a ranking into a budget decision. Instagram returning six times Facebook means nothing until we know Facebook was not six times cheaper.
Call activity from the CRM	We can see that 104 appointments are unconfirmed and 272 people sit in triage. We cannot see whether anyone rang them, when, or how many times. This turns page 7 from a description into a diagnosis, and it is the fix for the 85% we lose after a call is booked.
A date on every sale	There is no close date anywhere in the file. Without it we cannot say how long a sale takes, and we cannot compare one webinar against the next fairly. It is why Seif’s 278 people had to be held out of page 4 entirely.
Webinar attendance	The webinar is the product and nothing records who watched it, for how long, or who came back to the replay. Every page here treats it as a black box between signing up and being called.

Things we could fix ourselves, without asking anyone

Customers still filed as Potential	46 of 62
People who paid but are not customers	15, $20,052
Ad names in the wrong month	166
Names too short to use	1,698
People who told us nothing	1,457
Under eighteen	107

Update the status when someone buys. Right now the CRM cannot tell us who our customers are without joining it to the payment field.
Decide what won means. Fifteen people have paid us and are not counted as anything.
Agree one way to name an ad. Four conventions are in use and one typo put 166 people in June.
Keep the money question on every version of the form. It predicts buying better than our own scoring tool, and 1,457 people were never asked it.
Add an age gate. 107 people told us they are under eighteen, 17 of them under sixteen, and we are advertising a $7,000 product at them.

What the data already says we should do

People who cannot afford this	80%
Ads with no sales between them	866 people
Stuck between booking and calling	166 people
Money owed on sales already made	$142,624

Qualify on money earlier. Four in five people we pay for cannot buy this, and they tell us so on the form before anyone speaks to them.
Turn off what has never worked. Four things are running that have produced one sale between 866 people.
Confirm the appointments. A fifth of the CRM is waiting on a call that may never happen, and that group has produced two sales.
Chase the $142,624. It is already sold. It is the largest number in this report and no page here was built to watch it.

What we would still not know

Even with all of the above	Why
Whether any of this is causal	People with money buy more. That does not mean finding richer people would sell more, and nothing in an export can tell us. It needs a test, run deliberately, on the next cohort.
Whether 62 sales is enough to trust	Most of the groups on these pages hold one or two sales. The large gaps are real. The order of anything in the middle is noise, and more weeks of data is the only fix.