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.
How many people have something in each column
Nobody had to tell us what this business is. The column names did.
Q10. How long following Abu LahyaCapital available in next 30 daysProgram_TypeCourse Only (4k) · Full Program (7k)
Close_Lead_Status22 values, most of them a reason somebody dropped out
Q12 / Q13free text, full of halal · deen · allah · muslim
UTM Campaign159 values. A UTM is just a tag stuck on a link so we can tell which ad sent someone to us.
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 record of each call, only a flag for the stage someone sits in right now and a no show label that lasts until they are moved. We can see who booked, but not reliably who 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 where the selling starts, 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.
- There is no record of each call, only a no show label that lasts until the person is moved.
- So the 85% who booked and have not bought cannot be split into people who never turned up and people who said no, and those need opposite fixes.
Both ends leak, and they are different problems
| 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 never reach the CRM. Whatever happens to them, it is not a sales conversation. It is the single biggest number on this page. |
| 367 people, inside the CRM reached a salesperson, not marked as booked |
Just under half of everyone who reaches the sales team carries no booking. Some plainly had one, 42 of them sit at a no show stage, so this is an upper bound. The largest single reason in this group is that they could not afford it. |
| 352 people, after booking booked a call, have not bought |
Not all of these are lost. They are everyone still sitting in a booked or follow up stage, and 17 of them have paid a deposit. A person has spent time on each one, and without a record of each call we cannot say how many turned up. |
▶ How these numbers were built counting people, not rows
5,257 rows became 5,122 people$9,588 of cash was counted twice15 people removedThe 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 a tenth the size of the ads.
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
| 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% |
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. |
| One group is left off the chart on purpose | People with no tracking at all return $167 a person, more than any channel shown. But 69% of them had a CRM record 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 call outs brought 453 people and one sale. Email screenshot ads brought 337 and none. With the scam hooks, that is 743 different people for a single sale.
What angle the ad took
Who we called out in the ad
How the ad was made
Who made it
| Seif, all of it the last webinar | 278 |
| Not named in the ad title | 108 |
| Lahya, the newest batch | 22 |
| Imran, Ali and Shams | 28 |
- These 436 people are held out of every chart on this page, not counted against anyone.
- They signed up for the last webinar in the file, and the file was pulled the day after it.
- Every one of Seif’s people is in that group, so Seif cannot be judged yet.
- Lahya is the opposite case. 147 people who have had their webinar, and no sales. 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 ads that have had their webinar hold 36 customers. Split across angles, formats and audiences, many groups hold one or two. One extra sale moves a row several places. The order of the middle is 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 165 people in the wrong month. We can find an angle in nine names out of ten and a format in fewer than four, and the rest is guesswork that one agreed naming rule would remove entirely. |
Three things we are running that have produced one sale between them
| IT and tech call outs | 453 people, 1 sale |
| Email screenshot ads | 337 people, none |
| Scam awareness hooks | 117 people, none |
- Between them that is 743 different people and one sale. Some ads sit in more than one row, so the rows do not add up to it.
- They are not failing to attract anyone. They attract plenty, and almost nobody buys.
- The IT and tech call out is the clearest case: 453 people, the largest audience we name, and $8.02 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 either have less than $1,000 to hand or would have to find it. The one in five who have it buy at 4.6 times the rate.
The signup form asks 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, or would have to find it | 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% |
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. 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, just as well, 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% |
Split everyone with a score into ten equal groups
Score says yes, wallet says no
Grade D does not mean bad
- 1,457 of the 1,568 D grades never took a survey. D is not a judgement, it is a blank.
- Grade A is five people and no sales. It is not a tier, it is a rounding error.
How much of this to believe
| The problem | What it means |
|---|---|
| Only 3,539 people have a score above zero | 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 48 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.
- The form says the same about 80% of everyone who answered it, so on its own it cannot pick these people out in advance.
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.
Most of our sales are 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.
- The status label is not updated after a sale. The stage field is, and it picks out 57 of the 62 on its own. The CRM knows, it is one column over from where anyone looks.
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 still owed.
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 most of it
| 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 most anyone has paid is $7,000. The middle amount 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 most of our people are on UK and North American numbers. 23 of the 77 people have paid an amount that is not round, which is what instalments, exchange rates and card fees look like. |
| 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 of the 85% who booked and have not bought. |
| 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’s cohort against the next fairly. |
| Webinar attendance | The webinar is where the selling starts 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 | 165 |
| Names too short to use | 1,698 |
| People who told us nothing | 1,457 |
| Under eighteen | 105 |
- Update the status when someone buys. The stage field already identifies them; the status label does not, and it is the one people read.
- Decide what won means. Fifteen people have paid us and are not counted as customers.
- Agree one way to name an ad. Several conventions are in use and one typo put 165 people in June.
- Put the survey back on every version of the form. The money question predicts buying as well as our own scoring tool, and 1,457 people were never asked anything.
- Add an age gate. 105 people told us they are under eighteen, 15 of them under sixteen, and we are advertising a $4,000 to $7,000 product at them.
What the data already says we should do
| People without $1,000 to hand | 80% |
| Ads with one sale between them | 743 people |
| Stuck between booking and calling | 166 people |
| Money owed on sales already made | $142,624 |
- Use the money answer earlier. Four in five who answered do not have $1,000 to hand and buy at a fifth of the rate, yet they are still almost half of all sales. Route them, do not exclude them.
- Turn off what has not worked. Three things are running that have produced one sale between 743 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, and $122,159 of it sits on 39 payment plans that nothing here tracks.
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. |