This is a 30-day acquisition-efficiency case study, not a revenue case study. The sales numbers are developing and I've reported them as such below, including the parts that don't flatter us yet.
What were the results in the first 30 days?
Four numbers carry the story. All figures compare the seven months before we took over the account (1 January to 2 August 2026) with our first 32 days (3 August to 3 September 2026), both normalised to 30 days so they're like for like.
| Metric | Before (per 30 days) | After (per 30 days) | Change |
|---|---|---|---|
| Qualified leads | 24.1 | 60 | +148.8% |
| Cost per qualified lead | £521.07 | £147.65 | −71.7% |
| Meta cost per lead | £21.58 | £9.63 | −55.4% |
| Monthly ad spend | £12,564 | £8,859 | −29.5% |
A fifth number sits underneath those four and explains them: leads per 1,000 impressions rose 97.3%, while the cost per 1,000 impressions (CPM) fell only 11.9%. The campaign didn't win because traffic got cheaper. The ads got nearly twice as good at turning the same attention into an enquiry. More on why that matters below.
In raw volume, the new campaign produced 920 Meta leads per 30 days against 582 before. That's the number most agencies would lead with. It's the least important number in this article.
Who is the client, and what was the problem before we started?
Compare Funerals is an established funeral-plan provider. Its customers are British expatriates living in Spain, mostly older, who want their funeral arranged and paid for in advance so their family isn't left organising it across two countries. The sale is consultative: a lead form, then a phone conversation with an adviser, then a plan. Plan values are in euros; ad spend is in pounds.
The company had been running Meta lead ads for years and had the volume to prove the market existed. In the seven months before we took over, the account looked like this:
- Meta cost per lead averaged £21.58, which is respectable for a considered purchase.
- Only 7.02% of the leads that reached the CRM were marked qualified by the sales team.
- Cost per qualified lead had reached £521.07.
- Attribution between Meta and the CRM was incomplete: a large share of records carried no marketing source, so nobody could say with confidence which ad had produced which conversation.
That's the pattern in most established service businesses that come to us. The dashboard looks fine, the sales team says the leads are weak, and neither side can prove the other wrong because the data stops at the form. Spend was producing contact details, not enough commercially useful conversations.
So the brief wasn't "get us more leads." The campaign needed better economics across the whole journey, from impression to qualified opportunity. Cost per lead was a symptom to read, not a target to hit. I've written about why that distinction matters; this account is what it looks like in practice.
What counts as a "qualified opportunity" in this case study?
A qualified opportunity is a lead the client's own sales team has spoken to and marked as a genuine prospect in the CRM. It isn't my definition, and it isn't Meta's. That matters, because most case studies quietly use the loosest available definition.
We track four separate stages, and the numbers in this article are labelled by stage:
- Meta lead. Someone submitted the lead form on Facebook or Instagram. This is what Meta's cost per lead counts.
- CRM lead. The record arrived in the client's CRM with a marketing source attached. Not every Meta lead becomes a CRM lead, for reasons covered later.
- Qualified opportunity. The sales team contacted the person and marked them qualified: right person, real interest, able to proceed.
- Confirmed sale. A plan was purchased, matched back to the advertising by person or household (email first, then phone, then name), not by the CRM's source field alone.
Meta's dashboard stops at stage one. The client's revenue lives at stage four. Everything interesting happens in between.
What did we change?
Only what the data can show. The account changes were ordinary media-buying work; the measurement changes are where the leverage was.
On the advertising:
- Developed and tested new creative concepts rather than iterating on the existing winners.
- Changed the messaging and emotional angle. The incumbent ads sold the product; the new concepts spoke to the reason someone buys it, which for this audience is not wanting to leave a burden on family in another country.
- Improved how the offer was presented in the ad and on the form, so the person arriving already understood what they were enquiring about.
- Identified the strongest ads early and moved spend towards them, while cutting total spend rather than adding budget to a weak account.
On the measurement:
- Measured performance past Meta cost per lead, at qualified opportunity and confirmed sale.
- Matched Meta lead data to CRM qualification and sales records by person, because the CRM's marketing-source field was blank on a large share of records.
- Separated raw Meta leads, received CRM leads, qualified opportunities and sales into four reported numbers instead of one.
The second list is what made the first list possible to judge. Without it, the "worse CPL, better result" finding below would have been invisible, and we'd have scaled the wrong ad.
Why did the ads get more efficient?
Because the advertising got better, not because the auction got cheaper. Two numbers make the case:
- CPM (cost per 1,000 impressions) fell 11.9%. Cheaper attention, but only slightly.
- Leads per 1,000 impressions rose 97.3%. The same thousand people seeing an ad were almost twice as likely to enquire.
If the improvement had come from cheaper traffic, those two numbers would have moved together. They didn't. The gain came from creative, messaging, offer presentation and audience response, the part of a campaign an agency actually controls. Cheaper impressions are a gift from the auction that can be taken back next quarter. Ads that convert attention twice as well are an asset.
One caveat: part of a 97% lift from a new creative set is novelty. Fresh ads outperform tired ones in their first month, and some of this gain will decay. That's why the next result matters more than this one.
Why the ad with the worse cost per lead is producing the cheapest sales
This is the most useful finding in the account, and the sample is small enough that I'll present it as an early signal, not a verdict.
We ran two messaging tracks. The control carried the client's established angle. The second track led with the burden a death places on family, which is the real reason this audience buys a plan. At the reporting date:
| Control messaging | Family-burden messaging | |
|---|---|---|
| Spend | £7,221 | £2,229 |
| Meta leads | 780 | 201 |
| Meta cost per lead | £9.26 | £11.09 |
| Qualified opportunities | 48 | 16 |
| Confirmed sales (so far) | 3 | 3 |
| Cost per confirmed sale | £2,407 | £743 |
The family-burden ads produced a Meta lead that cost 19.8% more. On cost per lead alone, you'd cut them. On confirmed sales, they matched the control with roughly 69% less spend, and their leads qualified at a higher rate (8.0% of Meta leads against 6.2%).
Three sales each is not a safe comparison, and I'm not claiming the family-burden track is three times better. What it shows is why cost per lead can't be the scaling decision. Optimised the conventional way, the ad now producing the lowest cost per sale would have been switched off in week two for being 20% "more expensive." The lowest cost per lead and the highest lead quality are rarely the same ad. You only find out which one pays by measuring to the sale.
What do the sales numbers actually say so far?
Six confirmed sales, matched by person or household, had been attributed to the new campaign at the reporting date. Confirmed acquisition cost was £1,575 per sale, against £1,867 historically, a 15.6% improvement.
That is a real number and I'm pleased with it. It is not yet proof that we've increased sales, and I want to be precise about why:
- The post-takeover cohort is a month old. Funeral plans aren't bought on the day of the enquiry; the historical cohort had seven months to mature.
- 75% of the new cohort's CRM records had no recorded outcome at the reporting date. Most of those leads haven't been resolved either way.
- On the records resolved so far, sales conversion is running at 1.34% against 1.96% historically, and normalised sales volume is 5.63 per 30 days against 6.73. On today's data, sales volume is not up.
- Only €6,750 of plan value is directly documented against those six sales. A figure of around €13,500 is an estimate based on typical plan values, not verified revenue, and I'm not reporting it as revenue.
So the honest position after 30 days: the cost of acquiring a customer has fallen, the number of people who could become customers has more than doubled, and whether that turns into more plans sold depends on what happens next in the client's sales process. I'd rather publish that sentence than a revenue claim I have to walk back at 90 days.
What's still holding the result back?
Working the leads. The audit surfaced a downstream constraint that the advertising can't fix on its own: of the new cohort's CRM records, 26% had a recorded outcome, 34% had not been touched, and 40% were sitting in a dialler queue waiting for a call.
That's not unusual. An account that goes from 24 to 60 qualified opportunities a month has handed its sales team two and a half times the work, and most teams are staffed for the old number. The research on response time is unforgiving: contact inside five minutes converts at roughly eight times the rate of waiting even half an hour, and most firms take longer than a day. Every day a lead sits in a queue, the ad spend that produced it depreciates.
Read it this way: the marketing improvement has been demonstrated, and most of the commercial opportunity it created has not yet been processed. That's a better problem than the one the account had in July, but it's still a problem, and it's what the next 60 days are about. This is the gap between marketing and sales that decides whether any campaign pays.
When this approach wouldn't have worked
A 30-day acquisition turnaround like this depends on conditions that not every business has. It's worth being clear about them, because the same changes in a different account would have produced a nicer dashboard and nothing else.
- If the offer weren't already proven. Compare Funerals had years of sales and a 20% close rate on qualified funeral-plan leads before we arrived. Better ads amplify an offer that converts; they can't rescue one that doesn't.
- If nobody could work the extra volume. Doubling qualified opportunities into a team that can't call them is a way to spend less and sell the same. If your sales capacity is the constraint, fix that before touching the ads, or the improvement stalls exactly where this one is stalling now.
- If the CRM can't be matched to the ads. Everything in this article beyond the Meta dashboard came from person-level matching between the ad platform and the CRM. Without that, you can only report cost per lead, and cost per lead would have told us to kill the best ad.
- If you want a revenue claim in 30 days. For a considered purchase, a month is enough to prove acquisition efficiency and not enough to prove sales. Anyone showing you a 30-day revenue case study for a product people take weeks to buy is either counting something else or guessing.
If you run a funeral-plan business and want to know which of those conditions applies to you, the funeral plan scale-readiness diagnostic is built around exactly these questions.
What happens next?
In the first month, the campaign produced 2.5 times more qualified opportunities per 30 days on 29.5% less advertising spend. The immediate result is a 71.7% reduction in cost per qualified lead.
The next stage isn't more ads. It's speed to lead on the queue that's built up, repairing CRM attribution so every record carries its source, and giving the new cohort enough time to mature. I'll publish a 90-day update with confirmed sales, verified plan revenue, cost per sale and cohort conversion once the backlog has been worked, whichever way those numbers land. This account is one door of the Attention-to-Revenue System, the managed lead-generation engine, and the whole point of that system is measuring the chain to revenue rather than stopping at the lead.
Frequently asked questions
Is a lower cost per lead a good sign?
Only as a place to start looking. In this account the Meta cost per lead fell 55.4%, which is welcome, but the messaging track with the higher cost per lead is currently producing sales at less than a third of the cost. Cost per lead tells you how efficiently an ad produces a form submission. It tells you nothing about whether the person on the form will buy. Judge a campaign on cost per qualified opportunity and, once the data exists, cost per customer.
How long does it take to see results from a new Facebook ads campaign?
Acquisition metrics move fast: within a month you can see whether new creative produces more qualified opportunities per pound, as it did here. Sales metrics move at the speed of the buying decision. For a considered purchase like a funeral plan, a cohort needs 60 to 90 days before its sales conversion can be compared fairly with historical performance, which is why this case study reports acquisition results as final and sales results as developing.
Why did some Meta leads never reach the CRM?
Because the integration between the ad platform and the CRM was incomplete before we started, and a large share of historical records carried no marketing source. We matched leads to CRM records by person (email, then phone, then name) rather than trusting the source field. If you can't do that matching in your own business, your cost-per-customer figures are guesses, and repairing the link is usually cheaper than any change to the ads.
Does this mean video ads beat image ads for funeral plans?
This case study doesn't test that. The improvement came from new creative concepts, messaging built around the buyer's real motivation, clearer offer presentation and measuring to the sale. Whether the format is image or video matters less than whether the ad says the thing the buyer actually cares about and whether the lead gets called quickly afterwards.
Can this be replicated in another service business?
The method can: define what "qualified" means with your sales team, match ad data to CRM outcomes by person, test messaging angles against qualified opportunities rather than cost per lead, and cut spend on what doesn't qualify. The specific numbers can't, because they depend on your offer, your close rate and your sales team's capacity to work the leads.
Sources
- First-party data: Meta Ads Manager account exports for Compare Funerals, 1 January–2 August 2026 (pre-takeover baseline) and 3 August–3 September 2026 (first 32 days), and the client's FLG CRM exports for the same windows. Qualified status and sale records are the client's own; sales were matched to advertising by email, phone and name. Reporting date 3 September 2026. Figures normalised to 30 days where stated.
- Lead response timing: InsideSales, Response Time Matters (2021 analysis of 5.7 million inbound leads: conversion odds fall roughly eightfold after the first five minutes), building on the original MIT / InsideSales Lead Response Management Study by Dr James Oldroyd (2007).
