The Andromeda Field Manual  · Meta lead-gen · 2026
Operator's manual · v1 draft · built 2026-08-09

Stop running campaigns. Start running systems.

Everything you need to build and scale a Meta lead-generation system from zero under Andromeda — the account architecture, the ads themselves, how the algorithm decides, how to read the data, and how to scale without breaking it. Every claim is colour-coded to the operator who said it.

Sources  10 transcripts · ~300k characters
Teachers  Professor Charley T · Alex Becker
Window  Apr–Aug 2026, all post-Andromeda
Worked example  NZ life-cover advisory

00How to read this

This guide makes no claims of its own about what works on Meta. Every tactical statement traces to one of two operators, and is tagged accordingly. Where they disagree, you see both. Where I have extended their thinking into lead generation — which neither of them teaches directly at length — the panel is dashed and violet, and you should treat it as a hypothesis to test, not doctrine.

The provenance key

Charley Professor Charley T. Ex-Omnicom, in the room at Meta's 2017 “Build to Break”. Says he has managed over a billion dollars in spend; scaled Underoutfit 50k/mo → 1M/week, and 310 Nutrition 15M → 98M/yr. Invented the “one campaign method”. The architecture, metrics and testing discipline here are his.
Becker Alex Becker. CEO of Hyros, an ad-tracking platform — so he sees performance data across thousands of accounts, and he has a commercial interest in the tracking half of his advice. Scaled multiple offers past $100k/day. The offer doctrine, buyer-profile systems and signal manipulation are his.
Both Independently stated by both. Becker explicitly credits Charley on-camera for several of these, so treat “both” as strong consensus, not two independent confirmations.
Applied My extension of their principle into lead generation or the NZ example. Not something either man said. Test it; don't trust it.
Conflict The two disagree, or one contradicts himself across videos. Flagged, never smoothed over.
Read this first

Every dollar figure in the worked example is illustrative and invented. Neither source gives numbers for NZ life insurance, insurance commissions, or any lead-gen vertical. The arithmetic shows you the shape of the calculation. Replace every number with yours before you make a decision with it.

The NZ financial-advice regime is not addressed by either source. The offer construction in §16 uses guarantees and outcome claims because that is what Becker teaches. Guarantees and outcome claims about insurance in New Zealand are a regulated-advice question. Have a compliance read before anything ships.

The ten sources

DateSourceTitleWhat it carries
2026-04-09CharleyHow to CRUSH Facebook Ads with a Small BudgetThree-stage audience build; broad vs pixel retargeting; copy structure
2026-05-04CharleyThe NEW BEST Facebook Ads Strategy for 2026Andromeda One structure; GPT; hunters vs farmers; budget ladder
2026-05-11CharleyThe BEST NEW Way to Test Ads on MetaOlympic Rings; why volume testing self-harms; when to test
2026-06-28CharleyFacebook's NEW UPDATE just changed DTC foreverCustomer lifecycle strategy; exclusions; list hygiene; spend tiers
2026-07-07CharleyFacebook's New Update Just KILLED ChatGPT and ClaudeNative AI creative suite; niche-level performance priors
2026-07-14CharleyMeta Made $196 Billion… So Why Does Running Ads Feel Broken?Four eras; five algorithm generations; three winning business models
2026-07-18CharleyNew BEST 2026 Meta Ads Course After AndromedaThe spine. Five disciplines, end to end
2026-07-25CharleyThe NEW BEST Creative Enhancements GuideThe 11-enhancement traffic light; confidence↔enhancement rule
2026-07-30BeckerMy Meta Ads Are Awful…But Make $100k A DayOffer doctrine; high-ticket 1-in-100; cold ≠ warm
2026-08-07BeckerTHE 2026 Meta Ads MASTER CourseBuyer-profile systems; 5–8 ad funnels; signal front-loading

01The machine: what Andromeda actually does

Almost every mistake in a 2026 ad account comes from a wrong mental model of what happens between you pressing publish and a human seeing your ad. Get this right and the rest of the manual is obvious.

An ad is a web page competing in a search engine

Charley The first reframe. On Facebook and Instagram, every post — paid or organic — is a page on their site competing for attention in the feed. The feed is not a billboard. It is a search results page, continuously re-ranked.

“Every social media feed is basically just a Google search results page, where Andromeda is showing you content it thinks you'll engage with. Every single piece of content has a score called the estimated action rate, based on how likely people are to do things like engage and click.”

Charley T · 2026-05-11 / 2026-07-18

Your ad does not buy an impression. It earns one, by out-ranking organic content, your competitors' ads, and your own other ads, on predicted action rate. That is why the discipline in this manual looks more like SEO or content strategy than like classical media buying.

Two gates stand between your ad and a human

Charley Before your ad earns any real spend it passes two distinct systems, and they are optimising for different things.

A human opens the feed one slot opens GATE 1 · LATTICE Should this person see an ad at all? Balances user experience against advertiser objectives Attention is the product. GATE 2 · ANDROMEDA Which of millions of ads deserves a chance? Ranks on estimated action rate — merit, not bid Matches people to ads. SPEND IS EARNED Scroll stopped · watched clicked · converted “Users like this experience. Show it to more people.” Your budget setting is a ceiling, not an instruction. Spend is a verdict the machine returns.
The two gates. Lattice protects the user experience; Andromeda decides merit among competing ads. Source: Charley T, 2026-07-18. Note what is absent — there is no step where your targeting selections do meaningful work.
Rule 01 · Charley Spend is not a budget setting. It is the clearest available read on what the machine believes about your ad. Track it as your first-order KPI, above CPA and above ROAS.

The four metrics, and what they actually mean

Charley Charley's central diagnostic — the 4PI analysis — reads four numbers together to work out how Meta is using each ad. The full decision procedure is in §11; here is what each number means mechanically.

Spend — preference

A ranking of how well your ad meets both your objective and Meta's. High-spend ads can carry a slightly worse CPA, because when Meta spends harder it pushes past the easy conversions into colder people who fill the funnel.

Frequency — funnel position

Not fatigue. A read on who is being targeted. Daily frequency 1.05 means ~5% of people saw the ad twice; 1.95 means ~95% did. Low = Meta is finding new people. High = Meta is retargeting.

CPM — price and quality of attention

You compete against organic content too — friends, creators, memes. Better user experience earns lower CPMs even in competitive audiences. Bad experience means paying more just to get delivery.

Cost per result — contribution, not quality

“Not a measure of how good an ad is. It's a measure of how much that ad contributed to the conversion actually happening.” Lower cost usually means it did less work — it showed up at the end.

DAILY FREQUENCY — WHAT META IS DOING WITH THE AD 1.051.251.50 1.751.95 ~5% saw it twice Meta is using this ad to find NEW people. This is a prospecting ad, whatever you called it. ~95% saw it twice Meta is using this ad to RETARGET individuals. This is a closer, whatever you called it. “Creative does the targeting. Frequency is how you can see who's being targeted.”
Frequency is a position indicator, not a fatigue alarm. Source: Charley T, 2026-07-18. Three reasons it climbs: (1) cold audiences don't like the ad, (2) you keep resetting the machine with launches and budget changes, (3) it genuinely converts warm traffic well. Reasons 1 and 2 show up as high frequency plus low spend — that pairing is the tell.

Why launching lots of ads actively harms you

Both This is the single most counter-intuitive claim in the manual, and both operators land on it independently of each other's framing.

New ads are always shown first to your warmest audience, because those people are most likely to engage and convert — which is exactly what a new ad needs in order to prove itself. So every new ad you launch is spending your money to compete against your own existing ads for the same warm conversions.

“The more new ads you launch, the more you invest in competition against your warmest audience. The new ads take spend and credit from your existing ones, so the older ads look worse. And you're not filling the funnel… You end up day trading the ad account.”

Charley T · 2026-05-11

“When you go in here and you put in a thousand different ads, the ads never realise how they work together and they're constantly competing with each other… Facebook doesn't know how the system goes together, so it's just shuffling these ads all over the place, and never optimising the system around it.”

Alex Becker · 2026-08-07

Charley And the platform is explicitly built to punish it:

“Meta specifically states that Andromeda was built because so many people were launching so many ads, and now it penalises that. What Meta wants is simpler — a few ads that do different jobs.”

Charley T · 2026-05-11
Both

The doom loop, named

Results look worse → you launch more ads → the new ads eat the warm conversions → performance gets less stable → you become dependent on whatever new ad is winning today → results look worse. Charley calls the escape “becoming a farmer”. Becker calls the trap “the dumpster fire CBO”. Same loop.

Creative diversity is not ad volume

Charley The defence people offer for launching fifty ads a week is creative diversity. Charley rejects the premise, citing Meta's own CMO:

“Alex Schultz, Meta's CMO, explains that when Zuckerberg talks about personalisation, he's not talking about making a different ad for every single person. He's talking about the overall experience somebody gets across the feed, across all of the touchpoints, paid and organic… Personalisation is a delivery sequence problem, not a creative volume problem.

Charley T · 2026-05-11

Real creative diversity means a small set of ads that do different jobs in a sequence — which is exactly what §7 and §8 build.

02Why it feels broken when the data says it isn't

Meta made $196bn from ads last year, up 22%. More than ten million advertisers are on the platform. So why does your account feel worse every quarter? Charley's answer reframes the whole problem, and it determines what you should actually be optimising.

ERA 1 · PRE-PIXEL ERA 2 · GOLD RUSH ERA 3 · iOS14 + MACRO ERA 4 · DEMOCRATISATION $4.3bn $85bn $113bn $196bn $200bn+ $0.55 ~$10 ~$12 mid-teens 201220152020 202220252026e Pixel ships 14 Oct 2015 Meta annual ad revenue Typical CPM Endpoints are Charley's stated figures; the path between them is illustrative.
Four eras. Ads got roughly 18× more expensive between 2012 and 2020 — and brands chose to spend about 20× more. Source: Charley T, 2026-07-14. Era 3's dip tracks the stock market, not iOS 14 alone: “same curve, same drop, same timing… it wasn't a platform confidence problem, it was a macroeconomic confidence problem.”

Era 4 explains your CPMs

Charley Era 4 was not defined by AI. It was defined by democratisation. Meta stopped building better tools for the biggest spenders and started building smarter tools for everyone else — Advantage+, Andromeda, automation. There are now more than 10 million advertisers, and over 80% of them spend less than $100 a day: restaurants, roofers, dentists, gyms, creators.

Those tools were not built for the brands that survived era 3. They were built to bring the next million advertisers online — and it worked. Demand grew faster than supply, which is why the auction is more expensive even though nothing about your account got worse.

Charley

Why your CPM is $35 when the market average is mid-teens

Sort your own ads by spend. The ads getting the most spend usually have the lowest CPMs, and are rarely the most efficient on cost per result. CPM is the price of attention — it says nothing about what that attention was worth. Charley's question: “If you paid twice as much to reach people, but they were four times more likely to buy, did advertising actually get more expensive?”

ROAS is an averaging error

Charley Meta reports that the average advertiser earns well above $3 for every dollar spent, across $100bn+ in spend. Charley's objection is not that ROAS is a bad metric — it is that the average is meaningless:

“Imagine averaging the ROAS of a dentist, a restaurant, a roofing company, Nike, Amazon, and a $20 million supplement brand. You're going to get a number, but it won't tell you what good looks like, because none of those businesses make money the same way.”

Charley T · 2026-07-14

He then names the killer case: Allbirds peaked above $648/share after its 2021 IPO and hit an all-time low of $2.15. “You can chase 3× ROAS and still destroy the value of the business.”

The algorithm rewards a business model, not a niche

Charley Three companies kept winning across multiple eras, in totally different categories. What they share is not tactics.

Ridge — wins on profitability

A wallet. Premium pricing, healthy margins, a product understood in three seconds, and an experience that delivers what the ad promised. Spends $200k+/day acquiring customers. The advantage isn't the wallet — it's the margin structure behind it.

Grüns — wins on lifetime value

Launched 2023, subscription nutrition, reportedly on pace for hundreds of millions a year. Doesn't try to win on the first purchase. Dan Kennedy's line applies: “Whoever can spend the most to acquire a customer wins the game.”

Comfrt — wins on distribution

Born after iOS 14, no subscription, ~$1bn run rate. Turned customers into the marketing department — UGC is built into the business model, so every sale can create the next one. Meta sees the shares, comments and repeat attention around the purchase, not just the purchase.

Rule 02 · Charley “Facebook isn't trying to find you the cheapest click. It's trying to find the next person who's likely to engage, to click, to buy, and to feel good about it.” The machine rewards businesses that produce happy customers, because happy customers make people trust the platform. You are not optimising ads. You are optimising the business the ads point at.

Five generations — and where the control went

Charley Fifteen years of Meta updates read as one continuous project: taking decisions away from advertisers and making them better on their behalf. Fighting it has always been expensive.

GenEraWhat you controlledWhat Meta took over
1RulesTargeting, bids, budget, timing, sequenceNothing. Success depended on what you did outside the platform.
2OptimisationThe objectiveStopped asking “who do you want to reach”, started asking “what do you want them to do”. Clicks became purchases.
3Machine learningThe data you feed itAudience construction. Value optimisation, server-side signals, the Power Five.
4AndromedaCreative, offer, signalMatching. Flipped from matching ads→audiences to matching people→ads. Merit-based distribution rather than a bid auction.
5Generative (emerging)The business itselfRanking, adapting and generating variations. Understanding what your business is and why people buy.
Charley

The through-line

“Every generation pushes us to be a little less like media buyers and a little more like business builders.” And note the loop closing: in generation 1, success depended on what you did outside the platform. In generation 4, targeting and bidding are answered for you — so success depends, once again, on what you do outside the platform. Your offer. Your landing page. Your data. Your margins.

03The offer, before you touch the ad account

Becker's entire contribution starts here, and he is deliberately extreme about it: nothing you do inside Ads Manager can rescue an offer that isn't built for cold traffic. This section comes before architecture because if you get it wrong, every later section is wasted motion.

“The big lesson I need to teach you in the video… nothing in the ad account that you do matters. You have one single goal when you start running ads. You need to make an offer so good that you can literally just run an ad, repeating the offer, and then showing the results, and it works.”

Alex Becker · 2026-07-30

Take the framing, not the literalism — Becker himself spends an entire other video on account structure eight days later. What he means is that offer quality dominates account quality by an order of magnitude, and most operators have the effort allocation backwards.

Cold traffic is a different buyer to warm traffic

Becker The most common structural error: selling on ads the way you sell on your website. Someone arriving at your site already has context, intent and some trust. Someone on Instagram has none of the three, and is one thumb-flick from something more interesting than you.

Becker

The acquisition.com trap

Becker points at the page everyone models — Hormozi's — and makes a precise point: that page is selling to warm traffic. Everything on it works because the reader already knows who Alex is. Copy it for cold traffic and it fails on its face. Hormozi's own cold-traffic offer, Gym Launch, was structured completely differently — as a new, specific, guaranteed result for one buyer type.

The five-part offer test

Becker An offer that works from cold ads has all five. Missing any one of them and, in his words, “it's not going to work” — regardless of vertical.

01 · NEW A mechanism they haven't seen New words. New lingo. “I don't understand how that works.” 02 · RESULT One clear outcome they already want Not your product category. Not features. The result. 03 · NO EFFORT You remove the work, not them Done-for-you. Every objection is usually effort in disguise. 04 · PROVEN Endless results, named You just made a bold claim. Now prove it or it's noise. 05 · GUARANTEED Kill the last dose of scepticism “If you don't see it, you don't pay for it.” Becker's worked example: “tracking” → a new form of tracking (new) that lifts ad ROI 15–20% (result), we set it up for you (no effort), here are Tony Robbins and Playboy (proven), or you don't pay (guaranteed).” Every competitor was selling “track your ads better”. Nobody wants to buy that.
The five-part cold-traffic offer. Source: Alex Becker, 2026-07-30. His test for “new”: in supplements there's a new weight-loss mechanism every year — peptides, turmeric, butter in coffee — not because the body changed, but because novelty is what buys attention.

The 1-in-100 rule, and why lead gen should be high-ticket

Becker The economic argument for restructuring your offer upward. Send 100 cold people to three different price points and the conversion rates are far closer than intuition suggests.

100 COLD VISITORS · SAME TRAFFIC · TWO OFFER STRUCTURES $50 product ≈10 buyers · you will not break 10% $500 total from the same 100 people …and 90 people you never captured $2,000 total solution ≈1 buyer · “as consistently as we see the 10” $2,000 4× the revenue from identical traffic + the other 99 captured as leads to work “That one out of 100 will spend more than 10 out of 100 every single time. You go for that person to cover your ad cost while you build a huge audience.”
The 1-in-100 rule. Source: Alex Becker, 2026-07-30. The high-ticket sale funds acquisition; the other 99 become an owned audience you sell to later. Becker's structural recipes: SaaS → sell a done-for-you service that bills against the subscription (which just front-loads 6–12 months). E-commerce → sell coaching that requires buying product in bulk.
Applied to lead gen

What “high ticket” means when you're not selling a product

In lead generation you are usually not transacting on the page at all — so “make it high ticket” translates to make the thing you ask for proportionate to a high-value outcome, and capture everyone else on the way past. Becker's own funnel is exactly this and it is lead gen: apply → email captured → book a call → high-ticket done-for-you service sold on the call.

The practical translation: a two-step capture. Step one takes the email from everybody. Step two books the appointment from the fraction who are ready now. You are not choosing between volume and value — Becker's point is that the same page can harvest both, and most operators build only one.

The landing page is part of the offer

Becker One landing page for all traffic is, in his words, “really stupid”. Each buyer profile gets its own page, matched to the hook that brought them.

“I found CPA is the hot button for e-commerce marketers. So when they click that ad, the landing page talks about cost per acquisition as the main problem, and then shows them how we fix their cost per acquisition.”

Alex Becker · 2026-08-07

Two findings worth more than they look:

  • Ugly beat beautiful. Becker built an elaborate animated page that scans the visitor's website and personalises the testimonials. His plain, “kind of ugly” page converts better. “In the age of beautiful AI websites, being very clear about what you do is going to get you more results.”
  • Page production is no longer the constraint. He generates per-profile pages with Claude Code in minutes. If pages are cheap, there is no excuse for one-size-fits-all — which changes how many buyer profiles you can justify running.

Charley Charley arrives at the same requirement from the ad side: continuity. The voice in the ad should match the brand or the customer, the primary text should preview the landing page, and “when somebody sees that primary text and it's what they see on the landing page, the primary text that got that click is more likely to get that person to hit add to cart.”

Rule 03 · Becker If you cannot state your offer as one sentence that is new, promises a specific result, removes the effort, cites proof and carries a guarantee — stop. Fix that before you read another word about campaign structure. No account architecture rescues a commodity offer on cold traffic.

04Systems, not campaigns

This is the conceptual core of the manual and the thing that makes everything else cohere. Both operators arrive at it; Becker names it most directly.

“Each campaign is not some series of ads all put together. It's not a bunch of ad sets sharing conversion data. What each campaign is, is a funnel to get a person from the top of the funnel to the bottom of the funnel and convert. And all the ads in the campaign — which you don't want a lot of them — are not used to just compete against each other and then get the last click. They're used to get people to the bottom of the funnel… they all work together like a unit.”

Alex Becker · 2026-08-07

“Facebook ads are a team sport. Messi is incredible, but he's not winning matches if he's on the pitch by himself… If you're not winning, improve the worst player on the team.”

Charley T · 2026-05-11

The consequence: you judge the system, never the ad

Both If the ads are a sequence, then no individual ad's ROAS means anything — it is an artifact of where that ad happened to sit in someone's journey and who got credit for the last click.

Becker

The sales-call analogy

“Imagine you have a sales call and you have the opener… If you change that opener 52 times a week, are you going to get that much better results? No — because it's how that opener works with the rest of the script. The script itself and how it all works together is what gets the conversion.”

Testing thousands of creatives is testing the opener 52 times a week while never once looking at the script.

Ad fatigue is mostly operator error

Both A direct challenge to the industry's most common assumption.

“Ad fatigue's a really silly thing if you think about it. If the initial start of the ad works, why should it have to be changed every week? You're not running out of people you're showing it to, and if it's effectively reaching your target audience and bringing them down the funnel, you don't need to change it every week — because every new person goes down the funnel correctly.”

Alex Becker · 2026-08-07

Charley's version is blunter: “Ad fatigue is almost always operator error.” The mechanism is the one from §1 — you fatigue your own ads by launching competitors to them, then read the resulting decay as a law of nature. Becker has run essentially the same Hyros ad for six or seven years.

How good does each ad need to be?

Both Much less good than you think, and this is liberating.

  • Charley “None of these ads have to be perfect. They just have to be good enough at their role in the system.”
  • Becker “Once you get them mostly right, like 70% right, it's going to do most of the job… the entire system should work on its own even if the ads aren't perfect.”
  • Becker His estimate of the ceiling on ad-level optimisation: a swing from a 4.7% to a 5.3% click-through rate. “Still meaningful, but not enough to completely break it either way. It really comes down to the concept itself.”
Rule 04 · Both Design the sequence first, then fill the slots with adequate ads. A well-built sequence of mediocre ads beats a pile of excellent ads with no relationship to each other — and it is far cheaper to operate, because you stop needing a new winner every week to hold the line.

05Account architecture — and the one real disagreement

Charley and Becker agree on nearly everything in this manual. On how many campaigns you should run, they do not. This section gives you both structures exactly as taught, then a decision rule for choosing, then the budget constraint that overrides both.

Structure A — Andromeda One Charley

The modern version of the one-campaign method Charley says he invented five years ago. One CBO campaign. Everything lives inside it so that all spend runs through a single learning system.

ONE CBO CAMPAIGN — ALL SPEND, ONE LEARNING SYSTEM AD SET 1 · CONTROL The benchmark. Your proven team. No fewer than 4, no more than 8 ads. Good mix of images and videos. PROSPECT 1 PROSPECT 2 PROSPECT 3 RETARGET 4 RETARGET 5 …up to 8 · harvested winners These are not winners forever. They are the most stable ads — good enough to rely on and scale from. AD SET 2 · TEST ONE 322 AD 3 creatives · 2 headlines · 2 texts Exactly one ad. Its only job: improve or replace the worst ad in the control. AD SET 3 · TEST ONE 322 AD the A/B partner Ad sets 2 and 3 are read as an A/B test against each other. HARVEST → move the winning post ID into the control, then re-measure “Even when I'm spending a million a month, I don't have more than two testing ad sets. Once you get there, you're done. You're ready to scale to the moon.”
Andromeda One. Source: Charley T, 2026-05-04 and 2026-07-18. Note the hard ceiling: the structure never grows past three ad sets no matter the budget. Scale happens through budget and creative quality, never through structural sprawl.

Structure B — buyer-profile systems Becker

Becker does not run one campaign. He runs one campaign per buyer profile, each a self-contained funnel of 5–8 ads, each deliberately held at low spend, each pointed at its own landing page. There are no prospecting or retargeting campaigns, because both live inside every system.

FOUR CAMPAIGNS · ONE PER BUYER PROFILE · $100–200/DAY EACH E-COMMERCE BUYERS 1 · UGC problem video 2 · Static, same hook 3 · Second benefit 4 · Straight offer 5 · Client result 6 · Objection handler DEDICATED LANDER speaks to THIS hook only INFO BUYERS same 5–8 slot template different hook, script, proof and objections DEDICATED LANDER SAAS “cookie-cutter this across every profile” DEDICATED LANDER AGENCIES no retargeting campaign — retargeting is inside the system DEDICATED LANDER “I'm going to make four different campaigns at lower ad spend with five to eight ads arranged in a funnel each… well below where the audience threshold is, so it's focusing on getting the best person into each funnel.”
Buyer-profile systems. Source: Alex Becker, 2026-08-07. The deliberate low budget per campaign is a feature, not a limitation — it keeps delivery concentrated on the best-matched people rather than expanding into a broad audience.
Conflict

They cannot both be optimal

Charley: consolidate everything into one campaign so all spend feeds one learning system, and let Andromeda handle personalisation — “because all spend runs through one system, Meta's Andromeda gets better at matching the right ad to the right buyer.”

Becker: split by buyer profile because different buyers need different funnels and different landing pages — “you don't want them going down the same funnels.”

Both are describing accounts that work. The reconciliation below is Applied — neither man addresses the other's structure directly, so this is my synthesis and you should treat it as such.

Applied

A decision rule for splitting

Split a buyer profile into its own system only when all three are true. Otherwise consolidate, because consolidation is Charley's default and it is cheaper to run.

  1. Different problem. Not a different demographic — a genuinely different pain, needing a different top-of-funnel hook. A 32-year-old with a new mortgage and a 58-year-old whose premiums just stepped up are different problems. Two age bands with the same problem are not.
  2. Different landing page. If you would not write them a different page, you do not have a different system. Becker's split is defined by the page as much as the ads.
  3. Enough budget to survive alone. This is the hard constraint, and it comes from Charley — see the ladder below. A split that leaves any campaign unable to exit the learning phase is strictly worse than not splitting.

Note that Becker runs each profile at $100–200/day. Four profiles is $400–800/day minimum before the architecture makes sense on his terms. Below that, run Charley's single campaign and let the Olympic Rings (§7) carry the different messages inside it.

The budget ladder overrides everything

Charley Before you copy any structure, the budget decides what you are allowed to build. The rule is about the learning phase, not about ambition.

THE LADDER — CLIMB ONLY WHEN THE PREVIOUS RUNG IS RELIABLY EXITING LEARNING RUNG 1 Everything in ONE ad set Control ads and test ads are simply ads inside the same ad set. Trigger to climb: you can reliably get more than one ad set out of learning. RUNG 2 1 control + 1 test The first real Andromeda One. One 322 ad in the test set. Trigger to climb: budget supports two testing ad sets in learning. RUNG 3 · TERMINAL 1 control + 2 tests The two test sets are an A/B pair. This is the end of the ladder. You never climb again. At $1M/month, the structure is identical. “If your budget isn't high enough to reliably get more than one ad set out of the learning phase, then everything lives in one ad set.” Structure is a function of budget, not of ambition. Building rung 3 on a rung 1 budget guarantees instability.
The budget ladder. Source: Charley T, 2026-05-04 and 2026-07-18. This is the most commonly skipped rule in the whole manual — people copy the three-ad-set screenshot at $40/day and then blame Andromeda for the volatility.

Side by side

Andromeda One CharleyProfile systems Becker
CampaignsOne, CBOOne per buyer profile
Ad sets1 control + up to 2 test — hard ceilingFunnel per campaign; a head ad set shares the conversion data
Ads live4–8 in control5–8 per system
RetargetingRings 4 and 5 inside the control ad setAds 4–6 inside each system
Budget postureConsolidate to maximise shared learningDeliberately low per campaign, below the audience threshold
Landing pagesContinuity with the primary textOne per profile, mandatory
Testing322 ad in a dedicated test ad setSeparate ad sets with flex ads, winner swapped in
Best whenOne core buyer; budget concentrated; you want the least management overheadGenuinely distinct buyer problems; budget to fund each; page production is cheap
Applied

What I'd do for a lead-gen account starting from zero

Start on Charley's structure, single campaign, single ad set, because that is what the budget ladder permits and because at launch you do not yet know which buyer profiles are real. Use the Olympic Rings to carry your two or three candidate hooks as separate prospecting ads inside one ad set.

Let delivery tell you which hooks earn spend. When one hook proves it deserves its own landing page and its own proof and objections — and only then — graduate it into a Becker-style system of its own. You are letting the account discover the buyer profiles rather than guessing them up front, and you never pay for a split before it has earned one.

06The ad itself: the 322

One ad format carries the whole system. Charley says the three ads he shows that have each spent over a million dollars are the same format — and that after Andromeda it is the best kind of ad you can run, “and almost no one is using it properly.”

Anatomy

Charley Three creatives, two headlines, two primary texts, inside a single ad using Meta's multimedia creative workflow (the replacement for flexible ads / DCO, which Meta killed in April 2026). That is twelve combinations competing inside one post.

ONE AD · TWELVE COMBINATIONS · ONE SHARED LEARNING POOL 3 CREATIVES Video A hook 1 Video B hook 2 Video C hook 3 ALL ONE FORMAT — 3 videos OR 3 images. Never mixed. To compare video vs image, run two separate ads against each other. 2 HEADLINES “Buy now and save” “The last one you'll need” Two distinct frames of value. 40 characters max · NOT shown on Instagram. 2 PRIMARY TEXTS Short — ≤180 characters Long — uses “see more” Genuinely different angles, not rewrites. 125 chars show before “see more”. = 12 combinations SPEND IS EARNED, NOT SPLIT — META PUSHES BUDGET TO THE BEST COMBINATION A · H1 · T12% A · H1 · T23% B · H2 · T161% ← the winner B · H2 · T214% C · H1 · T14% …7 more combinations16% between them Every combination's performance data feeds one shared pool, not twelve isolated buckets. When something starts working, the signal isn't trapped in a single post ID — it is shared across every element, so Meta can build on what it learned. THE HARVEST When one combination dominates spend, that post ID is your winner. Don't interrupt it — pull that post ID into the control ad set and measure what the campaign does. Keep or kill on that answer alone.
The 322 ad. Source: Charley T, 2026-05-04 and 2026-07-18. The mechanism that makes it superior to separate ads: shared learning. Ads launched side by side each learn in isolation and none of it carries over — and the new ones that deliver first are the ones closest to conversion, which is why fresh ads look great for two days and then tank.

Why exactly three creatives when Meta lets you upload ten

Charley This is the single most-violated rule of the format.

“Remember that a 322 is already 12 ads. So if you load five or ten creatives, that could potentially be hundreds. Whatever gets lucky early is going to dominate everything — only because at your warmest audience, it was the thing people clicked on first. And this is why a lot of folks say ‘flex ads don't work, dynamic creative is stupid’ — because they overwhelm the machine.”

Charley T · 2026-07-18

With three creatives, Meta can make a real decision quickly and consolidate spend around the best one, which means all your spend is making that decision better. Either you have a winner or you kill it and move on.

Charley

Real multivariate testing — the trick nobody uses

Got six creatives? That is two 322 ads, not one six-creative ad. Now give both 322s the same headline and primary text and watch spend across the pair:

  • If the same copy dominates in both ads → the copy is doing the work. Real signal.
  • If the copy that wins differs between the two → the copy is not the reason either ad is winning or losing. The creative is.

Charley notes he doesn't see anyone else teaching this. It is a genuine multivariate read with no extra spend.

Writing the copy

Charley The structural facts that dictate how you write:

ElementConstraintJob
Headline40 characters max. Not shown on Instagram at all.Connects the creative to the offer, drives the click. If your headline has to win, remember half your placements never render it.
Primary text125 characters before “see more”The connective tissue. Provides context and previews the landing page — continuity is what converts the click into an action on the page.
Eye path (Facebook)Creative → headline → back up to primary textWrite in that order of priority.

The above/below-the-fold play: treat primary text as a conversation. What shows above “see more” is the hello; what sits below it is the close. If a detail would drive some people away but convert the right ones, put it below the fold deliberately. Charley used to put a free Facebook-group link below the fold and says it built communities of over half a million people.

Voice: the ad should sound like you if you're claiming authority, or like them if you want the customer to see themselves. Ads that do each job, running together, work well as a pair. His hard rule: “Do not sell to yourself. It's the single biggest mistake everybody makes.”

Where Becker simplifies

Becker runs the same structure with one deliberate reduction: “that Charley YouTuber I mentioned, he's going to do this process called 322 a lot… I just like to do three different creatives. I don't really test the headlines and descriptions. I like to keep it even simpler.”

So: 3 creatives, fixed copy. Fewer moving parts, no multivariate copy read. Charley's version extracts more information from the same spend; Becker's is faster to produce. If you are copy-constrained rather than creative-constrained, Becker's version is the pragmatic start.

07The Olympic Rings: five ads that do five jobs

Charley's answer to “what should the ads in my control ad set actually be?”. Five concepts, each with a defined role, deliberately connected. This is what real creative diversity looks like in practice.

FIVE CONCEPTS · EVERY AD HAS A JOB · ALL RINGS PURPOSEFULLY CONNECTED RING 1 Prospecting the problem RING 2 Prospecting the mechanism RING 3 Prospecting the trigger RING 4 Retargeting second touch for 1 + 2 RING 5 Retargeting second touch for 2 + 3 COLD fill the funnel WARM close the loop The connection rule is the whole point. Ring 4 is built as the logical second touch for whoever saw rings 1 or 2. Ring 5 is the second touch for rings 2 or 3. Same core message, rebuilt for someone who has already seen it. That overlap is why the rings interlock rather than compete — and it is why “every impression teaches Andromeda which sequence of ads works on which person”.
The Olympic Rings. Source: Charley T, 2026-05-11 and 2026-07-18. Five ads, not hundreds. “A small team where every ad has a job.” These are the ads that populate the control ad set in §5.

Broad retargeting, not pixel-event retargeting

Charley Rings 4 and 5 are retargeting, but not the kind most people run — and this distinction is worth real money.

“Funnel-based retargeting chases people who already said no. Most cart abandoners and checkout droppers already decided not to buy… If somebody's abandoning cart on your site, they're probably abandoning cart on a couple of your competitors' sites too.”

Charley T · 2026-04-09

His arithmetic: of 1,000 people who engaged with you, maybe 100 abandon a cart and maybe 10 of those will convert. You can spend your whole budget on those 100 — 90 of whom will never buy, and all of whom are being spammed by every competitor, in a high-bid auction — or you can reach all 1,000 interested people including the same 10, for less money, and probably get 12 or 13 sales instead of 10.

Broad retargeting also compounds: the pool grows every day from your organic reach and content without you raising budget, so it “never runs out of high-quality, ready-to-buy customers.”

Applied to lead gen

The five rings for a lead-gen system

Charley's ring definitions are deliberately abstract. Here is the mapping I'd use for an advisory or service business, following his connection rule exactly:

  • Ring 1 — the problem. Name a gap the prospect hasn't quantified. No product, no offer.
  • Ring 2 — the mechanism. Your named, new process. This is Becker's “new” carrying the load.
  • Ring 3 — the trigger. The life event that makes it urgent right now. Highly identity-specific.
  • Ring 4 — proof (second touch for 1 + 2). A named client outcome. Answers “does this actually work for people like me?” — the natural next question after seeing the problem or the mechanism.
  • Ring 5 — objections (second touch for 2 + 3). Handles what they are currently doing instead: existing cover, the bank's offer, “I'll do it later”. Answers the question that follows the mechanism or the trigger.

Note that rings 4 and 5 are Becker's ads 5 and 6 almost exactly. The two frameworks converge here.

08The ad sequence, slot by slot

Becker publishes his actual template — the one he cookie-cutters across every buyer profile at Hyros. It is the most concrete “what ads do I make” answer in either source, so it's reproduced here in full.

COLD · PROBLEM UNAWARE WARM · DECIDING SLOT 1 UGC video — the problem You, talking to camera. Educate on the problem, mention the product loosely. Run 3 hooks here as a flex ad to find the one that agitates most. SLOT 2 Static — winning hook Once slot 1 names the winning hook, build a static around it — and build the rest of the funnel around it too. SLOT 3 Same problem, second benefit Becker's example: the same problem framing, but leaning much harder on ROAS than on CPA. SLOT 4 The offer — straight up “The first retargeting ad, which is just a straight-up offer in what we do.” SLOT 5 Client result Named testimonial, and break down what you actually did. Also make a static version of the same results. SLOT 6 Objection handler Go through everything they're currently doing that's wrong, and what you fix. Simple big-text static works here. Mix formats across the sequence deliberately. “I want to hit people with static ads and I want to hit people with video ads.” Video does the teaching; statics do the reminding. “These things are constantly running and the person's constantly in this laundry machine of convincing, not just one ad at any time. No one sees your B2B offer and just knee-jerk buys.”
Becker's six-slot template. Source: Alex Becker, 2026-08-07. Note the sequence logic: educate on the problem → show how the product fixes it → make the offer → prove it → dismantle the alternative. It is a sales script distributed across six ads.
Both

Where the two templates meet

Becker's slots 1–3 are Charley's rings 1–3 (prospecting: problem, mechanism, trigger). Becker's slots 4–6 are Charley's rings 4–5 (retargeting: offer, proof, objections). The frameworks are the same object described from two directions — Charley from delivery mechanics, Becker from sales-script logic. Build against either; you will land in the same place.

09Creative enhancements: the traffic light

Meta bundles genuinely useful delivery optimisations together with features that silently rewrite your marketing. Charley's dedicated guide sorts all eleven core enhancements into three buckets. This is the highest-value-per-minute section in the manual — most accounts are leaking money here without knowing.

THE ELEVEN CORE ENHANCEMENTS FOR CONVERSION CAMPAIGNS RED · NEVER They don't optimise your ad — they change it. Text generation Enhanced CTA 3D animation YELLOW · CONDITIONAL Powerful only if you gave Meta the right assets to work with. Music Image expansion Text improvements GREEN · LEAVE ON They work with your creative. They never touch your copy. Visual touch-ups Brightness & contrast Relative comments Sitelinks The underlying rule: confidence and enhancement are inversely related NO IDEA WHAT WORKS KNOW EXACTLY WHAT WORKS Turn everything ON. Let the machine fish. Turn variation OFF. Stay in control. “These enhancements basically make every ad a C+ ad.” If you're failing, that's a massive win. If you're crushing it, they slow you down and waste money.
The enhancement traffic light. Source: Charley T, 2026-07-25. The classification logic is consistent throughout: green enhancements change delivery; red enhancements change marketing.

Why each red is red

EnhancementWhat it doesCharley's objection
Text generationWrites new headlines and primary text from your copy or site“It doesn't understand compliance, and it definitely doesn't understand the nuance that made your ad work in the first place.”
Enhanced CTAMeta swaps your button“Shop now has a whole bunch of data behind it. I want to leverage that data” — not have the algorithm decide there's a better option later.
3D animationInvents movement in a static image“Most of the time it just makes your ad look fake and cheap.”

Why each yellow is conditional

  • Music — fine on a silent product video. Not fine if you chose music or have a voiceover; the choices are dynamic and can be badly off. Charley's example: a friend's pet-urine-cleaner ad ran in India with “some of the most offensively generic AI music possible”, and wasted a lot of money.
  • Image expansion — brilliant on a product on a clean white background. Destructive if your product touches the frame edge or the image is busy: the AI invents the missing pixels and you get warped product and “strange third-hand stuff in the backgrounds.”
  • Text improvements — different from text generation, and easily confused. Meta can move your primary text into the headline and vice versa, rewrite sections, or change the emphasis of your message. Set up “restricted words” before you tick this box — it tells Meta which words, phrases and claims it may not generate or move.
Conflict — Charley contradicts himself

In the April/May multimedia-workflow walkthrough he says: “Yes to visual touch-ups, to relevant comments, to brightness and contrast, and yes to dynamic descriptions. And I highly, highly recommend that you avoid enhanced CTAs, overlays, anything to do with image or background or text music, and never the sitelinks.”

In the dedicated 2026-07-25 enhancements guide, sitelinks are green: “This gives people more ways to navigate your website directly from the ad. I use them everywhere that's not my hero offer.”

Resolution: take the later, dedicated guide — it supersedes an aside in an earlier video, and it carries the qualifier that matters. Sitelinks on, except on your hero offer, where you don't want to give people an exit from the one action you're paying for. Also note “dynamic descriptions” appears in the earlier yes-list but is not among the eleven in the traffic light; treat it as unclassified.

Four traps that catch almost everyone

Enhancements apply at the AD level, not the image level

Upload three creatives and every enhancement applies to all three. One image looking great is no evidence the others do. Preview every asset individually.

Settings survive duplication

“If you duplicate ads or bulk edit campaigns, go back and check your enhancements. Meta can carry those settings across automatically” — Charley has seen advertisers running enhancements they didn't know were enabled.

Always preview across placements

Feed, Stories, Reels — the big three. “Just because it looks good in one placement doesn't mean it looks good everywhere.” The more you customise, the more likely something is broken.

Check your crops before publishing

Hover the media, click crop, and check square, vertical and horizontal. Meta auto-adjusts but you should verify. “It's really easy to speed run through this one step and waste a ton of money on ads that will never work.”

Charley

The one time he breaks his own red-light rule

He turns text generation on in exactly two situations, both of which are “I don't know what works, so let the machine tell me”:

  1. Nothing is working. Brand new account or business, or you've tried a lot of ideas and none land. Activate text generation plus the AI image tools: “I'm essentially telling the machine — I don't know what works, but you have a ton of data around every buyer in my entire niche and all my competitors, so can you figure it out for me?” He says this works especially well for print-on-demand and mom-and-pop shops running nothing but product images.
  2. A new offer inside a business that already works. You know ads work here, you just don't yet know how to position this particular offer socially.

10Meta's native AI creative — and why it beats your prompt

Charley's most actionable near-term edge, and the one with the clearest mechanism: Meta's in-platform generation isn't just an image tool, it is a tool with access to what is already converting in your niche.

“It's not just learning from your own account. It's referencing what's already converting across your entire niche. Instead of guessing which angle is going to land, the AI already has a read on what's actually working inside your market right now. That is a wildly unfair advantage.”

Charley T · 2026-07-07

Inside the generation tab you get a “popular in your niche” section and a performance-based section sorted by return on ad spend — built from what everybody else running ads in your category is winning with. Charley's stated best practice: take one variation from each section and “essentially be able to print three 322 ads from right here alone.”

The build, start to finish

  1. Paste your product/landing page URL as the source
  2. Add your own product shots as permutation seeds
  3. Scrape your own landing page for the primary text
  4. Leave the headline blank — Meta pulls it from page metadata
  5. Generate images; select from the niche/high-ROAS sections
  6. Hit next — it generates video, including UGC-style, in styles that work for your niche
  7. Prune ruthlessly. “Don't just blindly trust artificial intelligence.”

Brand Memory

Solves the standard complaint that AI ads don't feel like your brand. It learns your rules, tone, voice and what to avoid, so generations stay consistent at scale without you policing every one manually.

The text-artifact fix

When generated text goes weird on the product — the most common AI failure — download it, hand it plus your real product shot to Gemini to repair, magic-erase the leftover in Canva, re-upload. Charley's point: minor work, because you are not testing hundreds of these.

Charley

Per-combination control — the update he calls Pandora's box

Previously every variation in a flex/dynamic ad shared the same settings. Now you can customise crop, placement, copy and destination URL per combination inside one ad. Direct consequences he names:

  • Put one creative in feeds but not in reels; different variations for Instagram vs Facebook
  • Route each creator's creative to that creator's own dedicated landing page — three creators, three funnels, one ad
  • Named for lead gen specifically: “Instagram mobile traffic behaves very differently than Facebook desktop. You can control platform and placement and then route that traffic to a dedicated user experience.”
  • Per-element reporting is back — “we haven't seen this since iOS 14 and now it's standard”

Becker's creative testing: vary the presentation, never the pitch

Becker A materially different — and complementary — use of AI video. His rule is that mass generation is the mistake; the win is sniper-placed variation of a proven winner.

LOCKED — THE PITCH The winning hook + the script Already proved it earns spend. Do not touch a word of it. VARIED — THE PRESENTATION (AI-GENERATED, e.g. Seedance) at the desk on stage on a podcast interviewed on the street in a desert in a panda suit Test 3 at a time in ONE flex ad, in a separate ad set, vs the original Winner only → swapped into the live system. Everything else is discarded, never accumulated. “I already know the pitch… now I want to find the video format or the video style that's going to hook them the most.”
Presentation testing. Source: Alex Becker, 2026-08-07. Why it works: the pitch is the variable that already passed its test, so isolating presentation is a genuine single-variable experiment — Charley's scientific-method rule (§13), executed with generative video. Becker's own read: “These usually do much better than the original ad.” His authority heuristic for choosing contexts — “have you ever seen Alex Hormozi speaking on stage in his ads? That looks authoritative.”
Becker

He names this as his own former mistake

“That's what I was doing at first. I'd just go and mass produce Seedance ads, throw them in there, and then optimise based around the one that got the calls and was getting the biggest view-throughs and the ROAS. That doesn't make sense, because again — the system is what matters.”

The generative tools do not change the doctrine. They make it cheaper to execute a small number of deliberate tests, not permission to flood the account.

11Reading the data: the 4PI analysis

Four metrics, read together, tell you what job Meta has assigned each of your ads — and therefore which ad to kill and which gap to fill. Charley calls this turning Ads Manager into a decision engine. It replaces staring at ROAS columns.

Charley The four are spend, frequency, CPM, cost per result (§1 explains what each means mechanically). You read every ad's four numbers relative to the campaign average, and the resulting signature identifies the ad's role.

THREE SIGNATURES · ALL VALUES READ vs CAMPAIGN AVERAGE HEALTHY · UPPER FUNNEL A great prospecting ad SpendABOVE ▲ FrequencyBELOW ▼ CPMBELOW ▼ Cost per resultABOVE ▲ High CPR is normal and correct here — it did the heavy work early. Low CPM means it's a genuinely good attention experience. HEALTHY · LOWER FUNNEL A great closer SpendMEANINGFUL FrequencyABOVE ▲ CPMABOVE ▲ Cost per resultBETTER ▼ Should be the highest-spending thing with above-average CPM and frequency. Not just enough spend for one or two sales a week. RED FLAG · THE LIABILITY Loved by the machine, bad for the business SpendHIGH ▲ Cost per resultBAD ▲ “Amazing at attracting the wrong kind of attention.” It gets distribution but pulls in people with no intent to buy. Variant: high freq + high CPM + CPR no better than prospecting = fake closer. The judgement that matters A high cost per result is only a problem when the ad has become a liability relative to the spend it is taking. Expensive prospecting that fills the funnel is an investment. Expensive prospecting that eats 40% of budget and returns nothing is a leak. Same number, opposite decision — which is exactly why cost per result cannot be read on its own.
The three signatures. Source: Charley T, 2026-07-18. Build these four columns into a saved view and read them relative to the campaign average, never against an external benchmark.

What the analysis tells you to do — only two outcomes

1

Optimisation by subtraction

Charley The fastest way to scale results, and where you start if you are running more than about eight ads. Find the ads taking meaningful spend with clear red flags and turn them off. Budget naturally flows to the ads doing the job — you scale the winners without touching the budget.

Constraint: never turn off more than 20% of spend in a single day. Turning ads off is a budget change.

2

Fill the gaps

Charley No clear red flag means you don't have a pausing problem — you have a coverage problem in the funnel. Three diagnostic patterns, each with a specific prescription:

What you observeWhat it meansWhat to test
Everything looks fine until you raise budget — then CPM, frequency and CPR all worsen togetherYou aren't filling the funnel effectively enoughStronger upper-funnel ads. New prospecting concepts, ring 1–3 territory.
When you scale, one prospecting ad soaks up all the spend and CPR gets steadily worseAn ad people love to watch that attracts the wrong attention at scaleReplace or iterate that specific ad. Not budget tweaks, not bid changes — give the machine better choices.
Nothing in the account behaves like a lower-funnel ad that earns spendYou have no closerBuild a second-touch version of your strongest prospecting idea. Same core message, built for someone who already saw it.
Rule 05 · Charley “Your job isn't to find one winning ad and abuse it until it breaks. Your job is to get ads that are working together so the system stays balanced, profitable and scalable.” The 4PI exists to answer one question — can I spend more money? — and to tell you which player to substitute when the answer is no.

12The profit metric — and its lead-gen translation

Charley's replacement for ROAS is the smallest change in this manual with the largest consequence. It is also the piece that needs the most careful translation for lead generation, because a lead has no immediate revenue.

Gross profit per transaction (GPT)

Charley ROAS is a ratio. It can look excellent while you make less money. GPT is the money.

THE SAME PRODUCT · TWO ADS · WHICH ONE DO YOU KILL? AD A ROAS4.0× CPA$10 AOV$40 GROSS PROFIT $30 per transaction AD B ROAS2.0× CPA$60 AOV$120 GROSS PROFIT $60 per transaction Half the ROAS. Double the profit. Optimising on ROAS kills Ad B. “You can't pay bills with a ratio. You can't buy whiskey with fractions. You need currency.”
GPT vs ROAS. Source: Charley T, 2026-05-04 and 2026-07-18. Build GPT as a custom metric in your dashboard. The evaluation question for every ad becomes: is this ad's GPT above campaign average? If not, it is a candidate for replacement.

Charley Only four numbers are needed: what you spent, what it cost to get a sale, what that sale was worth, and how much profit you made. “For every ad you look at, stop asking ‘what's the ROAS?' and start asking ‘how much profit did this make?'”

Applied to lead gen

Gross profit per lead (GPL)

Neither source gives a lead-gen profit formula. This is my construction, built from three things they do say: Charley's GPT logic, his warning that in “lead gen, cheap leads don't mean good customers”, and Becker's insistence on optimising toward verified qualified outcomes rather than form fills.

GPLad  =  ( P(closed | lead from this ad)  ×  gross margin per closed deal )  −  CPLad

The critical term is the first one, and it is the term almost nobody measures per-ad: two ads with identical cost per lead can have completely different close rates, and the cheaper one is frequently the worse one. That is precisely the failure Charley is pointing at when he says cheap leads don't mean good customers.

What this demands operationally: your CRM outcome must be joined back to the ad that produced the lead. Without that join you cannot compute GPL, and you are back to optimising cost per lead — which is optimising the wrong thing. §15 is how you build that join.

The same test applies: is this ad's GPL above campaign average? If not, it is the worst player and it is the one you replace.

The one question that governs everything

Charley Every framework in this manual reduces to a single test, and he repeats it in four separate videos:

“Can I spend more money tomorrow?”

If yes — you're winning. Don't fix what isn't broken. The single worst thing you could do is launch new ads. Just keep scaling.
If no — that, and only that, is when you test creative.

How to judge any test

Charley Not by CPA, ROAS, CTR or hook rate — those are diagnostics. Did the campaign's total profit volume go up? Total revenue minus total ad spend. If yes, you created more money to reinvest, so scale the budget. If no, the test is a loser. That is the whole judgement.

“It doesn't matter if any of your new ads are winners or if your ROAS goes from two to twenty. If profit didn't go up, it's a loss. Only the business outcome matters, because it's not about any individual ad — it's about the whole team.”

Charley T · 2026-05-04

Hunters and farmers

Charley The framing that explains why operators resist all of this. Hunters measure success by ROAS and daily CPA — did this ad work today? They live and die by short-term swings. Farmers focus on total profit and growth: build a system, protect it, and scale it with the resources the system generates for itself.

His argument for why farming compounds: one corn plant produces three or four pounds of food, and from what you don't eat you can plant ten more. Same work, but over time you go from four pounds to four hundred — because you invested in the system rather than the harvest.

13The testing loop

Creative testing has one purpose, and it is not finding winners. “The purpose of creative testing is not to find a winner. It's to build the best team.”

LAUNCH THE TEST 322 → WAIT → RUN THREE CHECKS IN ORDER STEP 1 · DELIVERY Did the ad earn spend? NO → the ad isn't competitive. Dead on arrival. Start over. YES → proceed to step 2. STEP 2 · EVALUATION Did profit volume go up? UP → winning, regardless of what any individual ad metric says. DOWN → loser. Start over. STEP 3 · SCALE Raise the budget. Keep scaling until profit volume stops improving — then you're back to testing. the loop — you never exit it, you only change which rung you're on THE HARVEST — WHAT TO DO WITH A WINNER When one combination inside the 322 dominates spend, that is your winner. Do not shut the ad down — take the winning post ID and introduce it into the control ad set alongside your other proven ads. Replace nothing yet. Then ask one question: did the new ad make the campaign better? Yes → keep it. No → turn it off. No grey area.
The testing loop. Source: Charley T, 2026-05-04 and 2026-07-18. “The worst thing you can do is interrupt something that's already winning.” Harvesting moves the winner without breaking its learning.

One variable at a time

Charley When the answer to “can I spend more?” is no, you run the scientific method, not a brainstorm. Start with the control — the system you know works, even if not well enough. Then change one variable until it does: a new hook, a new testimonial, a different objection handled.

“Don't change three things at once because you'll never know what actually fixed the problem.” And the target is modest by design: you are not looking for a perfect ad, you are looking for one small improvement that gets you back to “yes, I can spend more money” without performance breaking.

Charley

Choosing what to test — ask the rings

Instead of launching random new ideas, look at your five rings and ask one question: which one of these isn't doing its job? The 4PI gap patterns in §11 answer it for you. That is the entire test-selection process.

Rule 06 · Becker Test in a separate ad set, never in the live system. “Instead of testing all of them inside my main campaign or my main ad set and then flustering up the funnel, I'm just going to slap the winner in there and let it compete with the top ad.” Protect the working system from your experiments.

14Scaling: three stages, in order

“Why is it that every time you increase the budget, your performance tanks? Because scaling isn't one move, it's a system, and there's a specific order it has to happen in.” Most operators skip straight to stage three.

“Think of it like building a house. You don't put the roof on before the walls are up — but that's exactly what most advertisers do. They go straight to the budget before the foundation is even there.”

Charley T · 2026-07-18

Stage 1 — Efficiency (never budget)

Charley Growth does not come from spending more. Adding spend without adding profit is not leverage. The question is how do we make every dollar produce more?

1

Track profit, not platform metrics

Four numbers only: spend, cost per sale, value of that sale, profit (GPT). Add GPT to your dashboard.

2

Find the leak

Look at the ads spending the most money and identify the ones making the least profit per sale. That is where the immediate leverage is.

3

Pause the worst performers

The easiest way to scale profit today without extra work. Never turn off more than 20% of spend in a day — turning ads off is the same thing as changing the budget.

Stage 2 — The readiness check

Charley “Feeling profitable and being ready to scale are two very different things. Budget amplifies what exists, so you need to know exactly what you're amplifying before you touch it.” Three gates, all must pass:

  • Are CPA and GPT relatively stable? If no, stabilise first.
  • Are there more bad ads you could remove? If yes, keep optimising — create as much leverage as possible first. You don't want to scale bad ads.
  • If your CPA increased 10–20% tomorrow, would you still be profitable? If no, you have more work to do. If yes, you may begin to scale.

Stage 3 — Budget, using one of three methods

Charley Choose by answering three questions: how stable is the system, how confident are you in the performance, and how aggressive do you want to be?

DAILY BUDGET OVER TIME — THREE METHODS TIME → BUDGET LINEAR FRACTIONAL MARGINAL only when earned flat — CPA above target pulled back LINEAR · +$10–50/day, fixed +$10/day → over $3,000/day more in a year FRACTIONAL · +2%/day, compounding 6× your daily budget in 90 days MARGINAL · only when performance earns it 7-day CPA below target → raise, capped by margin
Three scaling methods. Source: Charley T, 2026-07-18. Charley's own favourite is marginal — the account scales itself when performance is good enough to deserve it. His worked rule: “if my target CPA is $50 and I'm currently coming in at $45, I can scale by 5% — and if I get no additional sales, I'm still profitable.”
MethodMechanicAdvantageDownsideRight when
LinearAdd a fixed amount on a schedule ($10–50/day)Stability. Each increase becomes a smaller % of the total, so the system gets more stable over time.Slow by designThe system is stable and protecting that stability matters more than growing fast
FractionalIncrease by a percentage on a schedule (~2%/day)Speed. Every increase is bigger than the last; the bigger the budget, the faster it compounds.Volatility. The system has far less time to absorb each increase.You are dramatically beating your goal
MarginalRaise only if trailing-7-day CPA is below target, capped by what margin allowsSelf-governing. Scales when earned, holds when not.Requires a mature system and a clearly defined target CPATarget CPA is clearly defined and you want the account to scale itself

Charley Use automated rules for all three. Linear and fractional get you to the next level, but eventually results plateau and you have to turn those rules off — which is when you move to marginal.

Scaling down without killing your winners

Charley Your CPA jumps 30% overnight and every instinct says fix everything. Three steps, in order:

1 · OPTIMISATION Not budget. Ads. Find the worst GPT and turn it off. Let budget reallocate to the strong. “Nine times out of ten the problem isn't the budget.” 2 · EVALUATION Is it actually broken? Act only when performance is clearly and consistently out of range. Don't react to bad days. If every week is better, it's noise. 3 · REDUCTION Half the speed you rose. Scaled +10%? Cut 5%. Added $50/day? Pull back $25. Then don't touch anything for 48–72 hours.
The scale-down protocol. Source: Charley T, 2026-07-18. “Let the spend redistribute. Let the strong ads take over. Let performance tell you what it wants.”

15The signal layer — where lead gen is won or lost

Both operators converge hard here, and for lead generation this is the single highest-leverage section in the manual. When the machine controls targeting, the only lever left is the quality of what you feed it.

“The more control Meta takes over the mechanics, the more important your inputs become. Your data, your exclusions, your customer definitions, your measurement and your economics. The machine is going to get better and better at showing the right ad to the right person, but it can't fix a bad business.”

Charley T · 2026-06-28

Optimise for the outcome, not the event

Both The most important sentence in this section, from two directions:

  • CharleyStandard events are for entry-level marketers. Optimise for custom conversion events that represent your most valuable customers.”
  • Becker “I push back to people that actually attend calls and are verified by our team as qualified leads — not just the form fill, which a lot of people do… If you start optimising for people that show up for calls, you're going to get so many more qualified calls in.”
THE LEAD-GEN SIGNAL LADDER — CLIMB AS VOLUME ALLOWS Form fill / Lead The default. Optimises for people who like filling in forms. HIGHEST VOLUME · LOWEST MEANING Contactable lead Phone answered or email verified. Strips out the junk tier. Qualified lead A human confirmed they fit. Becker's explicit floor for lower spend levels. Appointment attended Not booked — attended. Booked rewards no-shows. Closed / issued The real outcome. Often too slow and too sparse to optimise on directly. Predicted high-value lead — the shortcut past the wait LOWEST VOLUME · HIGHEST MEANING CLIMB AS VOLUME ALLOWS Each rung up: • fewer events • slower feedback • far better targeting Climb too early and you starve the machine of events entirely.
The signal ladder. Applied — the ladder itself is my construction, but every rung is named by a source: Becker on qualified/attended calls and predictive value, Charley on custom conversion events and volume thresholds. Becker's constraint: “you have to have a lot of call volume to do that. And at the lower level, qualified calls.”

Front-loading: the predictive-value shortcut

Becker The problem with optimising toward closed business is time. A year of value data takes a year. His answer is to predict it from early behaviour and feed the prediction in immediately.

“You can look at the type of mobile phone, the type of information the customer's doing, the thing they first buy, and then predict their total value over the next year. Then they feed that total value into Meta and say optimise for that… To get that data, a year's worth of data would take a year — that's impossible. But if you're able to front-load all that data in, it gets so much better at targeting right away.”

Alex Becker · 2026-08-07

His simpler variant for lower volume: forget predicted dollar values and make it binary. A custom event called high-value customer, fired only for profiles predicted to exceed a threshold. “You only push that back as a conversion.”

Read this with your eyes open

Becker is CEO of Hyros and the tracking half of this section is also his sales pitch — he says so himself, repeatedly and cheerfully. Two things are worth separating:

The mechanism is sound and vendor-neutral. Meta's browser-side tracking is blocked by browsers and phones, breaks across devices, and doesn't reliably persist past 7–30 days. Feeding server-side outcome data back is standard practice. Becker's own line: “I don't give a damn if you use Hyros or not. But you better find a way to fix it, period.”

The specific numbers are marketing. “15–20% ROI lift” is his product claim, not an independently verified figure, and it appears inside ad copy he reads aloud in the video. Treat it as a hypothesis about your account, measurable by you, not as a benchmark.

Conversion goal is not attribution

Becker The reframe that makes the rest of his advice make sense — and the one most likely to feel wrong at first.

“Your conversion goals inside your account are not your attribution… They're using it as a data source. So even if Google got the last click, they make sure to go in and find the last click that was associated with Facebook and still slap it on there. That's not accurate reporting — that's why you do your reporting elsewhere.”

Alex Becker · 2026-08-07

The logic: the pixel's job is to train targeting. If Meta genuinely influenced a conversion but didn't get the last click — someone saw four Facebook ads, then searched your brand and converted through Google — then withholding that event from Meta teaches the algorithm that its ad failed. You are training it on a lie of omission. His example is his own: people arrive from his YouTube videos carrying Facebook clicks in their profile that Meta never attributes.

Both

Keep two sets of books, deliberately

Both operators land in the same place from different vocabularies. The pixel is a training input. Your source of truth is a separate column.

Charley: “You need one strong source of truth for new-customer actions. It needs to be a column in your ad account… and you need a third-party tool to do this, even if it's Zapier.” He names Elevar, Popsicle and Blodata as options and explicitly doesn't care which.

Becker: his North Star is his own tracked, verified calls; the in-platform conversion metric is “the gee-whiz information”. Charley's warning completes it: “If you optimise for new customers but measure blended CPA, you're going to be wrong about all of your data every single time.”

Customer lifecycle strategy and exclusions

Charley An ad-set-level setting — “and the fact that it lives here is the whole point. This isn't a creative tweak… it's a delivery strategy decision.” Selecting acquire new customers is only step one; the exclusions do the real work.

Both sides of the exclusion

Customer list = your back-end truth. Website purchase-event audiences = your pixel truth. Charley: “The biggest mistake here is relying on one-week signal.” Purchase custom events now support retention windows up to 730 days.

But don't reflexively choose the longest window. A consumable buyer from 60 days ago is still an existing customer; a mattress buyer from 18 months ago is basically cold again. “Choose the window that matches your actual customer lifecycle. It's in the name of the product.”

Tiered, not blunt

Don't use one giant “customers” bucket. Separate lists for: customers vs leads, high-value vs low-value, one-time vs repeat, refunded/chargeback/disqualified vs good.

The nuance that stops you over-correcting: “Just because somebody spent a penny before doesn't mean they can't spend a hundred dollars later. Don't build exclusions that permanently block low-value customers. Just exclude the high-value ones. That's how you get more new high-value people.”

Charley

Signal hygiene — the boring part that gates everything

  • Match score of at least 8.5. “If it's not at least an 8½, you have work to do.”
  • Strong identifiers — not just email. Phone and mobile ad ID too.
  • Update lists frequently and dynamically. “A stale list is not a source of truth. It's a historical artifact. It's a retroactive report card.”
  • Expect a halo. Pushing Meta to find people who weren't already on the about-to-buy path produces ripples across search and email. Don't judge it on day one — “it won't be nearly as good at the end of the first week as it will be at the end of the first month.”

When to actually turn lifecycle optimisation on

Charley His spend tiers, verbatim in substance. Note how conservative he is — this is a rare case of an operator telling you not to use the new feature.

Daily spendRecommendationReasoning
≤ $100Set it all up, but don't optimise for new customers. Use the new-customer event as a dashboard column only.Not enough volume. “You'll pay a really high premium in learning costs that probably won't show up as profit.”
$100–500Testable, but “still a bit of a luxury item”. He'd wait.“Let bigger spenders train the system and use all of their money to help Meta get a lot smarter. First adopters pay a lot more. You don't have to.”
$1,000–2,500Worthwhile if you have robust incrementality measurement and a clearly defined most-valuable customer you can measure.“This is where the feature can actually become a strategic lever, not just a reporting problem.”
$2,500+Good idea — but don't rush it.

The gate that overrides the table: “If you can't measure new customers today, don't turn this on yet. Fix measurement first.”

Applied to lead gen

What “existing customer” means when you sell advice

Charley's lifecycle logic assumes a purchase event. For an advisory the equivalents are, in my reading:

  • Existing customer = client with business in force. Exclusion window should match your actual review or renewal cycle, not a default.
  • Tiered lists = clients by value; leads worked but not converted; declined or ineligible enquiries; leads who went elsewhere. The declined tier matters most — you are otherwise paying to reacquire people you already know you cannot serve.
  • Win-back window = Charley's 730-day idea applied to review cycles rather than repurchase.

None of this is stated by either source for advisory businesses. It is the obvious mapping, and it needs testing.

16Worked example: an NZ life-cover lead-gen system

Standing caveat for this entire section

The business is fictional. Every dollar figure is invented and illustrative — neither source discusses insurance, New Zealand, or advisory economics. The arithmetic demonstrates the shape of each calculation; substitute your own numbers before acting on any of it. The offer language uses guarantees and outcome claims because that is Becker's doctrine; guarantees and outcome claims about insurance in New Zealand are a regulated-advice question and need a compliance review before anything ships.

The scenario: a small NZ life-cover advisory. Revenue is commission on policies issued and staying in force. There is no e-commerce transaction, no AOV, no ROAS that means anything. This is the hardest case for everything above — which is why it is the useful one.

Step 1 — Build the offer before the account Becker

Run the five-part test. What most advisories actually run — "Get a free life insurance quote. We compare NZ's leading insurers." — fails four of the five.

TestThe typical advisory offerRebuilt to Becker's spec
New?No — every competitor says "free quote, we compare insurers"A named mechanism: "The 12-Minute Cover Gap Check". A specific process with a name they haven't heard.
Result?No — "a quote" is a step, not an outcome"Know the exact dollar figure your family would receive if you died tomorrow — and what it should be costing you."
Without effort?No — the form is the effort, and it's the objection"You answer six questions. We do the comparison across every insurer we're accredited with and bring you the answer."
Proven?Usually a logo barNamed, specific client outcomes with real numbers. You must supply these — they cannot be invented.
Guaranteed?Nothing"If your current cover is already right, we'll tell you to keep it and you'll have lost twelve minutes." compliance review
Applied

The high-ticket layer for an advisory

Becker's 1-in-100 rule says the same 100 visitors will produce one buyer of a $2,000 total solution about as reliably as ten buyers of a $50 one. An advisory can't price like that directly, but the structural move translates: offer a comprehensive engagement alongside the single-product one.

Most enquiries want life cover. A minority want the whole picture reviewed — life, trauma, income protection, TPD, plus the business ownership cover — and that engagement is worth several times a single policy in commission. Becker's argument is that you capture the small number who want everything and the majority who want one thing, from the same traffic, if you build both paths into the same page. Most advisories build only the second.

Step 2 — Define buyer profiles by problem, not demographic Becker

Applying the §5 decision rule: a genuinely different problem, needing a genuinely different landing page.

Profile A — New mortgage

Problem: just took on the largest debt of their life and the bank offered them something at signing that they didn't understand.
Hook territory: the debt, not death.
Objection to beat: "the bank already sorted it."

Profile B — New parent

Problem: a person now exists who cannot feed themselves.
Hook territory: the number of years until the child is independent.
Objection to beat: "we'll do it when things settle down."

Profile C — Over 50, premiums stepping

Problem: a policy bought decades ago is now repricing hard and they're considering dropping it.
Hook territory: the step-up itself.
Objection to beat: "it's too expensive to be worth keeping."

Profile D — Self-employed / contractor

Problem: no employer cover, and income stops the day they do.
Hook territory: income protection more than life.
Objection to beat: "ACC will cover me." (It won't, for illness.)

Charley

But do not build four campaigns on day one

Becker runs each profile at $100–200/day, so four profiles means $400–800/day minimum. Below that, Charley's budget ladder governs: one campaign, one ad set, all four hooks as separate ads inside it. Let delivery tell you which two profiles are real before you split. Splitting early is the most expensive mistake available in this section.

Step 3 — The launch architecture

LAUNCH — RUNG 1 OF THE BUDGET LADDER · ONE CAMPAIGN · ONE AD SET CBO CAMPAIGN · OBJECTIVE: LEADS · CONVERSION EVENT: QUALIFIED LEAD (custom) SINGLE AD SET — CONTROL AND TESTS LIVE TOGETHER AT THIS BUDGET RING 1 · PROBLEM “Most NZ families are covered for a number RING 2 · MECHANISM “The 12-Minute Cover Gap Check, explained” RING 3 · TRIGGER “Just signed a mortgage? Read this first” RING 4 · PROOF Named client outcome 2nd touch for rings 1+2 RING 5 · OBJECTION “The bank sorted it” 2nd touch for 2+3 EACH RING IS BUILT AS A 322 3 creatives (all one format) · 2 headlines · 2 primary texts = 12 combinations per ring Enhancements: green set ON · sitelinks OFF on the hero offer only · text generation OFF (you know your compliance constraints) ONE LANDING PAGE PER HOOK — CONTINUITY WITH THE PRIMARY TEXT Two-step capture: email from everyone (step 1) → booked check from the ready (step 2) Plain and clear beats beautiful — Becker's ugly page outconverted his animated one CRM OUTCOME → SERVER-SIDE EVENT → BACK TO META Qualified · Attended · Issued — joined to the originating ad. Without this join there is no GPL and no real optimisation.
The launch build. One campaign, one ad set, five ring ads each built as a 322, one page per hook, and a closed signal loop. Structure per Charley (§5, §7); page and capture logic per Becker (§3); signal loop per both (§15). Every number and hook here is illustrative.

Step 4 — The economics, shaped correctly

Applied This is the calculation the whole manual exists to enable. All figures below are invented.

Two ads, identical cost per lead, opposite value

illustrative numbers
 Ad R1 — “the problem”Ad R3 — “just signed a mortgage”
Spend$1,500$1,500
Leads6050
Cost per lead$25.00 ← “the winner”$30.00 ← “the loser”
Qualified rate35% → 21 qualified62% → 31 qualified
Attended rate (of qualified)55% → 12 attended74% → 23 attended
Issued (of attended)25% → 3 policies39% → 9 policies
Gross margin per issued policy$900$900
Gross profit$2,700$8,100
GPL (per lead)$45.00 − $25.00 = $20.00$162.00 − $30.00 = $132.00

The ad with the worse cost per lead is worth 6.6× more per lead. Optimising on cost per lead — the default for essentially every lead-gen account — kills the better ad. This is exactly Charley's ROAS-vs-GPT trap (§12) transposed into lead generation, and it is why he says cheap leads don't mean good customers.

Step 5 — What to optimise for, by spend level

Applied Combining Charley's volume caution with Becker's climb-the-ladder push. The constraint is events per week: too few and the machine cannot learn.

Daily spendOptimise onMeasure onWhy
$50–150LeadGPL, computed manually in a sheetDeeper events won't produce enough weekly volume. Charley's ≤$100/day advice: set it up, use it as a column, don't optimise on it yet.
$150–400Qualified lead (custom event, human-verified)GPL per ad; cost per qualified leadBecker's explicit floor: “at the lower level, qualified calls.”
$400–1,000Appointment attendedGPL; issued-per-attended by adAttended, not booked. Optimising on booked buys you no-shows.
$1,000+Predicted-high-value lead (binary custom event)Full GPL and cover-type mixBecker's front-loading. Fire the event only for profiles predicted above your margin threshold.
The prerequisite nobody skips successfully

Every row above requires your CRM outcome to be joined back to the originating ad and pushed server-side to Meta. Charley: “If you can't measure new customers today, don't turn this on yet. Fix measurement first.” Becker: “You better find a way to fix it, period.” Build the join before you build the second campaign.

17The 90-day build order

Everything above, sequenced. The order is derived from the sources' own dependency logic — measurement before optimisation, offer before ads, stability before budget.

WindowDoDo notGate to pass before moving on
Days
1–14
Offer and measurement. Run the five-part test and rewrite the offer until it passes all five. Build the CRM→Meta server-side join for qualified / attended / issued. Set up tiered exclusion lists and get match quality above 8.5. Build GPT/GPL as a computed column. Don't launch ads. Genuinely — neither operator's system produces a usable signal without this layer, and you will spend the whole of month two blind. You can answer, per ad, “how many of these leads closed?”
Days
15–30
Launch rung 1. One CBO campaign, one ad set. Five ring ads, each built as a 322. One landing page per hook. Green enhancements on, red off. Optimise on Lead. Don't build three ad sets. Don't run more than three creatives per 322. Don't mix images and video in one ad. Don't add ads because it feels thin. Delivery is distributing across more than one ring; frequency and CPM are stable week over week.
Days
31–45
First 4PI read. Score all five rings on spend / frequency / CPM / cost per result against campaign average. Identify signature per §11. Kill any clear liability — max 20% of spend per day. Don't test new creative yet. Don't touch budget. Don't react to individual bad days. You can name which ring is prospecting, which is closing, and which is neither.
Days
46–60
Close the gaps. Whichever of the three gap patterns you match, run its prescription. One variable at a time, in a separate test ad set. Harvest winners into the control by post ID. Don't change three things at once. Don't test inside the live ad set. Ask the question: can I spend more money tomorrow? Not yet a yes → keep here.
Days
61–75
Scale, in order. Stage 1 efficiency (cut worst GPL), stage 2 readiness (all three gates), stage 3 budget — linear or marginal via automated rules. Climb to rung 2 if the budget now supports two ad sets in learning. Don't use fractional unless you are dramatically beating goal. Don't skip the readiness gates because the week looked good. CPA and GPL stable through at least two budget increases.
Days
76–90
Climb the signal ladder, then consider splitting. Move the conversion event up a rung if weekly volume supports it. Only now, if one hook has earned its own page, proof and objections, graduate it into a Becker-style profile system. Don't split on a hunch. Don't split if it leaves either campaign unable to exit learning. A second system that is genuinely a different problem, not a different audience.

The weekly operating rhythm, after day 90

Charley's whole argument is that this should get boring. Once the system is built, the recurring loop is small:

  1. Ask the question. Can I spend more money tomorrow?
  2. If yes — scale by your chosen method and change nothing else. “The single worst thing you could do is launch new ads.”
  3. If no — run the 4PI, find the ring that isn't doing its job, test one variable against it in a separate ad set.
  4. Harvest any winner into the control by post ID and re-measure the campaign, not the ad.

That is the entire job. “Instead of day trading the ad account, people can work on their business and enjoy their life.”

18Where they disagree — and where each contradicts himself

A guide that presents two operators as one voice is lying to you. Seven genuine tensions surfaced across the ten transcripts. Four matter enough to change what you build.

1 · Campaign structure — the big one

Charley: one CBO campaign, hard ceiling of three ad sets, even at $1M/month. Consolidate so all spend feeds one learning system.
Becker: one campaign per buyer profile, each deliberately held at $100–200/day, “well below where the audience threshold is”.

Why it matters: these produce opposite behaviour at $500/day. How to resolve: the §5 decision rule — different problem and different landing page and enough budget for each campaign to exit learning. Default to Charley when any of the three is missing.

2 · Audience targeting — Charley vs Charley, and Charley vs Becker

Charley, 9 April: a detailed audience-building programme — Instagram engager seed audiences, 30-day windows, 1% lookalikes, engagement campaigns to grow the seed, and explicitly “choose original audience, not the advantage audience”.
Charley, May–July: the Andromeda One videos never mention lookalikes or seed audiences once. The structure is broad, and the argument is that creative does the targeting.
Becker: “there's no targeting anymore. You just let the AI go crazy. That's it, kids.”

Why it matters: the April video is his small-budget playbook and the later ones are his scaling playbook, so they may simply address different stages — but he never says so. How to resolve: treat the April audience-building as an audience-warming programme that runs alongside, not as targeting for your conversion campaigns. Both later sources agree conversion campaigns should run broad.

3 · Sitelinks — Charley reverses himself

April/May: “never the sitelinks.” 25 July: sitelinks are green, “I use them everywhere that's not my hero offer.” Take the later dedicated guide, with its qualifier. Covered in full in §9.

4 · How much of the 322 to actually test

Charley: 3 creatives + 2 headlines + 2 primary texts, and the two-322 copy-isolation trick.
Becker: 3 creatives, fixed copy — “I don't really test the headlines and descriptions. I like to keep it even simpler.”

Why it matters: less than the others. Charley's extracts more information per dollar; Becker's ships faster. Start with Becker's if copy production is your bottleneck, graduate to Charley's when it isn't.

Three lesser tensions, noted for completeness

  • Becker vs Becker on whether the account matters. 30 July: “nothing in the ad account that you do matters.” 7 August: an entire master course on account structure. The first is deliberate rhetoric to force attention onto the offer; read together, his position is “offer dominates, but structure is still worth getting right.”
  • Signal accuracy. Becker deliberately attributes conversions to Meta that Meta did not earn on last click — “that's not accurate reporting” — because the pixel is a training input. Charley stresses accurate truth and clean definitions. These reconcile if you keep two sets of books (§15), but the postures are genuinely different: Becker is willing to feed the pixel a useful fiction; Charley is not explicit about that.
  • Retargeting mechanics. Charley builds explicit broad-retargeting campaigns against seed audiences in April, then folds retargeting into rings 4–5 inside one campaign by May. Becker has no retargeting layer at all — “the retargeting is done inside the system itself.” The May-onward Charley and Becker agree; the April Charley doesn't.

What they agree on — the actual consensus

Worth stating plainly, because it is where your confidence should be highest:

  • Few ads, working as a sequence, beat many ads competing
  • Judge the system's profit, never the individual ad's ROAS
  • New ads cannibalise your warm audience and make old ads look worse
  • Ad fatigue is mostly self-inflicted
  • Ads only need to be ~70% right if the sequence is right
  • Optimise toward a qualified/valuable custom event, not a standard one
  • The pixel is a training input; your truth lives in a separate system
  • Landing page continuity with the ad is not optional
  • Test one variable, in a separate ad set, against a known control

19What neither of them covers

The honest boundary of this manual. These are questions you will hit in a lead-gen account that ten transcripts simply do not answer — do not let the guide's confidence elsewhere imply coverage here.

Meta Lead Ads / Instant Forms

Not discussed once, by either, in any of the ten sources. For lead generation this is a significant omission — the in-platform form versus landing-page decision is one of the first you must make. Everything in this manual assumes you send traffic to your own page, which is what both operators do.

Small markets

Neither addresses geographies the size of New Zealand. Charley's consolidation logic and Becker's “below the audience threshold” both assume large addressable pools. Whether five interlocking ads can stay non-cannibalising in a market of ~5 million is an open question — and it is the one I'd most want tested before trusting the architecture wholesale.

Learning-phase thresholds

The budget ladder turns entirely on “reliably getting an ad set out of the learning phase”, and no number is ever given. You have to determine it empirically for your conversion event and market.

Regulated verticals

No discussion of compliance constraints on claims, guarantees or targeting. Charley notes only that text generation “doesn't understand compliance” — which is a reason to leave it off, not guidance on operating inside a regime.

Attribution windows and view-through

Becker rejects last click but never specifies which window to read. Charley warns against blended CPA without prescribing the alternative view.

Creative production economics

Both assume you can produce video on demand — Becker is his own on-camera talent, Charley works with brands that have footage. Neither costs the production line for an operator who has neither.

Verification status of the sources themselves

Nothing in this manual is independently verified. It is a faithful synthesis of what two people said on YouTube, not an evidence review. Specifically:

  • Charley repeatedly cites private emails and internal Meta training documents from “friends on the Meta engineering and product teams”. These are shown on screen in his videos but are not public and cannot be checked.
  • Both men are selling. Charley promotes Disruptor Academy in every video, with price-rise urgency. Becker is CEO of Hyros and the entire signal section doubles as his product pitch — including the “15–20% ROI lift” figure, which appears inside ad copy he reads aloud.
  • Performance claims — the account screenshots, the scaling stories, the $100k/day — are self-reported.
  • Becker explicitly credits Charley as a source of his own ideas, so Both means strong consensus, not independent corroboration.

None of this makes the frameworks wrong. It means you should treat them as well-argued hypotheses from practitioners with skin in the game, and let your own GPL numbers arbitrate.

20Source ledger

Every load-bearing claim in this manual, traced. Use this to check anything that felt too confident.

§ClaimSourceDate
01The feed is a search results page; every post has an estimated action rateCharley05-11 / 07-18
01Two gates — Lattice balances user experience, Andromeda filters for meritCharley07-18
01Spend is a measure of preference, not a budget settingCharley07-18
01Frequency 1.05 ≈ 5% saw twice; 1.95 ≈ 95% saw twiceCharley07-18
01Cost per result measures contribution, not ad qualityCharley07-18
01New ads are shown first to your warmest audienceCharley05-11
01Andromeda was built because people launched too many ads, and penalises itCharley05-11
01Personalisation is a delivery sequence problem (citing Alex Schultz)Charley05-11
02Four eras; $4.3bn→$196bn; CPM $0.55→mid-teens; 10M+ advertisers, 80% under $100/dayCharley07-14
02Era 3 dip tracks the stock market, not iOS 14 aloneCharley07-14
02Ridge / Grüns / Comfrt win on profitability / LTV / distributionCharley07-14
02Five algorithm generations, ending in generativeCharley07-14
03Offer must be new, a result, effortless, proven, guaranteedBecker07-30
031-in-100 buys the $2,000 offer as reliably as 10-in-100 buy the $50 oneBecker07-30
03Cold traffic ≠ warm traffic; the acquisition.com page would fail coldBecker07-30
03One landing page per buyer profile; plain outconverted elaborateBecker08-07
04A campaign is a funnel, not a container of competing adsBecker08-07
04Facebook ads are a team sport; improve the worst playerCharley05-11
04Ad fatigue is almost always operator errorBoth07-18 / 08-07
04Ads only need to be ~70% / “good enough at their role”Both05-11 / 08-07
05Andromeda One: 1 CBO campaign, 1 control (4–8 ads) + up to 2 test ad setsCharley05-04 / 07-18
05Budget ladder: 1 ad set → 1+1 → 1+2, and never furtherCharley05-04
05One campaign per buyer profile at $100–200/day, 5–8 ads eachBecker08-07
06322 = 3 creatives, 2 headlines, 2 primary texts = 12 combinationsCharley05-04 / 07-18
06Never exceed 3 creatives; never mix image and video in one adCharley07-18
06Two 322s with identical copy isolate whether copy is doing the workCharley07-18
06Headline 40 chars, not shown on Instagram; 125 chars before “see more”Charley04-09
07Olympic Rings: 3 prospecting + 2 retargeting; ring 4 = 2nd touch for 1+2, ring 5 for 2+3Charley05-11
07Broad retargeting beats cart-abandoner retargeting on cost and volumeCharley04-09
08Six-slot sequence: problem → static → 2nd benefit → offer → proof → objectionsBecker08-07
09Red: text generation, enhanced CTA, 3D animationCharley07-25
09Yellow: music, image expansion, text improvements (set restricted words first)Charley07-25
09Green: visual touch-ups, brightness/contrast, relative comments, sitelinksCharley07-25
09Enhancements apply at ad level, not image level; survive duplicationCharley07-25
09Confidence and enhancement use are inversely related; “every ad becomes a C+ ad”Charley07-25
10Native AI creative references what's converting across your whole nicheCharley07-07
10Per-combination control of crop, placement, copy and destination URLCharley07-18
10Vary the presentation of a proven pitch; don't mass-generateBecker08-07
114PI = spend, frequency, CPM, cost per result; three signaturesCharley07-18
11Two outcomes: subtraction, or fill the gaps (three gap patterns)Charley07-18
12GPT beats ROAS; 4× ROAS/$30 profit vs 2× ROAS/$60 profitCharley05-04 / 07-18
12Judge every test on campaign profit volume, nothing elseCharley05-04
12“Can I spend more money tomorrow?” is the only success definitionCharley05-11 / 07-18
12Hunters vs farmersCharley05-04
12GPL — the lead-gen profit formulaApplied
13Three-step test: delivery → evaluation → scale; harvest by post IDCharley05-04 / 07-18
13One variable at a time against a known controlCharley05-11
13Test in a separate ad set, swap only the winner inBecker08-07
14Three stages in order: efficiency → readiness → budgetCharley07-18
14Never turn off more than 20% of spend in a dayCharley07-18
14Linear / fractional / marginal; +$10/day → $3,000/day in a year; 2%/day → 6× in 90 daysCharley07-18
14Scale down at half the speed you scaled up, then wait 48–72hCharley07-18
15“Standard events are for entry-level marketers”Charley06-28
15Optimise on verified qualified calls / attendance, not form fillsBecker08-07
15Predictive value front-loading; binary high-value event variantBecker08-07
15Conversion goal is a training input, not attributionBecker08-07
15Customer lifecycle strategy; both exclusion sides; 730-day window; tiered lists; match ≥8.5Charley06-28
15Spend tiers for turning lifecycle optimisation onCharley06-28
15“Lead gen where cheap leads don't mean good customers”Charley06-28
16Entire NZ life-cover worked example, all figures, all hooksApplied
1790-day sequencingApplied