ads

• What's the primary objective? (Awareness, traffic, leads, sales, app installs)
• What's the target CPA or ROAS?
• What's the monthly/weekly budget?
• Any constraints? (Brand guidelines, compliance, geographic)

• What are you promoting? (Product, free trial, lead magnet, demo)
• What's the landing page URL?
• What makes this offer compelling?

• Who is the ideal customer?
• What problem does your product solve for them?
• What are they searching for or interested in?
• Do you have existing customer data for lookalikes?

• Have you run ads before? What worked/didn't?
• Do you have existing pixel/conversion data?
• What's your current funnel conversion rate?

Testing phase (first 2-4 weeks):

• 70% to proven/safe campaigns
• 30% to testing new audiences/creative

Scaling phase:

• Consolidate budget into winning combinations
• Increase budgets ~20% at a time — never 30%+ in one move (resets platform learning)
• Wait 3-5 days between increases for algorithm learning

Problem-Agitate-Solve (PAS):

[Problem] → [Agitate the pain] → [Introduce solution] → [CTA]

Before-After-Bridge (BAB):

[Current painful state] → [Desired future state] → [Your product as bridge]

Social Proof Lead:

[Impressive stat or testimonial] → [What you do] → [CTA]

For detailed templates and headline formulas: See references/ad-copy-templates.md

These ratios are directional, not precise. Test in your actual account.

Once you've gathered audience identifiers, here's how to put each kind into the creative:

• Demographic identifiers (age, location, occupation) → embed as identity-trigger keywords in headlines (see [[#The one-keyword hack (identity-trigger keywords)]])
• Pain points + fears → headline + first line of body copy (Sabri Suby's framing: "the verbatim words your customers use about the problem")
• Hopes / desired outcomes → transformation copy + CTAs
• Objections + "why they didn't buy last time" → objection-handling retargeting ads (see [[#The 4-component retargeting framework]])
• Their language / vocabulary → the entire copy voice — never use industry jargon they don't
• Existing customer base → still feed it for lookalike audiences (see Key Concepts below)
• Niche / segment they identify with → identity-trigger keywords in headline ("for dentists" / "for B2B founders" / "for parents of toddlers")

• Lookalikes: Base on best customers (by LTV), not all customers. Still high-value across platforms.
• Retargeting: Segment by funnel stage (visitors vs. cart abandoners). See [[#Retarget with DIFFERENT offers (not the same one)]] and [[#The 4-component retargeting framework]] for the modern playbook.
• Exclusions: Exclude existing customers and recent converters — showing ads to people who already bought wastes spend.

Trying to make up for weak creative with hyper-precise targeting. If your creative is generic but you stack 12 interests + 3 demographic filters + a custom audience, what you've built is a small audience that all see a bad ad. Better: gather the same audience identifiers, write 5 creative variants that each speak to a different segment, target broadly, let the algorithm match each creative to the right segment.

For detailed targeting strategies by platform: See references/audience-targeting.md

• Andromeda is "a hungry panda" — it needs constant fresh creative or it fatigues
• Statics often outperform video in 2026 because:
  • Meta's algorithm has a bias toward statics — it can show more statics per session per user, so they're cheaper to deliver
  • Static creative is 10x cheaper and faster to produce than video, enabling the volume Andromeda needs
  • Even top advertisers running 17+ VSLs report that down-and-dirty native statics often beat 2.5-month-production VSLs
• Dedicate 1 hour per week to producing fresh creatives for your winning offer. Volume > polish.

• The old playbook: stack interests, narrow the audience, hope to find the right buyer
• The new playbook: target broadly (just the country) and let the creative do the targeting
• Long-form ad copy works better than short-form in 2026 — gives Meta a wider context window to understand who to show the ad to
• Test it: take your best winning ad with interest-stacked targeting, duplicate it, remove all targeting (just pick the country), run side-by-side for 7 days. Check CPAs. Broad typically wins.

• Take your winning ad
• Duplicate it with a niche/identity keyword inserted in the headline or body copy
• "Here's how to get 462 leads per week on autopilot" → "Here's how to get 462 dental leads per week on autopilot" / "...lawyer leads..." / "...property investment leads..."
• The keyword is an identity trigger for the viewer AND a targeting signal for Andromeda
• Dramatically drops CPL and opens audience pockets you couldn't reach with a generic ad

• Take your winning ad
• Feed to Claude/ChatGPT/Kong with the prompt:

  "I want you to read this ad and be the author. If I show the next ad I'm going to ask you to write to 100 people, not 1 in 100 would be able to tell you it's written by a different person. Now write this for [demographic/niche]."

• The output should read essentially the same with subtle relevance shifts for the target
• Apply in sequence: body copy → headlines → creative
• Drop all variants in a CBO, let Meta's AI allocate spend

• After running a CBO, Meta will give 80% of variants no spend
• Take the dead variants you have high conviction about
• Launch them in a separate ad set ("zombie campaign")
• Typically resurrects 20% as winners that Meta's first allocation passed over

• Hundreds of millions of people have ad blockers — the polished-ad aesthetic kills performance
• Study what content natively performs in your niche on TikTok/Instagram/YouTube → produce ads that match that aesthetic
• Burner account technique: create a clean Instagram/TikTok account, follow all influencers and pages in your niche, like their content. Your feed becomes a curated view of what's natively winning. Produce ads that match.
• If you have an organic video with millions of views, run that exact video as a paid ad — proven content + paid distribution = the highest-leverage move

• Clear product screenshots showing UI
• Before/after comparisons
• Stats and numbers as focal point
• Human faces (real, not stock)
• Bold, readable text overlay (keep under 20%)

1. Hook (0-3 sec): Pattern interrupt, question, or bold statement
2. Problem (3-8 sec): Relatable pain point
3. Solution (8-20 sec): Show product/benefit
4. CTA (20-30 sec): Clear next step

Production tips:

• Captions always (85% watch without sound)
• Vertical for Stories/Reels, square for feed
• Native feel outperforms polished
• First 3 seconds determine if they watch

1. Concept/angle (biggest impact)
2. Hook/headline
3. Visual style
4. Body copy
5. CTA

If CPA is too high:

1. Check landing page (is the problem post-click?)
2. Tighten audience targeting
3. Test new creative angles
4. Improve ad relevance/quality score
5. Adjust bid strategy

If CTR is low:

• Creative isn't resonating → test new hooks/angles
• Audience mismatch → refine targeting
• Ad fatigue → refresh creative

If CPM is high:

• Audience too narrow → expand targeting
• High competition → try different placements
• Low relevance score → improve creative fit

1. Start with manual or cost caps
2. Gather conversion data (50+ conversions)
3. Switch to automated with targets based on historical data
4. Monitor and adjust targets based on results

• Existing customers (unless upsell) and recent converters (7-14 day window)
• Bounced visitors (<10 sec)
• Irrelevant pages (careers, support)

The conventional retargeting playbook re-shows the same product/offer to people who didn't buy. The Sabri Suby principle: the #1 reason someone didn't buy is the offer wasn't right for them. Re-showing the same thing harder doesn't help.

Instead, retarget with different products, services, or offers from your catalog:

• Visitor clicked on protein powder, didn't buy → retarget with creatine (totally different category)
• Visitor downloaded a lead magnet, didn't book a call → retarget with a different lead magnet on a related topic
• Visitor viewed pricing, didn't sign up → retarget with a free audit or assessment instead

The lift from this is often dramatic — a 2-3 ROAS audience on the original offer can hit 6+ ROAS on a different offer.

Build out your retargeting layer with these 4 ad types running simultaneously:

1. Objection-handling ad — directly addresses the most common reasons people didn't buy. To find these, outbound call every lead who didn't convert and ask why. The verbatim objections become the headline of this ad.
2. Proof testimonial carousel — multi-image/multi-slide carousel of testimonials and proof that supports the claims of your original ad
3. Other-offers CBO — your other best-performing ads for other products/services in one CBO, retargeted to the same audience
4. Value-first audit/assessment ad — wraps your call in a free piece of value. Whether they buy or not, they leave with something useful. Lowers the friction to engage.

These four together, retargeting the same audience that didn't convert from the top-of-funnel ad, dramatically lift the ROAS of the entire funnel.

Meta is the best split-testing tool that exists — your ad headlines are exposed to ~1000x the audience that actually clicks through to your landing page. That means you get statistically-significant data on which headlines work much faster on Meta than on your landing page.

The play:

1. Run 20-40 different headlines as ad variations
2. Identify the best-performing headline (by CTR + downstream conversion)
3. Mirror that winning headline on your landing page — exact wording in the H1, sub-headline, and lead-in copy of the body
4. Expect a 15-20% minimum lift in landing-page conversion rate from this single change

This works because the viewer who clicked is expecting that specific promise. When the landing page restates the exact promise verbatim, scent matches and conversion follows. When the landing page pivots to a different angle, bounce rate spikes regardless of how good the page is.

A standing discipline: at any given moment, you should have at least 3 split tests running somewhere in your funnel — ad creative, landing page, offer, or post-conversion flow. If you don't, you've capped your improvement curve.

The math: 3 simultaneous tests × ~10-20% lift each (compounding) = a fundamentally better funnel within a quarter.

• Spend vs. budget pacing
• CPA/ROAS vs. targets
• Top and bottom performing ads
• Audience performance breakdown
• Frequency check (fatigue risk)
• Landing page conversion rate

• Platform attribution is inflated
• Use UTM parameters consistently
• Compare platform data to GA4
• Look at blended CAC, not just platform CPA

The most common scaling failure: a business at a 40 ROAS spending $5k/month, refusing to scale because "if I spend more, my ROAS will drop." This is the wrong frame.

Net cash flow > ROAS percentage at the business level:

• ROAS dropping from 10 → 5 sounds bad
• But if spend goes from $10k → $100k, you net dramatically more total profit
• The number to optimize is blended ROAS at the business level, not per-ad-set ROAS
• Even better: optimize net free cash flow, not ROAS at all

Find your break-even ROAS:

1. Calculate the absolute maximum you can pay to acquire a customer and still be profitable (factoring LTV)
2. That's your break-even ROAS / CPA ceiling
3. Scale until you approach that ceiling, not until your ad-account ROAS drops below an arbitrary preference

The 3-hour founder review:

• Block out 3 hours per month in the calendar to physically review the numbers yourself
• Not what your data analyst says. Not what your media buyer says. You, going through the actual data
• The confidence this generates is irreplaceable — and confidence is what lets you scale with conviction
• "Data gives you confidence. Confidence gives you speed."

Outbound-call your leads who didn't convert:

• Every lead that downloaded a lead magnet or hit your funnel but didn't buy gets a call
• Ask why they didn't book, what was confusing, what the actual blocker was
• These verbatim answers become objection-handling ads (see Retargeting section)
• Massive insight-to-creative loop that most advertisers skip

• Conversion tracking tested with real conversion
• Landing page loads fast (<3 sec)
• Landing page mobile-friendly
• UTM parameters working
• Budget set correctly
• Targeting matches intended audience

• Launching without conversion tracking
• Too many campaigns (fragmenting budget)
• Not giving algorithms enough learning time
• Optimizing for wrong metric

• Audiences too narrow or too broad
• Not excluding existing customers
• Overlapping audiences competing

• Only one ad per ad set
• Not refreshing creative (fatigue)
• Mismatch between ad and landing page

• Spreading too thin across campaigns
• Making big budget changes (disrupts learning)
• Stopping campaigns during learning phase