Chris Marrano recently shared something that caught my attention: "100 static ads in 25 minutes." Then he followed it with the real punchline: "The biggest bottleneck for ecommerce brands right now isn't targeting. It's not even budget. It's creative production."

That framing is dead-on for 2026 performance marketing. Most teams are still acting like the primary constraint is finding the next targeting hack or increasing spend. Meanwhile, Meta keeps moving in the opposite direction: broader delivery, more automation, and a stronger preference for creative variety.

In his post, Chris also pointed out the platform reality: "Meta's algorithm wants diversity. Andromeda rewards fresh concepts. But most brands can't keep up with the demand." I want to expand on that idea because it explains why so many accounts plateau even when the product is good and the budget is there.

The bottleneck has shifted from targeting to throughput

For years, ecommerce advertisers could paper over average creative by leaning on:

Narrow audiences and interest stacks
Retargeting-heavy structures
Incremental bid or budget tweaks
Aggressive offer cycling

Meta has steadily reduced the advantage of those levers. Broad targeting and conversion modeling put more weight on inputs the algorithm can actually learn from, and the input it learns from fastest is creative.

When Chris says the bottleneck is creative production, he is really talking about throughput: how quickly you can generate, ship, and iterate on new messages and visuals. If you cannot keep shipping new angles, your tests slow down, learning slows down, and your account starts repeating yesterday's winners until they stop winning.

Key idea: You do not scale ads by finding a single perfect ad. You scale by building a system that continuously produces and tests new ads.

Why Meta rewards diversity (and why brands feel the pain)

Chris mentioned two important forces: the algorithm and Andromeda.

At a practical level, "diversity" means Meta wants multiple distinct creatives that:

Speak to different motivations (save time vs save money vs feel confident)
Use different proof types (reviews, before-after, demo, founder story)
Open with different hooks (problem-first, curiosity, contrarian, social proof)
Fit different placements (Feed, Reels, Stories)

If you only have a handful of ads, your account has fewer shots on goal. Frequency climbs faster, creative fatigue hits sooner, and performance becomes fragile. The brand experience is often: "Our ROAS was fine, then it fell off a cliff." The cliff is usually creative exhaustion.

The pain is not just design. It is coordination: briefs, approvals, edits, resizing, compliance checks, versioning, and uploading. Creative becomes the slowest moving part of the system, so testing becomes sporadic.

The real requirement: a repeatable creative system

Chris wrote: "That's exactly why we built AdIQ. 4 clicks. No graphic designer. Dozens of ready-to-upload creatives in minutes." Whether you use AdIQ or a different workflow, the underlying principle is what matters:

Standardize what can be standardized
Automate the production of variations
Spend human time on strategy and selection, not manual assembly

If you are stuck in a world where every new ad requires a designer, a long brief, and multiple rounds of revisions, you are going to under-test. Under-testing looks like "being efficient" but it is actually expensive because you are running too few bets.

Start with personas, but keep them operational

In Chris's walkthrough, he calls out building personas ("like health-conscious suburban moms"). This is important, but only if personas turn into executable ad inputs.

A useful persona is not a paragraph in a doc. It is a set of:

Jobs to be done (what they are trying to accomplish)
Objections (what prevents purchase)
Triggers (what makes them ready now)
Language (the words they use to describe the problem)

A quick example

If the persona is "health-conscious suburban moms," an operational breakdown might be:

Job: quick, reliable meals that still feel healthy
Objection: "My family will not eat it" or "processed ingredients"
Trigger: back-to-school schedule or starting a new routine
Language: "clean," "easy," "kid-approved," "no junk"

Now you can generate variations that are meaningfully different, not just different colors.

Hooks, elements, and angles: the triad that scales testing

Chris also listed the production steps: "Customizing ad elements and hooks" and "Testing different messaging angles at scale." That is exactly the structure I recommend.

Think of each ad as three layers:

Hook (first 1-2 seconds or first line): earns attention
Angle (the argument): why this product matters
Elements (the build): proof, visuals, offer, CTA, format

If you only vary one layer, your tests are shallow. If you vary all three intentionally, you create true diversity.

Angle ideas you can scale across formats

Problem agitation: "If you keep doing X, you get Y"
Outcome promise: "Get Z in N days"
Proof-led: "Over 12,000 customers switched because..."
Mechanism: "The reason it works is..."
Comparison: "Stop using A, switch to B"

When you map 5 personas x 6 angles x 5 hooks, you already have 150 distinct starting points. The winning teams are not manually producing 150 one-off pieces. They are using systems that can generate variations quickly, then humans curate, refine, and double down.

Where UGC fits (and why it pairs well with static)

Chris noted: "This pairs perfectly with UGC if that's your focus." I agree, and here is the practical reason: UGC is high-trust, but it is slower to produce and harder to version.

Static and templated creative can shoulder the load of:

Rapid angle exploration (find what resonates)
Fast iteration on hooks and headlines
Quick placement coverage

Then UGC can be deployed more selectively:

Convert the best angles into authentic creator scripts
Provide credibility and lived experience
Extend the lifespan of a winning message

A simple workflow looks like this:

Use static variations to discover 2-3 winning angles
Turn those angles into UGC briefs
Use UGC to scale spend and add trust
Keep static variations running to keep learning and avoid fatigue

What to do if you are "waiting on creative"

Chris ended with a line that should make most teams a little uncomfortable: "If you're spending more time waiting on creative than actually testing..." That is the warning sign.

If that is you, here is a practical reset you can implement this week:

1) Define your weekly creative output target

Pick a number you can actually hit consistently (example: 25-50 new creatives/week). Consistency beats occasional big batches.

2) Build a simple testing matrix

Create a table with:

3 personas
5 angles
3 hooks

That is 45 combinations. Your job is to fill the grid over time and track what wins.

3) Standardize templates and specs

Decide your default formats (1:1, 4:5, 9:16), typography rules, and safe zones. Make production mechanical.

4) Treat creative as a pipeline, not a project

Assign ownership, deadlines, and an approval SLA. The goal is flow. If one stakeholder can stall everything for a week, you do not have a pipeline.

5) Promote winners, prune losers

Scale what works, but keep feeding the system. Diversity is not a one-time task.

The takeaway: scale the system, not just the spend

Chris Marrano's core message is not "AI makes ads faster". It is that modern Meta performance depends on your ability to produce and test creative at the speed the platform demands.

When creative throughput becomes your competitive advantage, you stop relying on lucky winners. You build a repeatable machine that finds winners.

If Meta rewards freshness and diversity, the brands that win are the ones that can ship fresh creative continuously.

This blog post expands on a viral LinkedIn post by Chris Marrano, Scaling 7 & 8 Figure DTC Brands Profitably | Building AI-enhanced systems | Founder@BlueWaterMarketing | Founder@ADIQ.AI. View the original LinkedIn post →