# Adam Taylor

Adam Taylor works with direct-to-consumer brands on Meta advertising. Taylor's posts describe building a creative-testing system that uses customer research to develop ad angles, track what works, and guide the next round of ads.

- Profile: https://b2binfluencer.marketing/creators/adam-taylor/
- LinkedIn: https://www.linkedin.com/in/adamtaylorl
- LinkedIn followers: 10,745
- Topics: paid-ads, meta-ads, creative-testing, customer-research
- Based on 16 dated posts, latest 2026-09-30

## Summary

Adam Taylor is most useful for building a Meta ad creative testing system for direct-to-consumer brands.

- Best for: Direct-to-consumer subscription brands with sliding Meta ROAS and unclear past winners.
- Not for: B2B SaaS sponsorship, creator-led LinkedIn content, or campaigns without Meta ad creative.
- Check first: Ask for fees, contract length, independent verification, and underlying performance data.

### Takeaways

- Declining results usually mean the brand cannot explain its own winners.
- Creative should work like a research lab, not a content factory.
- Ad angles should be built from the customer's own words.

## Main ideas

- **Declining results usually mean the brand can't explain its own winners**: Taylor's recurring diagnosis: a brand with falling ROAS isn't short of creative; it's short of an explanation. Teams can report a top ad's results but can't name its hook, angle, or the awareness level it met the customer at. When the winner fatigues, they replace it at random, and every batch starts from zero. Taylor argues for recording what works while the ad is still running, not conducting a post-mortem after it dies.
- **Creative should work like a research lab, not a content factory**: Taylor separates output from learning. A content factory asks how many ads it can produce and measures success in volume; a lab asks how many winning angles it can validate and treats each ad as one answer to a question. The practical difference is tagging: every ad is labelled by angle, persona, hook type, and awareness level, so even a failed or fatigued ad informs the next batch. Taylor's test for which mode a team is in is how it answers the question “What are we testing this week?”
- **Ad angles should be built from the customer's own words**: Taylor treats customer language as raw material for strategy, not something copywriters supply later. Their research involves reading reviews, forum threads, support tickets, and refund requests for the exact phrases customers use about their problems, objections, and desired outcomes, then turning those phrases into hypotheses about which belief an ad has to shift. The starting question becomes what belief needs to change, not what the ad should look like.
- **A single winner, or a single person, is a structural risk**: Taylor argues that an account or creative system resting on one winning ad or one founder's head is equally fragile. When the ad fades or the founder steps back, whoever takes over inherits the asset without the reasoning behind it and starts guessing. Taylor's remedy is to document decisions as they are made, so a strategist or agency can carry the work forward and the founder's role can shrink to approving finished ads rather than writing every script or supplying every next angle.
- **Taylor argues that creative has become the targeting signal on Meta**: Taylor writes that after Meta's Andromeda update, the system reads a brand's visuals, text overlays, and landing page to find buyers, making unstructured creative actively harmful: random videos teach the algorithm nothing and reset its learning phase week after week. Structured creative built around a defined angle, audience, and awareness level compounds instead. This is Taylor's reading of the platform, not an established fact.
- **How a founder describes their own business shapes what they will attempt**: One of Taylor's posts moves beyond creative production. They say the gap between $1M and $10M brands shows up in how founders describe their business when they are not selling: those who are scaling talk about where they are going as if it has already happened, while stuck founders list what is not working yet. The consequences are behavioural: a founder who talks about the brand as fragile cuts spend early, kills ads before they have spent enough to teach anything, and hires people they do not really believe in.

## Work to read

- [A $1M/month pet supplement account and the missing creative system](https://www.linkedin.com/posts/adamtaylorl_a-founder-spending-1mmonth-on-meta-booked-activity-7508895645240508416-SB5o)
- [Rebuilding one winning founder ad for a menopause supplement](https://www.linkedin.com/posts/adamtaylorl_a-founder-doing-12myear-booked-a-call-with-activity-7511070003388112896-R_TJ)
- [Four creative hires that make ads perform, not just look good](https://www.linkedin.com/posts/adamtaylorl_most-agencies-hire-creative-teams-the-wrong-activity-7430257360478306305-LBKi)
- [From factory floor to $3M/month in Meta spend](https://www.linkedin.com/posts/adamtaylorl_at-16-i-was-working-in-a-factory-at-24-activity-7437142739382640640-2JSB)
- [Post-Andromeda: why creative is now targeting](https://www.linkedin.com/posts/adamtaylorl_90-of-e-com-founders-are-completely-misdiagnosing-activity-7467980492571824129-ho6W)

## Brand relationships

- **Creative Data System** (disclosed_partnership)

## Partnerships

The reviewed LinkedIn posts document Adam Taylor's commercial offer as a paid agency engagement, not sponsored content or brand ambassadorships. The sales posts target direct-to-consumer brands buying Meta advertising creative. The offer is a “Creative Data System”: research mined from customer reviews, Reddit threads, and competitor ads, converted into ad angles, then taken through production, delivery, and analysis. Taylor describes running creative end-to-end for brands spending a combined $20M+/month on Meta, from a solo founder at $100K/month to nine-figure brands, positioning the work as a substitute for the brand briefing, reviewing, or writing its own ads. Scale is the key buyer consideration: posts repeat a $30K+/month Meta spend threshold, and the case stories feature subscription e-commerce brands in categories such as pet supplements and menopause supplements. The posts describe an agency service, not sponsorships, gifted products, affiliate arrangements, or paid placements for third-party brands. One post details the internal team model behind delivery, useful for brands assessing how the agency staffs the work or considering whether to copy the approach.

## Alternatives

- Amir Faizan Malik: When the bottleneck is conversion copy, not account structure. Amir Faizan Malik's posts document copy projects with measured outcomes: a landing page rewrite that moved conversion from 2.1% to 8.4% by replacing a generic promise with one specific problem; an email sequence for a tile installation course with a 55.6% average open rate and 8.23% click rate that booked 22 calls in four weeks; and a Meta creative test for a men's lifestyle brand reporting a 53% hook rate, 4.33% hold rate and 3.87x ROAS. The method is consistent: research the audience first, mine its exact language from Reddit threads and reviews, write to one person, then test multiple hooks and keep the winner. For a DTC brand scaling Meta spend, this is the better pick when the message itself is failing and the buyer wants a specialist to rewrite the page, email and ad copy around a sharper audience definition.
- Ujla Shakoor: When the buyer wants a plain, practitioner-level argument against letting one winning creative carry the whole account. Ujla Shakoor's reviewed advice post makes exactly that case for a DTC Meta account: one hook, angle and message means the whole account feels it when the creative tires. Keep asking what is being tested next across different hooks, angles, customer problems and formats, and build a pipeline of winners instead of replacing one at a time. A companion post describes five years of work, including three years across DTC brands, Meta ads, creatives, campaigns, scaling and data. For a brand still relying on a single ad to hold up spend, this directly articulates the risk.
- Alex O.: When the client is a mobile app, not an ecommerce brand, and the task is building a UGC content engine. Alex O.'s posts cover content-market fit for app growth: define the real user by situation and behaviour rather than demographics, mine their language from Reddit, TikTok search and App Store reviews, find angles competitors ignore, then run the resulting content system. One post describes running Claude Cowork as a full UGC content backend, with weekly automation for customer-language mining, hook generation, creator briefing, angle rotation and comment seeding, and cites Tea App, Turbo AI and WhatColors as examples. This is a better match for an app-install or app-activation need than for DTC ecommerce.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/