Ernest Simonyan works in performance marketing at ScaleLoop, a marketing agency for e-commerce and information-product businesses. Simonyan's posts discuss Meta advertising, creative strategy and production, ad measurement, and hiring for the agency.
Text-wall ads can be made faster than UGC video, letting teams test more angles cheaply.
Platform ROAS can look strong while MER, total revenue divided by total spend, is weaker.
ScaleLoop hiring posts describe creative strategy, production, and media buying as separate staffed roles.
Check first: Confirm whether they accept sponsorships, offer terms, and can share audience demographics or engagement data.
Main ideas
Text-wall ads as a cheap first testing layer · ROAS overstates performance; MER is the check · Creative is argued about with numbers, and the team must own it
Ernest Simonyan’s LinkedIn posts focus on performance marketing for e-commerce and information-product businesses, especially Meta ad creative and measurement.
The clearest examples argue for testing low-cost text-wall ads before investing in more produced creative, and checking platform-reported ROAS against total-revenue-to-total-spend MER.
ScaleLoop hiring posts also describe an agency combining creative strategy, production, and media buying.
These posts offer a practical reason to follow them: they connect creative choices to testing speed and business-level measurement.
The posts connect two decisions often treated separately: what creative to test and how to judge whether advertising is paying off.
In the text-wall ad post, Simonyan says the format can be made faster than a UGC video, letting a team test more angles before committing production budget.
In the ROAS-versus-MER post, an example of strong platform ROAS alongside weaker MER shows why platform attribution can obscure overall business performance.
Together, these arguments give readers concrete questions to take into a Meta campaign: which ideas can be tested cheaply first, and does total revenue relative to total spend support scaling?
The hiring posts show how ScaleLoop describes its creative, media-buying, and operations roles.
Ernest Simonyan writes about performance marketing at ScaleLoop, an agency serving e-commerce and information-product businesses.
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Their posts treat Meta advertising as a discipline of testing and measurement: cheap plain-text ads can find winning angles faster than polished production; platform-reported ROAS can hide a cash-flow problem that a back-end MER figure exposes; creative work should be grounded in performance data and customer psychology, not produced for its own sake; and scaling a service business requires systems, margin ownership and delivery processes—not a side task.
Text-wall ads as a cheap first testing layer
Ernest Simonyan argues that polished ad creative triggers what the post calls ad-evaluation behaviour: viewers register the high production value, recognise an ad and scroll past.
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A plain wall of text reads like an ordinary feed post, so people start reading and the platform collects the engagement signals it needs to optimise delivery.
The post also makes the case for production speed: a UGC video takes days to brief, produce and edit, while a text-wall ad takes about an hour.
A brand can test ten or more angles in the time it takes to make one creator video, finding what resonates before committing production budget.
The post opens with a deliberately unstyled format—no creator, no studio, no polished visuals, just a wall of text—and claims it consistently ranks among the top-performing formats for DTC brands. It closes by advising readers to test a text-wall ad this week.
Ernest Simonyan describes a familiar pattern: a brand has its best ROAS month, increases budget on what is working, then hits a cash-flow problem three months later that nothing in the dashboard explains.
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ROAS is Meta's own number, and the post argues that it credits sales it can connect to a click or impression—including returning customers who would have reordered anyway, email subscribers who clicked an ad on the way to checkout, and organic buyers who saw an ad and later searched the brand. MER offers a correction: total revenue from the back end divided by total spend across every channel, with no attribution logic.
The post says that when ROAS says 4.5 and MER says 2.1, the gap is what is making the business broke. It tells readers to calculate MER before touching the budget again.
Creative is argued about with numbers, and the team must own it
Across the hiring posts, creative strategy sits at the intersection of performance data, customer psychology and creative execution, helping clients find more winning creatives and scale profitably on Meta.
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The media-buyer post emphasises profitable Meta account scaling, analytical work and collaboration with creative strategists—not just task completion.
The hiring language repeatedly calls for people who take ownership, need no chasing or micromanagement, and are serious about growing with a lean team.
It also makes clear that creative decisions should be tied to performance data and execution, not made for their own sake.
The creative strategist post says the right person does more than complete tasks: they bring solutions, identify challenges early and take responsibility for results.
The head-of-operations post frames scale as something to build deliberately, not handle as a side task.
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The role covers a full operational audit of agency workflows; P&L ownership, cost tracking and margin optimisation; scalable standard operating procedures and delivery frameworks; OKR and KPI architecture; onboarding and client-success processes aimed at retention and lifetime value; and resource allocation to keep teams profitable. The hire partners directly with the CEO on growth strategy and operational risk.
The post tells candidates they will do more than manage: they will architect, owning the systems, structure and strategic alignment that let the team perform as the agency scales.
For marketers deciding how to spend a Meta creative budget, this post explains where cheap testing fits relative to expensive production.
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Simonyan argues that polished advertising triggers what the post calls ad-evaluation behavior: viewers spot high production value, recognise an ad and scroll.
A plain wall of text reads like an ordinary post, so people start reading, the hook works and the platform collects the engagement signals it needs.
The second argument is production economics.
A UGC video takes days to brief, produce and edit, while a text-wall ad takes about an hour.
That gives a brand time to test ten or more angles while producing one creator video, then identify what resonates before committing production budget.
For brands planning a campaign
Use text-wall ads as the first testing layer to find angles, then invest in production for the angles that show demand. For a DTC brand, this changes the order of creative work and lowers the cost of testing each angle.
This answers a founder's question after a record month: why can a profitable-looking Meta account still lead to a cash-flow problem?
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Simonyan describes the pattern: a best-ever ROAS month, a budget increase and, three months later, a cash-flow problem that nothing in the dashboard explains.
The reason given is that ROAS credits Meta for returning customers who would have reordered anyway, email subscribers who clicked an ad on the way to checkout, and organic buyers who saw an ad and later searched the brand.
MER—total revenue from the back end divided by total spend across every channel—is offered as a check, without attribution logic.
Where ROAS reads 4.5 and MER reads 2.1, the gap shows what the business is spending without getting back.
For brands planning a campaign
Pair platform-reported ROAS with a back-end MER calculation before scaling spend, and make it a named step in the measurement plan.
This explains what the creative side of a performance marketing agency is staffed to do, useful to know before briefing one.
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The post advertises a remote, full-time creative strategist role at ScaleLoop, an agency working with e-commerce brands and information businesses generating six and seven figures a month.
The stated requirements are experience with large brands, staying up to date with creative trends, taking ownership without needing to be chased, and comfort at what the post calls the intersection of performance data, customer psychology and creative execution.
The role reflects the approach in the ad-format and measurement posts: creative is tested and debated with numbers, not produced for its own sake.
For brands planning a campaign
When briefing a creative partner, this describes the working style to expect and ask for: trend-aware, data-critiqued creative rather than design-led production.
This explains how the buying side is staffed and what the role is expected to deliver, useful when judging whether one partner can cover both testing and scaling.
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Simonyan's media-buyer post describes the work behind the accounts: scaling Meta advertising for e-commerce and information clients.
The role calls for experience, analytical thinking and ownership rather than waiting for direction.
The post stresses that the right person brings solutions and flags problems early instead of only completing tasks.
Working terms include fully remote work, flexible hours, twenty paid vacation days, paid professional development, and a $200 payment to both parties if a referred candidate is hired.
For brands planning a campaign
Useful when assessing scope: the same shop presents creative strategy, media buying and creative production as one set of roles, so a brief can cover angle testing and account scaling together.
Text-wall ads as a low-cost creative testing format
One post argues that plain, text-heavy ads — no creator, no studio, no polished visuals — often rank among the top-performing formats for DTC brands.
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The reasoning: high production value triggers ad-evaluation behaviour, while a wall of text reads like organic feed content, prompting people to read instead of scroll past. The claimed practical edge is speed: a text-wall ad takes about an hour, so a brand can test ten or more angles in the time it takes to produce a single UGC video and find what resonates before committing production budget.
Draft text-only angles quickly, run them as the first testing pass, and move the winners into fuller production.
For brands planning a campaign
For a DTC brand rebuilding creative testing, this makes a concrete case for a cheap, fast first-pass loop before spending on creator video. Treat the performance claims as a hypothesis to test; the author provides no supporting data in the posts.
A post explains how a brand can have its best ROAS month and still hit a cash-flow problem three months later.
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The argument is that ROAS is Meta’s own number and claims every sale it can connect to a click or impression — including returning customers who would have reordered anyway, email subscribers who clicked an ad on the way to checkout, and organic buyers who saw an ad and searched later.
MER is presented as the correction: total revenue from the backend divided by total spend across every channel, with no attribution logic.
When ROAS reads 4.5 and MER reads 2.1, the post describes the gap as the source of the leak.
For brands planning a campaign
This offers a method for pairing platform ROAS with a backend MER figure before changing budget.
The post argues for MER but gives no worked example using the brand’s own numbers.
Before using the method, define which revenue and spend totals feed the calculation.
Creative strategy framed around data, psychology, and execution
A recruitment post for a creative strategist places the role at the intersection of performance data, customer psychology, and creative execution, supporting clients in finding more winning creatives and scaling profitably on Meta.
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The stated expectations include experience with large brands, keeping up with creative trends, taking ownership without being chased, and being serious about growing with a lean team.
Translate performance data and customer psychology into creative concepts rather than treating creative as a separate brand exercise.
For brands planning a campaign
A brand evaluating the approach can read it as a working method: a small team ties creative decisions to performance data and execution rather than brand identity. The job description does not show how the work performs on a specific account.
One post describes the agency as working with e-commerce brands and information-product businesses generating six to seven figures monthly, supported through Meta ads management, creative strategy, creative production, and consulting.
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A separate recruitment post for a media buyer emphasises scaling Meta accounts profitably, analytical work, and collaboration with creative strategists.
For brands planning a campaign
This sets the operating context a brand would be buying into: performance-focused Meta advertising for businesses already at meaningful revenue, with media buying and creative handled in the same place. Hiring posts outline intended service lines; ask for results delivered for named clients.
Operational scale treated as a build, not a side task
A post recruiting a head of operations describes the role as covering a full operational audit of agency workflows; P&L ownership; cost tracking and margin optimisation; scalable SOPs and delivery frameworks; talent sourcing; OKR and KPI architecture; org design; onboarding and client success processes aimed at retention and lifetime value; and resource allocation to keep teams profitable.
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The post says the hire partners directly with the CEO on growth strategy and operational risk.
For brands planning a campaign
For a brand judging whether added volume could be absorbed without service slipping, this shows the agency treating delivery infrastructure, margin, and client retention as explicit leadership responsibilities. Ask how these systems have performed for existing clients.
Ernest Simonyan’s LinkedIn posts center on ScaleLoop, a performance marketing agency serving DTC e-commerce and information-product businesses with Meta ads management, creative strategy, creative production and consulting.
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Three posts advertise ScaleLoop roles and refer to “we” and “our clients,” but don’t state their role in the business; ask them to clarify their relationship to ScaleLoop.
The other two posts discuss text-based ad formats and MER versus ROAS measurement.
The posts name no brand partners or clients.
ScaleLoop
Disclosed partnership
Three ScaleLoop hiring posts recruit a Media Buyer, a Creative Strategist and a Head of Operations.
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They describe ScaleLoop as a boutique performance marketing agency serving e-commerce and information-product brands with Meta ads management, creative strategy, creative production and consulting.
The agency offers a $200 referral bonus for hires.
The posts speak as the agency (“we’re hiring,” “our clients”) but don’t state Simonyan’s role; ask them to clarify their relationship to ScaleLoop.
Ernest Simonyan writes short, argument-led LinkedIn posts about performance marketing for e-commerce businesses.
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Two contrasting arguments offer a quick introduction to the work.
One is about creative: a plain wall of text — no creator, no studio, no polished visuals — often ranks among the best-performing formats for DTC brands.
Low production value slips past the reader's reflex to skip an ad, and a text ad takes about an hour to make, allowing a brand to test ten or more angles in the time it takes to produce one UGC video.
The other is about money: a post explains how a best-ever ROAS month can be followed by a cash-flow problem that the dashboard does not explain, and why a back-end MER figure — total revenue divided by total spend across every channel — shows what Meta's own attribution number hides.
The hiring posts show how the work is organised.
A recruitment post for a creative strategist places the role at the intersection of performance data, customer psychology and creative execution.
A media-buyer post stresses scaling Meta accounts profitably and working alongside creative strategists.
A head-of-operations post treats agency scale as an explicit build, covering workflow audits, profit-and-loss ownership, standard operating procedures, OKR and KPI architecture, and client-retention processes.
For a next step, readers can use the text-wall format as a cheap first testing layer and the ROAS-versus-MER argument as a measurement check before raising budgets.
Three other creators writing on the same DTC paid-social beat are listed below for comparison.
Both write short LinkedIn posts about the numbers behind DTC brands scaling on Meta.
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Farah Nyadu describes brands launching 40 to 60 new creative assets a month to scale past $500k monthly, and reports an analysis of 31 brands spending $100k or more a month on Meta. Ernest Simonyan approaches the same pairing of creative volume and budget decisions through testing formats and measurement.
Farah Nyadu frames the work through portfolio benchmarks, brand counts and spend or ROAS outcomes, with advice to scale budgets aggressively once signal thresholds are hit.
Ernest Simonyan's arguments are more conceptual: why a text-wall ad works and why ROAS overstates performance.
They favor cheap testing and measurement discipline before spending.
Both write about DTC brands producing paid-social creative at volume.
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Nikita Ganzina argues that more clips and endless variations mean little if the editing is weak, the story does not land and the first seconds give viewers no reason to care. Ernest Simonyan makes a similar point about text-wall ads: they need to get someone reading and hold their attention.
Nikita Ganzina writes about the craft and bottlenecks of editing: motion design, hooks, retention, cutting a beautiful shot that takes four seconds to reach the point, and the gap between video editing and direct-response editing. Ernest Simonyan writes about testing formats and measuring profitability, not the edit itself.
Both recruit for and describe the daily production of DTC paid-social creative.
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Jim Schroën describes creating UGC ads for DTC brands every day and hiring editors and creative strategists to work on brands with serious ad spend, echoing the creative-production and hiring focus of Ernest Simonyan's ScaleLoop posts.
Jim Schroën's distinctive argument is that creator content extends beyond the ad: AI tools recommend products, while affiliate and UGC networks shape what ChatGPT, Claude and Google AI cite about a brand. Ernest Simonyan's posts do not cover this discovery and distribution angle.
The posts report 12,156 LinkedIn followers on October 9, 2026, but provide no audience breakdown by geography, age, gender, job function, or seniority.
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Three hiring posts—for a media buyer, a creative strategist, and a head of operations—describe ScaleLoop's clients as eCommerce and information-product businesses at 6–7 figures monthly and set expectations for people who scale Meta accounts.
Two analytical posts—the argument that plain text-wall ads beat polished creative and the ROAS-versus-MER breakdown—address operators managing ad spend and reordering budgets.
For a DTC brand focused on Meta creative testing and MER, this is a reasonable LinkedIn-led test; keep initial spend contained until you can assess audience fit.
Ask for a LinkedIn follower demographics view (country, job function or seniority, industry) and engagement figures for the last three to six months of measurement and creative-strategy posts, then compare them with the brand's customer profile.
LinkedIn followers
12,156
LinkedIn profile snapshot captured with the reviewed account · 2026-10-09
The posts do not document sponsorship or brand-partnership formats offered by Ernest Simonyan.
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They cover Meta advertising, creative testing and production, ad measurement, and hiring at ScaleLoop, but provide no rate card, sponsored-content format, sponsorship policy, or route for brand inquiries. Brands considering a paid collaboration should ask about available formats and commercial terms.
A DTC eCommerce brand running Meta ads wants to lower creative-testing costs and stop relying on platform-reported ROAS before scaling spend.
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Reasons
The posts outline a creative-testing method for finding winning angles before committing to video production: build plain-text ads in about an hour, then use the results to decide which angles merit production.
The ROAS-versus-MER post addresses the other half of the brief. It explains how a best-ever ROAS month can lead to a cash-flow problem three months later: platform ROAS credits returning customers, email-clickers, and organic buyers who saw an ad. It proposes total back-end revenue divided by total spend across every channel as a check.
The shop presents media buying, creative strategy, and creative production as three staffed roles, so one engagement can cover the testing loop and account scaling without splitting the work across vendors.
The stated client profile matches the brief: eCommerce and information-product businesses at six to seven figures monthly, where the MER argument matters most.
Verdict
Strong fit for a paid agency or consulting engagement on creative testing and measurement. Not a fit for a sponsored creator placement: the posts provide no sponsorship offer, rate card, or inquiry route.
Watch outs
The posts include no client results, case study, or account data. Performance claims are arguments, not documented outcomes; treat the method as worth testing, not as a proven lever.
The only audience figure is 12,156 LinkedIn followers, captured on 9 October 2026. The posts provide no country, job function, seniority, or engagement data, so follower count alone does not establish DTC-operator reach.
Commercial terms are unconfirmed. Ask for sponsorship formats, partnership terms, and a brand-inquiry route; none are documented in the posts.
When to choose a specialist
A consumer skincare brand wants a paid creator partnership: short-form video content for Instagram and TikTok, with agreed usage rights, an exclusivity window, and a rate card.
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Reasons
The posts provide no sponsorship format, rate card, usage-rights term, or partnership inquiry route. Ask Ernest Simonyan whether they accept sponsorships and what terms they offer.
The posts are LinkedIn text posts. No video, carousel, or image assets appear, leaving no visible creator work to assess, license, or reference for a skincare brand's channel.
The measured audience is 12,156 LinkedIn followers, with no age, gender, geography, or platform breakdown. The posts do not support a consumer-reach or purchase case.
The work is framed as an agency service for eCommerce and information businesses, a different commercial arrangement from a sponsored creator placement.
One of the five posts argues for dropping creator and studio production during the first testing pass, directly opposing a campaign centered on produced creator video.
Alternative
If the skincare brand still wants this layer, separate the needs. Ask the shop to handle Meta media buying and creative testing, which the posts support. For the sponsored placement, choose a creator with documented sponsored-content formats, platform audience data, and visible video work.
Verdict
Poor fit based on the posts. They show an agency-side operator publishing text posts about Meta advertising, not a creator with a documented sponsored-content offer or consumer-facing content library.
A worked campaign example
Angle
Find angles cheaply first, scale only against total revenue per total spend, and use both numbers to set the creative budget.
Brief
Combine the DTC creative-testing and profitability-tracking brief in one campaign angle: a bounded text-wall testing sprint, gated by a back-end MER number.
Handoff
Brief the media buying and creative production work together, since the same shop staffs both roles. Before committing larger spend, ask for LinkedIn follower demographics and actual client results. If the brand needs strategy only, keep the testing sprint and MER guardrail in-house and buy the media-buying layer.
Steps
Set the measurement floor before spending. Pull total revenue from the store backend and total spend across every channel for the last three to six months, compute MER, and record platform ROAS beside it. The 4.5-to-2.1 example in a post is an illustration, not the brand's data; the brand needs its own figures.
Make the first test pass text-only. Write 10 to 12 angles, spending roughly an hour on each, with every angle aimed at a distinct buying objection such as price, skepticism, already-happy-with-the-current-product, or returning customer. Keep creator video and studio production out of this pass.
Hold spend flat and review results after a fixed window, for example five to seven days. Keep angles that hold cost per result and retire the rest before moving any into production.
Move surviving angles into fuller production, including creator video, and use MER as the scaling gate: do not increase budget while MER sits below the agreed threshold, however good platform ROAS looks.
Set the cadence: check MER weekly against the store backend and review monthly which angles actually moved the number. If creative and targeting look fine but MER still leaks, track the leak rather than explaining it away.
Choose Farah Nyadu over Ernest Simonyan when the testing routine is in place and the bottleneck is creative throughput and scaling speed.
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The two posts argue that brands scaling past $500k a month on Meta run 40 to 60 new creative assets monthly; winning ads fatigue in 7 to 14 days at scale; and top performers doubled budgets overnight once they hit their target cost, moving from $50k to $150k in 18 days, compared with slower 10 to 20 percent increases that kept brands learning-limited. For a DTC brand whose winning ads die faster than it can replace them, and whose budget moves are already gated by a back-end profitability number, that’s a more useful answer than a cheap, text-first test pass.
The tradeoff is that the advice favors momentum over caution.
These posts treat platform signals as enough reason to bet bigger and frame careful scaling as leaving money on the table.
They offer no equivalent of the ROAS-versus-MER check: platform ROAS can claim returning customers, email clickers, and organic buyers who saw an ad.
A brand that follows the velocity-and-conviction advice without that guardrail can scale into the cash-flow gap the MER argument describes.
The posts also don’t explain how to produce 40 to 60 assets a month cheaply—the problem a text-wall first pass solves.
Choose Nikita Ganzina when the brand is already making video ads and the problem lies in the edit, not the volume or the dashboard.
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The two posts distinguish a good editor from a direct-response editor: a performance ad must stop the scroll with a hook, introduce the problem quickly, make the product and value obvious, earn trust, use social proof, handle objections, and close with a reason to act.
They argue that cutting a beautiful opening shot or putting a plain customer quote on screen can be the right call if it moves viewers toward action.
For a brand with old footage and an editor who asks how to make the video look better rather than how to make every second more likely to convert, that diagnosis is more valuable than another testing framework.
The tradeoff is that this is craft direction for video already in production.
It doesn’t lower the cost of the first testing pass or supply a measurement rule, so the brand still needs its own testing cadence and profitability gate.
It also assumes enough paid-social spend for edit quality to matter; a brand spending too little to learn from video would pay for production before identifying an angle worth producing.
Choose Jim Schröen when the decision is about content supply and where buyers discover products, not paid-media efficiency.
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One post describes producing UGC ads for DTC brands and argues that AI tools also draw on creator content when recommending products.
It cites 58 percent of shoppers using AI tools instead of regular search and 85 percent of what AI says about a brand coming from other sites such as reviews, creator content, and blogs, and points to affiliate, reviewer, and creator networks as the route into those answers.
A brand whose discovery depends on AI and search answers, or that wants a creator-content pipeline instead of an agency engagement, gets more from this than from a media-buying method.
The measurement question goes unanswered.
These posts offer no ROAS, MER, or testing-cadence framework.
The route offered is a guide sent by direct message in exchange for a comment; no rate card, usage terms, or deliverable format is documented.
Before moving budget into creator and affiliate content, ask how results will be measured against a back-end profitability check.
This page is based on five full public LinkedIn posts attributed to Ernest Simonyan: two on Meta ad creative testing and ad measurement, and three ScaleLoop hiring posts for a media buyer, a creative strategist, and a head of operations.
A LinkedIn snapshot dated 9 October 2026 records 12,156 followers.
Simonyan's posts do not include client results, campaign data, video or image assets, transcripts, or audience demographics, so the posts present arguments and role descriptions rather than documented outcomes.
The posts do not carry publication dates, so readers cannot see a timeline of changing positions, and three of the five posts are recruitment notices.
Earlier signature work such as a book or show is not mentioned in the posts.
