УКРEN
Portfolio · Dasha, marketing strategist

The Economics of Trust

One piece of market research, stress-tested against a billion-dollar brand, carried into B2B, taken down to a single clinic's quote — then into running a network. Twelve movements: seven are market research from the finding to the invoice, five are operations with a 107-node automation layer under them.

20 sources, primary sources read in full · a confidence rating on every finding · the operational block runs on a model network with economics built from real Ukrainian data for 2026 · 5 n8n workflows + 2 bots


Seven findings

This page is six minutes. Twelve full versions are linked below — open them by interest, not in order. The companies are fictional. Market inputs are real, with sources and a confidence grade. The companies' own numbers (LTV, margin, payback) are the model's output on those inputs — not "a fact I found": every assumption is visible, and any of them can be changed. Every movement reads in English and in Ukrainian, switchable on each page; Ukrainian is primary. Method: open data, assumptions named out loud, and “I don't know” said plainly.


It starts with one question: where in this industry does the money actually sit.

Movement I ⅔+ of value is created in the chair, not in the vial

Industry research: aesthetic medicine in Europe

The drug itself is 30–50% of an injectable procedure's price (industry COGS estimates). The rest is the physician's time and qualification, the premises, the brand, the follow-up. So competing on which filler you stock means fighting over the smaller part of the chain — and whatever defends the business sits where the value is made: in forty minutes of conversation. (An earlier version divided the European medical-aesthetics market by a global services market and got "89.5%" — non-comparable figures, the number was removed; see the source register.)

From there the data converges. Before-and-after photography ranks fifth of seven trust factors in a peer-reviewed patient study. In the UK it is banned outright for injectables, along with naming the drug, hashtags and influencer endorsement — 47 enforcement notices in a year. Meanwhile the country's largest chain, 70 branches, collapsed in a market growing 11% a year. Behaviour, the regulator and a new patient demographic all point one way. The budgets point the other.

21 sections · 20 sources · 60-metric appendix · 5 charts

Open the research →

The thesis holds on the data. Now stress-test it against a billion-dollar brand.

Movement II 5.0× revenue multiple — the price of a celebrity brand

Brand audit: Augustinus Bader

The brand sells science. Capital markets priced it at 5.0× revenue — the same multiple as Rhode, a celebrity-founded brand of comparable size sold for a billion on $212m of sales. Science, in this category, is paid for differently: Medik8 went at roughly 20× earnings, Paula's Choice at about 18×.

The audit opens by dismantling the usual accusation: cosmetics are under no obligation to publish trials, and the founder's academic record is real. The precise vulnerability is subtler — the brand named as its moat the one axis where it structurally loses to a conglomerate. And the celebrity moat is shared verbatim with a rival: two names on 111Skin's own advocate list are the same.

19 sections · comparable-deal table · 4 counter-arguments to my own case · right of reply noted

Open the audit →

It works on a consumer brand. Now carry it into B2B.

Movement III 40–60% of enquiries arrive outside business hours — that's where the gap is

Go-to-market for a vertical AI agent

The first version leaned on a "2h 05m average response time" — the source has since changed the figure, and a field check contradicts it: on their main channel clinics reply in 2–10 minutes. Reframed: the gap is coverage, not speed — evenings and weekends (40–60% of enquiries), the phone (small US practices miss 25–40% of calls), peak, the second channel. The value of speed is proven by outside data (MIT, 15k leads: contact ×100 at 5 min vs 30) — but that's US B2B, so we carry the direction, not the coefficient.

Fresh data killed the obvious strategy: 81% of med spas are single sites, target segment ≈ 140 groups nationwide. Added risk: a fast solo owner isn't our client — the lift for them is near zero and the holdout will show it. The hardest question — how do you prove the visit came from the product, not the clinic's own advertising? — is answered through a randomised holdout, which in turn dictates which segment you can sell to at all.

21 sections · hiring and funding plan · 3 scenarios with preconditions · says plainly the beachhead isn't a business

Open the strategy →

Three independent confirmations. Now apply it to one real client.

Movement IV 0.46% of the segment is all the clinic needs (sized from demographics) — one in 220

Brand platform for an aesthetics studio

Sized from Kyiv's demographics: about 218,000 women aged 27–48 with above-median income. A three-doctor studio can hold roughly 990 active patients. Which means alienating 99.5% of the market costs nothing — and narrow positioning stops being a matter of taste.

The position is built on refusing to sell. It is evidenced by four Kyiv clinics' published price lists: some offer the consultation free, one charges the equivalent of a single cent — on condition that you go ahead with a procedure. Both structures give the doctor a financial stake in your yes. Here the consultation is paid and non-refundable against treatment — the only arrangement in which “you don't need this” costs the doctor nothing.

20 sections · visual identity · positioning map of 8 clinics · rollout plan with costs

Open the platform →

The position is chosen. Now build the page people will actually land on.

Movement V +21% lift a multi-step form gives over a single-page one

Landing page with a working booking form

Four steps, contact details asked last, and step two qualifying the lead against the segments from the brand platform. The conversion forecast is shown step by step and lands at 4.2% — the top of the typical healthcare band.

In the annotation layer I retract my own earlier recommendation: a sample-size calculation showed that at 800 monthly visitors, detecting a 20% conversion lift would take twenty-two months. “Test your headlines” is not advice at that traffic. A workable programme for low volume replaces it.

working form · toggleable rationale layer · sample-size maths · contraindications block

Open the landing page →

The page exists. Now fill the pipeline that feeds it.

Movement VI 7× the reach gap between medical and beauty framing

Content system across two platforms

Healthcare posts engage at 2.22%; beauty and personal care at 0.32%. A near-sevenfold gap on the same platform, driven not by format but by the category the audience files you under. Reels in beauty are the worst-performing format in any industry at 0.2%, while carousels beat them by 109%.

And a hard defect got closed: the copy discussed injectable procedures without once checking advertising law. Promoting prescription-only drugs is prohibited, as are guaranteed-outcome claims and images of bodily change. All four prohibitions turned out to match what the brand already refuses to do.

16 sections · rubric system · prompts shown with their output · resourcing model in hours

Open the system →

Everything is built. All that remains is to check whether it pays.

Movement VII Mo 13 the month the advertising turns profitable

Unit economics calculator

A monthly cohort model. It shows more than payback — it shows the depth of the trough: $44,000, bottoming out in month six. Which is exactly when the owner switches the advertising off, seven months before it turns.

And a constraint no other model carries: there is one chair, and returning patients occupy it. On a large budget, by month twelve only sixteen of the ninety patients you paid for can be seen at all — and half a million dollars of advertising burns on people nobody has time for.

interactive · capacity ceiling · sensitivity analysis · every formula shown

Open the calculator →

Seven movements answered what to do. Now the operational block — how it runs day to day. The model client changes here, and not by accident: a single “Kontur” studio does not need an operations system — a network of several locations, contractors and ad accounts does. LUMÉ is a fictional Kyiv network of aesthetic-cosmetology studios, its economics built from the same real Ukrainian market data for 2026.

Movement VIII 76% network utilisation — growth hits the chair, not the budget

Metrics and CRM: a report for Google Sheets

The lead-to-patient funnel, unit economics and a deposit experiment on one quarter of data. Every number comes from the LUMÉ Bible — an economic model of the network built on real Kyiv clinic prices, ad rates and retention for 2026.

The finding reframes every movement that follows: three of the four studios are at their physical capacity ceiling. There is nowhere to push ad spend — new bookings crowd out returning patients. Growth is now about ticket size and a fifth studio, not cost per lead.

16 formula-driven sheets · n8n workflow · “reading the month” · LUMÉ Bible on Ukrainian data

Open the report (EN) →

The data showed where people are lost. Now, what happens in the messages.

Movement IX 100% of medical questions go to a doctor, not the front desk

Client communications

Ten inbound types, each with an owner and an SLA; frameworks instead of read-aloud scripts; a three-tier escalation matrix; a FAQ bot and a crisis playbook.

Negative reviews are answered in public, not deleted — a direct consequence of the trust position: you can't sell honesty and erase the inconvenient reviews. And a safety question about a procedure is, by law (MoH order №117), not for the front desk or the bot.

6 frameworks · 3 escalation tiers · n8n router · FAQ bot with a hard line

Open the movement (EN) →

The inbound flow is under control. Now, producing what that flow needs.

Movement X 14 blocks in the brief — a contract with the contractor, not a request

Writing briefs for creatives

The creative team is external contractors who weren't in the room and don't know Ukraine's medical-advertising law. The brief carries the load: 14 blocks, compliance checklist included, and nothing enters the queue with a field missing.

Plus a board with WIP limits and deadline control on a critical chain: a slip shows up at the 30%-of-schedule checkpoint, and the buffer sits on the chain as a whole rather than smeared across tasks where it quietly gets eaten.

5 brief templates · WIP limits · Asana CSV · acceptance by checklist

Open the movement (EN) →

The creative is ready. Now, how to launch it and when to stop.

Movement XI ₴4,400 the CAC that stops a campaign — set against LTV, not mood

A runbook for launching campaigns

Six phases with a QA gate between build and start. A UTM spec that makes the Movement VIII incident — a space in a tag, 50 leads lost to “(not set)” over 24 days — structurally impossible: the tag is generated, not typed.

The stop decision is made on CAC, checked against LTV from the Bible (the LTV/CAC = 4 line), inside a window of statistical significance. Not “switch it off when you're tired of spending”, but four outcomes: kill / hold / iterate / scale, each with a threshold.

6 phases · 1 gate · UTM generator · kill/scale grid · n8n guardrails

Open the movement (EN) →

The machine is built. Now the regulation that keeps it from breaking silently.

Movement XII +20% a tax in the model, repealed back in 2022 — caught in review

Background operations and QA

A schedule of checks by cadence — daily, weekly, monthly, quarterly — each line with an owner and a definition of failure. A synthetic lead hits every landing page every day: a broken form shows up in a day, not a month.

A finding from external review: the model kept a "non-resident advertising tax" (20% on Meta/Google) that had been repealed by Law No. 1525-IX back in 2022. The status was taken from an old source ("a repeal bill is in progress") and not checked against whether it had become law. Removed (verified against the primary text on zakon.rada): CAC ₴2,106 → ₴1,806. The status of a tax rule is data too, and it goes stale.

cadence-based regulation · synthetic form checks · advertising tax · n8n watchdog

Open the movement (EN) →

Five operational movements aren't only documents. There's automation running underneath.

Automation layer 107 nodes across five n8n workflows — they do the work, not draw dashboards

LUMÉ automation overview

Five n8n workflows and two Dify bots under movements VIII–XII. Lead intake keeps first- and last-touch attribution, captures click IDs, scores the lead by service and sets the SLA within Kyiv working hours. The router classifies inbound (keywords → Claude) and hands a medical question to a doctor, while a Lead Ads submission flows into the shared lead pipeline. Guardrails compute CAC with the advertising tax and message the marketer only when there is a decision: kill / iterate / scale. The watchdog sends a synthetic lead to every landing page every day — a broken form shows up in a day.

Everything writes to one Google Sheet — the same one the Movement VIII report reads from. A person gets a signal only when action is needed.

5 n8n workflows · 2 Dify bots · one data layer · deployment guide

Open the overview (EN) →

How I work

Three principles visible in the projects themselves, not merely claimed here.

I check myself

  • The audit has a section that dismantles my own opening accusation as unfair
  • In the GTM work, fresh data forced a change of target segment
  • On the landing page I retract an earlier recommendation the maths proved unworkable

I go to primary sources

  • The peer-reviewed study read in full, including its stated sampling limits
  • Regulator rules from the regulator; prices from published price lists
  • Data age and sample skew stated out loud

I show the arithmetic

  • Every formula is written out rather than hidden behind a result
  • One consistent method: ratios on gross profit, never on revenue
  • Every project carries a “what we don't know” section

About

I came into marketing for the numbers, not the pretty pictures. Everything here is built on open data: market reports, peer-reviewed publications, official regulator guidance, published clinic price lists. No figure without a source, and no conclusion without a note on how much it can be trusted.

English at B1: I read professional sources comfortably and write structured system prompts in English — reproduced in Movement VI. Working correspondence with preparation.


Materials

Bible
The LUMÉ network's economic foundation — model, sources, open risks
Automation
The n8n and Dify layer under the operational block (107 nodes)
Pitch
Defending the research — how to tell it in a minute and under a hard question (UK)
CV
CV · Dasha Dbar (UK)
Course
"Strategist's Workshop" — a training course built on this portfolio (UK)
Live demo
The LUMÉ sandbox — n8n, Cal.com, a FAQ bot, a market radar

Happy to discuss a brief

Open to marketing strategist, brand manager and performance marketing roles. Remote and relocation both considered.

Email
[email protected]
Telegram
@daridbr
Based in
Dnipro · remote · open to relocation