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Growth, Lifecycle & Marketing Operations

I build the systems that turn content, lifecycle & distribution into growth.

Lifecycle marketing, marketing automation, and AI-native workflows — strategy, execution, and optimization working together, across media, subscription, and digital-product businesses. Remote from Brazil, on US hours.

The receipts

8x

LinkedIn audience growth — 2,236 → 17,942 followers · The Brazilian Report, Jan 2023 – Jun 2026

7,427

LinkedIn newsletter subscribers, grown organically from launch — founders & CEOs among top readers

49.6%

Open rate on a rebuilt 3,152-subscriber list — well above media-newsletter benchmarks

The operating model How the four systems fit together

AI-Native Lifecycle & Growth Operating System

One model runs underneath everything: move a stranger to a habit across six stages, with AI on the repeatable middle and human judgment on every decision that matters. Each stage below names the mechanism I use, the AI workflow inside it, and the real system that proves it.

The lifecycle — mapped to real systems

01 Acquire Organic distribution across owned channels; content engineered to travel past the base. AI: research passes, format variants per channel. SYS/02 · 04
02 Onboard Day-one sequences and a clear first-value path on landing. AI: drafts welcome/first-touch copy from a fixed brief. SYS/03
03 Activate Landing & conversion paths optimized against live behavior. AI: variant copy for pages and CTAs. SYS/03
04 Engage Fixed-cadence newsletter; the rhythm is the product. AI: first drafts, format, SEO — never voice or judgment. SYS/01
05 Retain Segmented lifecycle, quality watched by open-rate as a health signal. AI: personalization drafts per segment. SYS/01 · 03
06 Reactivate Sequenced win-back to dormant segments, most-engaged first. AI: drafts re-engagement variants; human sets the offer. SYS/03
Human decision — what matters, the voice, the offer AI leverage — research, drafts, variants, QA support

The proof layer — capabilities, with evidence and honest maturity

Newsletter & email infrastructureProven

Owned lifecycle channel built and run solo on a fixed weekly clock, with segmentation and day-one sequences.

Evidence: 0 → 7,427 subscribers · 49.6% open rate on a rebuilt 3,152 list · SYS/01, SYS/03

AI-assisted research, drafting & QAProven

AI runs the repeatable middle — research, first drafts, format variants — behind a human QA gate nothing skips.

Evidence: sustained ~26 pieces/week across 4 accounts · unbroken 12-mo newsletter cadence · SYS/01, SYS/02, SYS/04

Website & landing-page optimizationProven

Conversion paths and landing pages optimized against live behavior during the subscription launch.

Evidence: revenue-ready launch in 30 days · conversion path rebuilt · SYS/03

Segmentation & automationBuilt

Engagement-based segments and sequenced journeys — lighter on triggered automation, honest about where it ends.

Evidence: staged migration by engagement cohort · lifecycle sequences · SYS/03

Multi-market operating scaleProven

One coordinated operation across two markets and four accounts — standardize once, localize at the edge.

Evidence: 1,702 posts / yr · 7,519 followers across the account set · SYS/04

Reporting & experimentationData-driven, not formal A/B

I iterate on real performance data — shifting production mix and framing on what the numbers show. I don't claim controlled A/B testing.

Evidence: per-format mix shifts on engagement data · reader-title-informed framing · SYS/02

One automated journey, end to end — subscription re-engagement

Dormant no opens, N weeks Segment by past engagement Draft win-back AI variants QA gate human · offer set here Send sequenced re-engaged → back into the active lifecycle

Case 01 The Newsletter System · Lifecycle & Audience

0 → 7,427 professional subscribers

The Brazilian Report · "Brazil Business News Roundup" · sole owner — strategy to send

Context

An English-language publication on Brazilian politics and economics — a Digiday Media Awards finalist alongside Axios and Harvard Business Review. I ran its marketing for 3.5 years alongside a cofounder. The newsletter was mine end-to-end.

Problem

The publication needed a recurring channel that could turn episodic social reach into habitual readership among business professionals. A LinkedIn newsletter offered native distribution, subscriber notifications, and direct access to the audience we wanted.

The constraint: no promotion budget, no dedicated writer — it had to run inside the existing operation without adding headcount.

Case 01 The System

A weekly pipeline, not a writing task

↺ Analytics feed back into research — formats that earn reads get more room next week.

Positioning aimed deliberately at senior readers: business framing, decision-maker relevance, no fluff. The format was designed to be producible on a strict weekly rhythm — the cadence was a feature, not an aspiration.

Case 01 Results

7,427

subscribers from zero — solo-owned, organic

77,942

article views, final 12 months — ~1,500/issue

LinkedIn newsletter analytics: 77,158 article views across 12 months, showing an unbroken pattern of weekly spikes
The cadence is the proof. Weekly and uninterrupted for 12 months — through holidays, shifting priorities, and competing production demands.
Reach among decision-makers. Founders, CEOs, co-founders, and owners consistently among the leading reader job titles.

SYS/01 The specification

How the newsletter system is wired

Research AI-assisted Draft fixed format QA gate human · nothing skips Publish same slot, weekly Distribute daily posting sys. analytics feed back — what earns reads gets more room next week
One key node. The QA gate (red) is the only place a human stops the line — everything upstream is AI-assisted, everything downstream runs on a fixed schedule.
Full specification Purpose, constraints, decision logic, stack, outcomes, lessons Open ↓Close ↑

Purpose

Convert episodic social reach into habitual, weekly readership among senior business decision-makers — a recurring subscriber channel more durable than one-off feed reach.

Business problem

Social reach was spiky and rented. The publication needed a recurring, owned touchpoint that compounded — without hiring a writer or spending on promotion.

Constraints

  • No promotion budget — growth had to be fully organic
  • No dedicated writer — had to run inside existing headcount
  • Strict weekly cadence — the rhythm was the product

Decision framework

Every issue answered one question: would a founder or CEO forward this? Format, length and framing were fixed in advance so production never stalled on taste debates. Cadence beat perfection.

AI workflows

AI ran the boring middle — scanning the week's signal, first-pass drafting inside a fixed briefing template, format variants. It never chose what mattered or set the voice.

Automation & distribution

Publishing locked to the same weekly slot and folded into the existing distribution calendar, so distribution required no separate decision.

Cross-functional partners

Editorial (fact & tone QA)Cofounder / strategySocial/distribution

Tools & stack

LinkedIn NewslettersChatGPTClaudeAnalytics exports

Business outcomes & metrics

  • 7,427 subscribers from zero — solo-owned, organic
  • 77,942 article views in the final 12 months (~1,500/issue)
  • Founders, CEOs, owners consistently top reader titles
  • Unbroken weekly cadence for 12 months, through shifting priorities

Lessons learned & how I'd improve it today

Readership stayed consistent; the acquisition engine needed a second stage. Growth plateaued once the organic audience matured. Today I'd wire a referral loop and cross-promotion partnerships in from month one, instead of leaning on platform distribution alone — and A/B the subject framing against the reader-title data I was already collecting.

Case 02 The Organic Distribution Engine · Operations

1,174 posts in 365 days. One person.

The Brazilian Report · multi-channel distribution, effectively zero ad spend

Problem

The publication needed daily presence across every channel while resources and production capacity were becoming increasingly constrained. No ad budget. No additional headcount. The bottleneck was never ideas — it was the distance between idea and published.

The System

AI pointed at the boring middle — research passes, first drafts, format variations, SEO checks. Never at the judgment calls.

What stayed human: what was worth covering, what the brand sounded like, and a QA gate nothing skipped.

↺ Performance data feeds back into what gets made next week.

Case 02 Results

548K

impressions in 12 months — 99.2% organic

102K

content clicks — 19.7% engagement incl. clicks

8x

LinkedIn audience across tenure — 2,236 → 17,942

The channels we actively rebuilt grew the most. The ones without a dedicated system stayed comparatively flat.
Idea intake single queue Format factory templated · AI-assisted Schedule queue set & forget LinkedIn Instagram YouTube TikTok per-format data → intake
The factory is the key node. One idea becomes many formats before it ever hits a channel — the leverage is upstream of distribution.
Full specification Purpose, constraints, decision logic, stack, outcomes, lessons Open ↓Close ↑

Purpose

Sustain daily presence across every channel with one operator, by collapsing the distance between having an idea and it being published.

Business problem

As resources and production capacity tightened, the audience still expected daily output. The bottleneck was never ideas — it was throughput from idea to live post.

Constraints

  • Effectively zero ad spend — organic only
  • One person — no additional headcount
  • Every channel, every day — cadence could not drop

Decision framework

Produce once, adapt many. No format got bespoke effort until the data earned it. Anything that couldn't be templated didn't enter the pipeline.

AI workflows

AI handled research passes, first drafts and per-channel format variations inside fixed templates — turning one core idea into a full day's cross-channel set.

Automation & distribution

Content was batched and scheduled ahead of time, so daily publishing ran without a daily decision.

Cross-functional partners

EditorialDesignLeadership (shifting priorities)

Tools & stack

AI research & draftingScheduling systemsPlatform analytics exports

Business outcomes & metrics

  • 1,174 posts in 365 days, one operator
  • 548K impressions in 12 months — 99.2% organic
  • 102K content clicks — 19.7% engagement incl. clicks
  • 8× LinkedIn audience across tenure (2,236 → 17,942)

Lessons learned & how I'd improve it today

Engagement concentrated in evergreen and visual formats, and I had the per-format data for months before I acted on it. Today I'd make the feedback loop enforce itself — shift the production mix on the data far earlier and cut formats that were only earning volume, rather than reviewing by hand.

Case 03 Subscription Infrastructure · Lifecycle & Subscription

Launch the product, then move it — without losing the audience

The Brazilian Report · one system, two phases: a revenue-ready launch, then an audience-safe migration

Problem

Launch a paid subscription product on a 30-day clock — then, later, move the entire newsletter operation off a complex legacy WordPress stack without losing the audience in the cutover.

The System · two phases

Phase 1 — Revenue-ready launch: cut "launch" down to what actually blocked revenue — positioning, site structure, the conversion path, the day-one lifecycle emails. Everything else waited.

Phase 2 — Audience-safe migration: staged communications instead of one blast, segmented by engagement — most active readers first and most often. Every message answered the reader's only real question: what do I do, and when.

Case 03 Results

30

days from brief to live subscription platform

3,152

active subscribers on the rebuilt list

49.6%

open rate — media benchmarks typically run 30–40%

What I can and can't prove

I can't give you a clean retention figure for the cutover itself. The legacy stack's analytics are gone, and I didn't own that reporting at the time.

The figures above are the rebuilt list's current performance — I'd rather cite those than quote a number I can't stand behind. I don't publish the platform dashboards; they belong to the publication, not to me. Happy to walk through the detail in a conversation.

Where the credit sits

The editorial team wrote the journalism — award-shortlisted work by real journalists.

I built and moved the machine around it: the subscription platform, the migration, the lifecycle programs, and the growth work on top. The open rate is what the audience does with all of it together.

Stack — beehiiv · WordPress (legacy) · segmented lifecycle sequences · subscription tiers & access logic

Full specification Architecture, migration logic, constraints, outcomes, lessons Open ↓Close ↑
Segment by engagement Pre-warn most active first Cut over new stack live Re-engage sequenced Monitor opens = health the ordering is the risk control
Sequence over blast. Pre-warning the most engaged readers first (red) meant the cutover was de-risked by the people most likely to survive it.

Purpose

Two jobs in one system: launch a paid subscription product fast, then move the whole newsletter operation to a new stack without losing the audience in the cutover.

Business problem

A 30-day clock on revenue, and a complex legacy WordPress stack that couldn't be carried forward — but whose audience was the entire asset.

Constraints

  • 30 days to live — brief to paid product
  • Minimize audience loss — the list was the business
  • Legacy analytics dying — reporting wouldn't survive the move

Decision framework

Cut "launch" to only what blocked revenue — positioning, site structure, the conversion path, day-one lifecycle. For migration: stage by engagement, and make every message answer one reader question — what do I do, and when.

Automation & lifecycle

Segmented lifecycle sequences, subscription tiers and access logic — sequenced comms instead of a single blast, most-active cohorts first and most often.

Cross-functional partners

Editorial (award-shortlisted journalism)Engineering (stack)Leadership

Business outcomes & metrics

  • 30 days from brief to live subscription platform
  • 3,152 active subscribers on the rebuilt list
  • 49.6% open rate — media benchmarks run 30–40%

I can't give a clean cutover-retention figure — the legacy analytics are gone and I didn't own that reporting. I'd rather cite the rebuilt list's real performance than a number I can't stand behind.

Lessons learned & how I'd improve it today

The gap I'd close is measurement, not method. The staged migration worked, but I couldn't prove the cutover cleanly because instrumentation lived on the stack I was leaving. Today I'd stand up independent tracking before touching the legacy system, so the before/after is mine and portable — the machine was right; the evidence trail wasn't.

SYS/04 Multi-Market Marketing OS · Growth Ops · Real Estate

One marketing operation, two markets, many agents

Jana Caudill Team · coordinated marketing across Northwest Indiana & Southwest Florida — proof the systems thinking transfers beyond publishing

1,702

posts across 4 channels & 2 markets in 12 months

~26

pieces per week, sustained — one coordinated operation

7,519

followers across the full account set — 4 pages, 3 platforms

Problem

Marketing was fragmented across two geographies, multiple agents, several websites, and many production channels — listings, open houses, newsletters, email blasts, print, social, and recurring market reports — with no single operating layer holding it together.

The System

One intake and one production standard feeding every market and channel: a shared template library, a single content calendar, and a defined hand-off so any listing or report moves through the same path regardless of market.

The point isn't more output — it's that two markets run on one coordinated machine instead of two ad-hoc ones.

NW Indiana market · agents SW Florida market · agents Marketing OS intake · templates · calendar Listings & open houses Email & newsletters Social distribution Print Market reports many inputs → one standard → every channel
Convergence, not more output. Two markets and many agents feed one operating layer (red) — the leverage is the single standard, not the volume of channels.
Full specification Purpose, constraints, decision logic, stack, outcomes, lessons Open ↓Close ↑

Purpose

Give two geographically separate markets one coordinated marketing operation, so quality and cadence don't depend on which market or agent is producing.

Business problem

Fragmented marketing across two markets, multiple agents, multiple websites, and many production channels — no shared standard, so effort was duplicated and output was uneven.

Constraints

  • Two distinct markets — different inventory, seasonality, audience
  • Multiple agents & sites — many hands, one brand
  • Lean operation — coordination can't add headcount

Decision framework

Standardize once, localize at the edge. Anything repeatable across markets becomes a template; only genuinely market-specific detail is produced fresh. The audience data shows the localization lands — top follower cities are the actual target markets (Crown Point, Valparaiso, Schererville), not scattered reach. It also shows the system working across pages: the brand-new Florida Facebook page's top follower city is Crown Point, Indiana — the established NW Indiana audience seeding the new market, exactly what one coordinated operation is supposed to do.

AI workflows

AI handles first-pass copy normalization and format variants from a single listing or report input — turning one source into the set each channel needs. Human judgment sets positioning and approves before anything ships.

Automation & distribution

A shared content calendar and templated production path move each listing, blast, and recurring report through the same steps across both markets — so ~26 pieces a week ship without ~26 separate decisions.

Cross-functional partners

Agents (both markets)Team leadershipDesign / print vendors

Tools & stack

Facebook — 2 pages (per market)Instagram — sharedLinkedIn — sharedTemplate libraryShared content calendarSocial analytics

Business outcomes & metrics

  • 1,702 posts across 4 channels & 2 markets in 12 months (~26/week)
  • 471K + 78K FB views · 105K Instagram views · one coordinated operation
  • 7,519 followers across the full account set — 4 pages over 3 platforms
  • ~48% of Instagram reach from non-followers — content travels past the base

Lessons learned & how I'd improve it today

The transferable lesson: the industry changed, the method didn't. The same constraint-first, standardize-then-localize approach that ran a newsroom runs a two-market real-estate operation. The honest nuance: the two Facebook pages are at different ages — NW Indiana is years old and grew (+163 net followers), while the SW Florida page is new and is still being seeded off the Indiana base, so its raw totals are naturally smaller. Today I'd close two gaps: per-market reporting that accounts for page age so a young market isn't judged against a mature one, and lead attribution from social to inquiry, which the current stack doesn't yet trace end-to-end.

About

"I don't just create content — I build the structure behind it."

Eight years across marketing and design, trained originally in architecture — where the systems thinking comes from. I spent 3.5 years running marketing at The Brazilian Report through platform launches, audience growth, and major operational transitions; today I run marketing for the Jana Caudill Team across two US real estate markets, turning fragmented channels into one coordinated, lead-focused system.

Portuguese native, English fluent. Remote from Brazil, on US hours.

Contact

Talk to me

Hiring for lifecycle, growth, or marketing operations — or want the systems behind any of these numbers? The analytics exports are all saved.

lab.victorkq@gmail.com

Or just email me directly — whichever is faster for you.