Bryant Nankee · 2026
Designed for 10+ concurrent campaigns across Growth, Client Marketing, and Brand — with structured intake, AI-assisted QA, locked UTM conventions, and measurement that connects directly to business outcomes.
As Twin scales across Growth, Client Marketing, and Brand — running member engagement, B2B pipeline, retention, and always-on programs simultaneously — the risk isn't any single campaign failing. It's the system breaking under volume: missed suppressions, inconsistent attribution, delayed launches, and leadership flying blind.
A 2×4 matrix plus team ownership layer means any request gets classified instantly — no ambiguity about what it is, who owns it, or how it gets measured.
Highlighted cells = current highest priority based on Twin's growth stage and retention economics
Every campaign gets tagged: team_motion_audience_YYYYQX — this tag flows through everything: name, UTM, Braze tag, Lightdash filter.
Every campaign follows the same path. Requests come through a structured form. Nothing gets built without a brief. Nothing launches without QA sign-off.
No tool lives in isolation. Every platform passes data to the next. The UTM convention is the thread that ties them all together for clean attribution.
| Tool | Owner | MarOps Role |
|---|---|---|
| HubSpot | MarOps | B2B campaigns, build + launch |
| Snowflake | Data & MarTech | Validate outputs |
| Hightouch | Data & MarTech | Scope + validate syncs |
| Braze | Shared / MarOps | Member campaigns, QA, launch |
| Short.io | MarOps | Own all UTM links |
| Lightdash | Analytics | Scope reports, review |
| Monday | MarOps | Own the intake queue |
Five lifecycle stages. Every campaign targets one. Overlap is managed by suppression — not audience design. Audiences are built in Snowflake and synced to Braze via Hightouch.
Habits slip under pressure. Systems don't. Every campaign runs through an AI pre-flight before a human reviews the report — not a blank checklist starting from zero.
AI handles everything binary — did the sync run, does the link resolve, is suppression applied, does the UTM match the convention. The human reviews the AI's report + content/compliance items AI can't assess. Human QA time: 30 min → 5 min.
Leadership lives in Tier 1 — outcomes, protected revenue, trends. Ops and channel owners live in Tier 2 — channel performance, UTM attribution, anomalies.
| Metric | Business Value |
|---|---|
| Member Retention Rate % active at 30/60/90 days |
Each retained = $8K+ annualized savings |
| At-Risk Reactivation Rate % re-engaged within 14 days |
Proxy for churn prevention ROI |
| B2B Pipeline Influenced Deals touched by marketing |
Revenue attribution to marketing |
| Protected Revenue Retained members × $8K |
Twin's own published ROI metric |
| Channel | Key Metrics |
|---|---|
| Email (Braze) | Open rate ±baseline, CTR, unsubscribe, conversion |
| SMS (Braze) | Delivery, click rate, opt-out rate |
| Paid Media | CPL, CTR, UTM-attributed pipeline via Salesforce |
| Direct Mail | Delivery confirmation, response via short link |
| In-App | Impression rate, click, action taken post-view |
Enter a brief and watch the system run — AI generates the architecture, QA checklist, and UTM. A real Short.io tracking link is created. Send it to reviewers and watch clicks come in live.
A Slack-native agent that acts like a senior brand strategist — asking goal-first questions, catching bad briefs early, and handing a structured campaign spec directly to the execution engine.
Forms get filled out mindlessly — people describe what they want to run, not why it matters. A conversational agent flips the frame: it asks about business outcomes first, validates in real time against active campaigns and suppression rules, and refuses to generate a brief until the context is solid. By the time a brief hits the MarOps queue, it's already been filtered.