Content Generation · Read + Write

Marketing email + 3 ranked variants

Augment Rep · High Reason · Med

The problem

Each campaign needs 1 marketer for ~5 hours — writing subject lines, body copy, CTAs. A/B variants get skipped because no time. Results swing.

The AI approach

LLM drafts 3 variants in your brand voice from a brief; a predictive ranker trained on past sends scores expected open-rate; brand grid checks tone.

The outcome

5 hr → 25 min

3 variants always, ranked by expected open-rate. Marketer edits the winner and ships.

Try itInput → Process → Output

Input — Campaign brief
Brief B-2026-44Q2 nurture
AudienceSMB owners · 10–50 staff · trial-day 14
Offer30% off annual plan · 7 days only
CTA goalStart free trial → upgrade
Send windowTue 09:00 · Bangkok time
Brand voicepractical · jargon-free · never hype · "you" not "we"
Process — AI pipeline
1Read brief + brand voiceReadSymbolic
2Draft 3 variants (LLM)WriteGenerative
3Predict open-rate per variantRankPredictive
4Brand grid + ESP formatWriteSymbolic
Output — 3 variants ranked
Click Run demo to draft 3 brand-voice variants and rank them by predicted open-rate.
EMAIL VARIANTSready · Mailchimp
PICK
A · practical42.8%
7 days left on your trial — keep what you've built
Your team's already set up 3 dashboards. Lock in the annual plan and they stay.
Continue at 30% off →
B · curious31.4%
A question before your trial ends
Which dashboard saved you the most time this week? Lock that in for $9/mo.
Show me the offer →
C · direct28.1%
30% off annual — for the next 7 days
No fluff: same plan, 12 months for the price of 8. Click to upgrade.
Upgrade now →

Three AI types in this use case

SymbolicBrand glossary, do/don't word list, claim guardrails, ESP-format rules (subject ≤ 60 chars, alt-text, UTM).
PredictiveOpen-rate ranker (gradient-boosted on past sends × subject features × audience segment).
GenerativeLLM drafts subject, body and CTA per tone; rewrites for brand voice; explains why each variant works.

The stack

  • LLM · Claude Opus 4.7
  • Brand · YAML glossary + rules
  • Ranker · XGBoost on past sends
  • ESP · Mailchimp / Klaviyo / HubSpot

When this works

  • Brand voice codified (don't / always words)
  • ≥ 20k past sends for ranker training
  • Audience segments defined
  • Marketer reviews before send

When it fails

  • Brand new product — no past sends to learn from
  • Regulated copy (finance, pharma) — needs legal review
  • Event-sensitive timing (crisis, holiday)
  • Generic LLM voice leaks past the glossary