Email Marketing — List, Segmentation, Automation
Build an email engine that compounds. List acquisition, segmentation that respects subscribers, automated sequences (welcome, cart-abandon, re-engagement) — measured by revenue, not opens.
About this course
Email is the highest-ROI marketing channel after referral — and the most underused in MENA. We build a real email program: list signups that don't tank conversion, segmentation that increases (not decreases) deliverability, and 4 automated sequences that earn money in their sleep. Klaviyo-friendly but the patterns transfer to Mailchimp, ActiveCampaign, and HubSpot.
What you'll cover
- 1
Why email still wins
Owned vs rented audience. The math of email vs paid ads.
- 2
List building without ruining the page
Pop-ups that convert. Lead magnets. The 5 form mistakes.
- 3
Deliverability and the inbox
SPF, DKIM, DMARC. Warming up. Why your emails go to Promotions.
- 4
Segmentation that pays back
Behavioral vs demographic. RFM segmentation. The 3 segments to start with.
- 5
The welcome sequence
The 4-email welcome that converts cold subscribers. Real templates.
- 6
Cart abandon, browse abandon, win-back
Three flows that print money for e-commerce. Triggers, timing, content.
- 7
Measurement — opens lie, revenue doesn't
Revenue per recipient. The metrics that matter post-iOS 15.
Who it's for
E-commerce marketers, SaaS marketers, founders running their own marketing, and freelancers selling email setup.
Prerequisites
Some marketing background. You've sent at least one email campaign before.
Skills you'll build
- email marketing
- Klaviyo
- Mailchimp
- deliverability
- segmentation
- automation
- lifecycle marketing
- DMARC
Who we're looking for
Open call · Apply to teachRequired skills
- email marketing
- Klaviyo
- Mailchimp
- deliverability
- segmentation
- automation
- lifecycle marketing
- DMARC
Experience
3+ years professional experience
Languages
English or Arabic (both a plus)
Time commitment
8 sessions × 90 min over 6 weeks
Compensation
80% of seat revenue (Tahout takes 20%)
If your CV matches, apply to teach. We use AI to rank applicants by fit, then admin reviews and approves the right instructor(s).
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