AI & Automation
Personas
Ecommerce
Time to ROI
Short-term (< 3 months)
Every marketing "expert" will tell you the same thing about email frequency: "Don't overwhelm your subscribers." "Respect their inbox." "Follow the golden rule of once per week maximum."
I used to believe this religiously. I'd carefully space out emails, agonize over sending "too many," and watch my revenue plateau while my competitors seemed to be everywhere at once.
Then I worked with a Shopify client who was drowning in inventory and needed to move products fast. We were facing a simple choice: follow best practices and hope for gradual growth, or test what actually works regardless of what the gurus say.
What happened next challenged everything I thought I knew about email marketing. We didn't just increase frequency - we completely rethought how email campaigns work in the context of real business needs versus theoretical best practices.
Here's what you'll learn from this experience:
Why industry "best practices" often ignore business reality
The email frequency framework that actually drives revenue
How to test frequency without destroying your list
When to ignore unsubscribe rates completely
The psychology behind why customers actually want more emails (when done right)
This isn't about spamming your list - it's about understanding that ecommerce email strategy has fundamentally different rules than B2B newsletters.
Industry Reality
What Every Email Marketer Gets Wrong About Frequency
Walk into any marketing conference and you'll hear the same tired advice about email frequency. The industry has settled on a comfortable set of "rules" that sound professional but often ignore business reality:
The Standard Advice:
Send emails once per week maximum
Always prioritize open rates over revenue
Unsubscribes are the ultimate failure metric
Segment religiously before increasing frequency
"Quality over quantity" in all scenarios
This conventional wisdom exists because it feels safe. Nobody gets fired for following industry best practices. Marketing managers can point to "expert recommendations" when campaigns underperform.
But here's the uncomfortable truth: these rules were largely created by B2B SaaS companies and newsletter publishers, not businesses that need to move physical inventory or drive immediate purchases.
The problem with this one-size-fits-all approach is that it completely ignores the fundamental differences between business models. A B2B software company building long-term relationships has different needs than an ecommerce store trying to clear seasonal inventory.
Most importantly, these "best practices" assume that all email subscribers have the same relationship with your brand - which is demonstrably false when you look at actual customer behavior data.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
I learned this lesson the hard way while working with a Shopify client who ran a fashion ecommerce store. They had built a decent email list of about 15,000 subscribers but were struggling with a classic problem: too much inventory and not enough sales velocity.
Their existing email strategy followed all the "best practices" perfectly. One newsletter per week, carefully crafted content, beautiful design, respectable 22% open rate. Everything looked great in the marketing reports.
But when we dug into the revenue numbers, something wasn't adding up. Email was generating less than 8% of their total revenue, despite being their largest owned audience. Meanwhile, their SMS campaigns (which they sent more frequently) were pulling 23% of revenue from a list one-tenth the size.
The client was hesitant to change their approach. "We don't want to annoy our subscribers," they said. "What if people unsubscribe?"
I asked a simple question that changed everything: "How many of your current subscribers have purchased in the last 90 days?"
The answer was devastating: only 12% of their email list had made a purchase in the last quarter. We were treating 88% of subscribers like potential customers when they were actually just digital window shoppers.
This realization led us to completely rethink our frequency strategy. Instead of treating all subscribers equally, we started treating them like what they actually were: different segments with different relationships to the brand.
Here's my playbook
What I ended up doing and the results.
Here's exactly what we implemented, step by step:
Phase 1: The Segmentation Reality Check
First, we abandoned the fantasy that all subscribers are equal. We created three distinct segments based on actual behavior:
Hot Buyers: Purchased in the last 30 days (8% of list)
Warm Prospects: Purchased 31-90 days ago or highly engaged (15% of list)
Cold Subscribers: No purchases in 90+ days (77% of list)
Phase 2: The Frequency Experiment
Instead of sending one email per week to everyone, we tested a completely different approach:
Hot Buyers: Daily emails during sales periods, 3x per week normally
Warm Prospects: 2x per week with targeted offers
Cold Subscribers: Once per week maximum (our old frequency)
Phase 3: Content Strategy Overhaul
We stopped treating emails like newsletters and started treating them like what they actually are: sales opportunities. Each email had one clear purpose: drive a specific action.
For Hot Buyers, we sent:
New arrival notifications (they were already proven buyers)
Restock alerts for items they'd viewed
Exclusive early access to sales
Cross-sell recommendations based on purchase history
Phase 4: The Unsubscribe Mindset Shift
This was the biggest mental hurdle for the client. We had to reframe unsubscribes from "failure" to "list hygiene." People who unsubscribe from frequent emails were never going to be high-value customers anyway.
We tracked what actually mattered: revenue per email sent, not vanity metrics like open rates.
Phase 5: Testing and Iteration
We A/B tested frequency within each segment, gradually increasing until we found the revenue sweet spot. The key was watching revenue metrics, not engagement metrics.
We also implemented abandoned cart recovery sequences that could send up to 5 emails over 10 days - something that would have horrified the old "best practices" mindset.
Segmentation Strategy
Split your list by purchase behavior, not demographics. Recent buyers want frequent updates, cold subscribers don't.
Revenue Tracking
Monitor dollars per email sent, not open rates. A 15% open rate that generates $500 beats a 25% open rate that generates $200.
Unsubscribe Reframe
View unsubscribes as list cleaning, not failure. People who leave weren't going to buy anyway - you're just making room for real customers.
Frequency Testing
Test upward gradually within segments. Start with your hottest buyers - they can handle the most frequency and generate the most revenue.
The results were honestly shocking, even to me:
Revenue Impact:
Email revenue increased from 8% to 31% of total store revenue
Average revenue per email sent increased by 240%
Hot buyer segment showed 67% higher lifetime value
List Health:
Yes, we lost about 8% of subscribers in the first month
But the remaining list was 3x more valuable per subscriber
Engagement rates actually increased among remaining subscribers
Timeline:
Week 1-2: Implemented segmentation and increased frequency
Week 3-4: Saw initial revenue uptick and subscriber churn
Month 2: Revenue gains stabilized, churn stopped
Month 3: Hit our highest email revenue month ever
The most surprising outcome? Customer complaints actually decreased. When we sent more relevant, frequent emails to people who actually wanted them, satisfaction went up.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons that completely changed how I think about email frequency:
1. Frequency isn't the problem - relevance is. Sending daily emails to recent buyers isn't spam, it's good customer service. Sending weekly emails to people who haven't bought in two years is the real waste.
2. Industry best practices often optimize for the wrong metrics. Open rates and unsubscribe rates are vanity metrics if they don't correlate with revenue. A smaller, more engaged list always beats a larger, passive one.
3. Your best customers want more communication, not less. People who love your brand want to hear from you frequently. The "don't overwhelm" advice assumes everyone is on the fence about your business.
4. Segmentation should be behavior-based, not demographic-based. How recently someone bought tells you more about their email preferences than their age or location.
5. Test upward, not downward. Most businesses are sending too few emails, not too many. But you'll never know until you test increasing frequency with your best segments.
6. Unsubscribes can be a positive signal. When non-buyers leave your list, your email performance metrics improve across the board. Don't fight to keep subscribers who don't contribute to revenue.
7. Different business models need different email strategies. B2B advice doesn't apply to ecommerce, and newsletter advice doesn't apply to promotional emails.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups implementing this frequency strategy:
Segment by trial usage and feature adoption, not just signup date
Send daily emails during trial periods to high-engagement users
Focus on educational content that drives product usage
Track activation metrics, not just open rates
For your Ecommerce store
For ecommerce stores applying this playbook:
Segment immediately by purchase recency and frequency
Send daily emails to customers who bought in the last 30 days
Use frequency to move inventory during sales periods
Monitor revenue per email, not engagement rates