Sales & Conversion
Personas
Ecommerce
Time to ROI
Short-term (< 3 months)
OK, so you're probably here because you want to know what "good" email open rates look like for ecommerce. You've probably read somewhere that 20-25% is the industry average and you're either celebrating because you're above it or panicking because you're below it.
But here's the thing – I've worked with dozens of ecommerce stores, and the ones obsessing over industry averages are usually the ones leaving the most money on the table.
Last month, I helped a Shopify store owner who was celebrating their 28% open rate while completely missing the fact that their emails were generating almost zero revenue. Meanwhile, another client with a "terrible" 15% open rate was pulling in 30% of their monthly revenue from email campaigns.
The real question isn't "what's the average open rate?" – it's "what open rate actually drives revenue for MY business?" And that's exactly what we're going to figure out.
In this playbook, you'll discover:
Why industry averages are misleading for your specific business
The actual metrics that matter for ecommerce email success
How I doubled email revenue for clients while their open rates stayed flat
The framework I use to optimize for profit, not vanity metrics
Real examples from automated email workflows that actually convert
Industry Reality
What every ecommerce owner believes about email metrics
Let me guess – you've been told that email open rates are the holy grail of email marketing success. The industry loves throwing around these "benchmark" numbers:
Retail average: 18-22% according to most email platforms
Fashion/apparel: 15-20% depending on the source
Beauty/cosmetics: 20-25% because engagement is supposedly higher
Electronics: 18-23% for tech-savvy audiences
Food/beverage: 20-28% since people love food content
Every marketing blog, email platform, and "guru" will tell you to aim for these numbers. They'll show you colorful charts and industry reports that make these averages seem like gospel truth.
The conventional wisdom goes like this: higher open rates mean more people are seeing your emails, which means more clicks, which means more sales. It's logical, right?
And honestly, this thinking isn't completely wrong. Open rates DO matter to some extent. But here's where the industry gets it backwards – they've made open rates the PRIMARY metric instead of a supporting one.
The problem with chasing industry averages is that your business isn't average. Your audience isn't average. Your products, pricing, seasonality, and customer lifecycle are unique to you. Optimizing for someone else's average is like trying to wear someone else's clothes – it might fit, but it's probably not going to look great.
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 sold handmade jewelry. When they first came to me, they were frustrated because their email open rates were consistently around 12-15%, way below the "industry average" of 20-25% for retail.
They'd tried everything the email marketing blogs suggested: A/B testing subject lines, sending at "optimal" times, segmenting by purchase history. Their open rates improved slightly, maybe hitting 17% on a good day, but their email revenue stayed flat.
Here's what was actually happening: their customer base was primarily women aged 35-55 who checked email once or twice a day, not constantly like younger demographics. They were quality email readers, not quick scrollers.
Meanwhile, I was working with another ecommerce client selling phone accessories. Their open rates were consistently hitting 25-30%, which looked amazing on paper. The problem? Their audience was mostly impulse buyers who opened emails but rarely converted. High engagement, low value.
That's when I realized we were optimizing for the wrong metric entirely. The jewelry client with "bad" open rates was generating 25% of their monthly revenue from email, while the phone accessories client with "great" open rates was pulling in maybe 8%.
The difference wasn't in the open rates – it was in the intent and value of the audience. The jewelry buyers opened fewer emails, but when they did, they were serious about purchasing. The phone accessory browsers opened everything but bought nothing.
This experience completely changed how I approach email optimization for ecommerce stores.
Here's my playbook
What I ended up doing and the results.
Instead of chasing industry averages, I developed what I call the Revenue-First Email Framework. Here's exactly how it works:
Step 1: Calculate Your Email Revenue Rate (ERR)
Forget open rates for a moment. I start by calculating how much revenue each email generates per recipient. Here's the formula: Total email revenue ÷ Total emails sent = Email Revenue Rate.
For the jewelry client, this looked like: $15,000 monthly email revenue ÷ 50,000 emails sent = $0.30 per email. For the phone accessory client: $3,200 ÷ 40,000 emails = $0.08 per email.
Suddenly, the "low performing" jewelry emails were actually 375% more valuable than the "high performing" phone accessory emails.
Step 2: Segment by Purchase Intent, Not Demographics
I stopped segmenting by age, location, or purchase history. Instead, I created segments based on email behavior that indicated buying intent:
"Product Browsers" – opened product-focused emails in the last 30 days
"Sale Seekers" – only opened emails with discount keywords
"Content Consumers" – opened educational/lifestyle emails consistently
"VIP Buyers" – purchased within 48 hours of opening any email
Step 3: Optimize for Revenue Per Segment
Here's where it gets interesting. Instead of trying to improve overall open rates, I optimized each segment for maximum revenue generation:
For VIP Buyers, I sent fewer emails but made them extremely targeted. Open rates dropped from 28% to 22%, but revenue per email doubled because these people were getting exactly what they wanted to buy.
For Sale Seekers, I increased email frequency during promotions. Open rates went up slightly, but more importantly, conversion rates increased by 40% because we were hitting them at their most receptive moments.
For Content Consumers, I mixed educational content with soft product recommendations. Open rates stayed steady at 20%, but click-through rates to product pages increased by 60%.
Step 4: The 72-Hour Revenue Tracking
This was the game-changer. Instead of tracking immediate email clicks, I started tracking all revenue generated within 72 hours of each email send. This revealed that many "failed" emails were actually triggering purchases days later through other channels.
The jewelry client's abandoned cart emails had terrible open rates (8-12%), but they were generating massive revenue through website visits and social media engagement that happened 24-48 hours after the email was sent.
Revenue Tracking
Track total revenue generated within 72 hours of each email send, not just immediate clicks from the email.
Intent Segmentation
Segment subscribers based on email behavior patterns that indicate purchase intent rather than demographics.
Value Optimization
Optimize each segment for maximum revenue per email rather than maximum open rate across all subscribers.
Quality Focus
Focus on attracting and retaining high-value email subscribers rather than growing list size with low-intent users.
The results completely transformed how both clients approached email marketing. For the jewelry client, we actually decreased their overall open rate from 15% to 13%, but increased their email revenue by 85% over six months.
Here's what happened: by focusing on revenue per email instead of open rates, we identified that their most valuable customers preferred longer, more detailed emails with multiple product options. These emails had lower open rates but much higher conversion rates.
The phone accessory client saw different but equally impressive results. We segmented their list more aggressively and stopped sending daily emails to low-intent subscribers. Their open rates dropped from 28% to 24%, but their email revenue increased by 120% because we were focusing on their highest-value segments.
The most surprising discovery was about email frequency. Conventional wisdom says more emails = lower open rates. But for high-intent segments, increasing email frequency actually improved both open rates AND revenue. People who want to buy from you want to hear from you more often, not less.
Within 90 days, both clients were generating more revenue from email than they had in the previous year, despite having "worse" open rates according to industry standards.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons I learned from optimizing for revenue instead of open rates:
Industry averages are marketing tool benchmarks, not business success metrics. They're designed to make email platforms look good, not to maximize your profits.
Email behavior varies dramatically by product price point. High-ticket items have different email patterns than impulse purchases.
The best email subscribers aren't always the most active ones. Quality trumps quantity every single time.
Revenue attribution is complex. Many email "failures" are actually contributing to sales through other channels.
Segmentation by intent beats segmentation by demographics. How people interact with your emails matters more than who they are.
Frequency optimization is individual to each segment. Some people want daily emails, others want weekly. Both can be profitable.
Lower open rates can indicate higher purchase intent. Serious buyers are more selective about which emails they open.
The biggest mindset shift was realizing that email marketing isn't about broadcasting to the masses – it's about having the right conversations with the right people at the right time. Sometimes that means fewer people see your emails, but more people buy your products.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies, focus on trial-to-paid conversion rates rather than open rates. Track emails that lead to feature usage and upgrade decisions, not just opens and clicks.
For your Ecommerce store
For ecommerce stores, segment by purchase behavior and optimize for revenue per email sent. Track 72-hour attribution and focus on high-intent subscriber quality over list size.