Top Brands Get Half Their Email Revenue From 6% of Sends. Here's What Those Sends Are and How to Replicate Them

Most email strategies are still built around campaigns, but performance is coming from somewhere else. Automated flows make up just 6 percent of sends, yet generate $513 per 1,000 emails compared to $62 for campaigns. That is an 8x difference. And this pattern shows up consistently across North American e-commerce brands.

The math is clear: campaigns build awareness, flows convert it. Yet most brands still pour the bulk of their email effort into blasts, while leaving flow revenue on the table.

And here's what separates good from great: Our top performers get over half their email revenue from flows alone. Not because they run more of them, but because they run them better. These flows use branching logic, personalized content, and artificial intelligence-optimized timing.

Here's what those flows look like at every stage of the customer journey — broken down and ready to copy.

1. Welcome Flows That Adapt to Who Just Signed Up

Most welcome sequences treat every subscriber the same — a discount code and a brand story. A customer who just bought something still gets a "here's 10% off your first order" message. It's a waste of a send and a bad first impression.

The fix is simple: branch based on customer state.

Pinemelon, an online grocery service, gets 55.8 percent of its direct-to-consumer revenue from automated campaigns. One reason is its welcome series. It branches based on purchase status — buyers get content designed to increase order frequency, while new subscribers get personalized product picks and a promo code.

2. Browse Abandonment Flows That Convert Window Shoppers

Between the first click and the final purchase, consumers drop off at a dozen different points — search, category browse, product page, wish list, cart, checkout. Each stage reflects a different level of intent, which means a single reminder isn’t enough. This is where leading brands take a different approach.

Coolibar, a UPF 50+ apparel brand, runs two flows most brands don't have. A Price Drop Alert notifies shoppers when an item they viewed or carted goes on sale. An Abandoned Collection flow fires even earlier — when a shopper browses a category but leaves without adding anything to cart. After rolling out these and other specialized flows, flow revenue grew 62 percent and abandoned-item revenue tripled.

Magnum Bikes sells everything from $3,000-plus flagship e-bikes to pre-owned models to accessories. Therefore, a single browse abandonment email would be tone-deaf. Magnum Bikes built flows that branch by product category. Someone looking at a top-tier e-bike gets feature-focused messaging, while someone browsing the outlet gets value-driven emails with links to discounted inventory. In its first full year on Maestra, online revenue grew 56.6 percent and order volume more than doubled.

The closer the message matches what the shopper was actually browsing, the higher the conversion. Generic "come back!" emails waste the opportunity.

3. Post-Purchase Flows That Turn One-Time Buyers Into Repeat Customers

A confirmation email and a shipping notification aren't a post-purchase strategy. The real opportunity is what comes after, recommending what makes sense based on what the customer just bought, and doing it before the customer forgets about the brand.

Furniture Fair, a multilocation furniture retailer, built a post-purchase recommendation flow with two layers. First, hand-picked pairings from its merchandising team (buy a sofa, get recommendations for end tables that go with it in the brand's showrooms). Then, pieces from the same design collection. One flow, $26,000 in additional monthly revenue.

Unidragon, a wooden puzzle brand, sends a three-email cross-sell sequence three weeks after delivery — timed for when the customer has likely finished their puzzle. Each email introduces a different puzzle category in order of popularity, automatically skipping any category they've already purchased. The idea is simple: help buyers discover product lines they wouldn't have found on their own. This single flow generates 7.4 percent of Unidragon's total revenue.

Post-purchase flows work best when they feel like a recommendation from someone who knows what you bought, not a generic upsell blast.

4. AI-Driven Win-Back That Finds the Right Moment to Re-Engage

Most win-back flows fire on a fixed timer: 30 days inactive, send a discount. Sixty days, send a bigger one. It has nothing to do with how the customer actually engaged with the brand.

JOLYN, a competitive swimwear brand, took a different approach. Its win-back flow uses AI to predict the right moment for re-engagement based on each customer's browsing patterns and engagement history, not a calendar trigger. The flow personalizes three things at once: timing, discount level (based on predicted conversion probability), and product recommendations (based on individual browsing, not generic best-sellers). A/B tested against a standard win-back, it delivered 9x conversion growth and 15 percent higher average order value.

A calendar-based win-back treats every lapsed customer the same. A behavior-based one doesn't and the gap is enormous.

Why Most Brands Don't Do This

If advanced flows are this effective, why don't more brands run them?

Three reasons. First, they require clean, unified customer data, including browsing history, purchase data, and engagement signals all feeding into one profile. Most brands have this data scattered across platforms that don't talk to each other. Second, most email platforms weren't built for this. They handle campaigns well but make it difficult to set up flexible segmentation, multi-step branching, or conditional logic without workarounds. Third, it takes people who know how to design these flows and the bandwidth to build and maintain them. Most marketing teams are stretched thin running campaigns and don't have a dedicated CRM or lifecycle person to own flow strategy.

Ultimately, most teams default to what's easy: more campaigns, more blasts, more subject line testing while leaving flow revenue on the table.

Where to Start

The brands earning the most from email didn't get there by sending more. They got there by building flows that react to what customers actually do. The examples are here. The data backs them up. What's left is execution. Clean up your data, pick the right tool, and give someone ownership. Start with one flow, build it, and let the numbers make the case for the next one.

Maryna Hradovich is the co-founder and COO of Maestra, an all-in-one marketing platform that helps scaling DTC brands personalize beyond email and SMS.