Increasing Email Revenue by Removing Excessive Flow Exclusions

Summary

If you're a CRM or lifecycle marketing leader seeing low email volume from your automated flows and/ or low revenue compared to industry benchmarks, overly strict suppression logic is often the hidden culprit.

As part of a broader lifecycle and behavioral trigger audit, I identified that The Vitamin Shoppe’s automated flows were significantly constrained by overly aggressive suppression rules. Customers who demonstrated high intent (browsing, adding to cart, waiting for back-in-stock items, etc.) were often excluded from receiving key triggered email flows due to multiple overlapping suppression criteria such as “received any other abandon email” or “purchased in the last X days”.

This finding aligned with the core recommendations in my overall automated email audit, which called out suppression cleanup as one of the top levers for immediate revenue impact: removing volume caps, opening the top of the funnel, and allowing customers to receive the most relevant and time dependent touch points amid inbox saturation.

Over a two-week period, I redesigned suppression logic across key flows (Cart Abandon, Browse Abandon, Back in Stock, Price Drop, Low Inventory) and closely monitored performance. The result was a substantial increase in reach and revenue across every program.

The Challenge

Trigger programs were under-delivering volume and revenue because:

• Suppression logic was based on opinion and not data

• High-intent users were excluded by simply qualifying for more than 1 automated flow

• Frequency caps were set too conservatively

• Some flows even suppressed some qualified customers due to a lack of personalized data (like item browsed product information, for example)

In short: customers weren’t receiving the right messages at the right time—because they weren’t receiving the messages at all.

My Approach

1. Audit suppressions flow-by-flow, and step-by-step
   I mapped every existing suppression, frequency cap, and inclusion/exclusion rule to identify unnecessary blockers.
   (Ex: Cart Abandon excluded customers who received any abandon, Back in Stock, Price Drop or Low Inventory sequence in the last 7–30 days – dramatically reducing eligible volume.)

2. Redefine suppression logic

   • Retained only essential rules (suppress recent purchasers, for example)

   • Prioritized each flow by conversion rate & reach to ensure the most impactful flows are delivered.

3. Reduced overly conservative frequency caps

   I reduced frequency caps on major flows to ensure customers are receiving these key emails after site behavior like cart abandon & browse abandon flows. Some of these flows has frequency caps of 30 days, significantly reducing volume of relevent and high converting messages.

Analysis & Insights

1. Significant increase in eligible audience

The largest gains came from programs previously bottlenecked by heavy suppression:

• Low Inventory volume surged +676%

• Price Drop volume grew +92%

• Cart Abandon delivered volume increased +48%

These flows target high-intent audiences, so increasing delivered volume directly improved revenue.

2. Revenue growth across almost every program

• Price Drop revenue more than doubled (+111%)

• Low Inventory revenue more than tripled (+219%)

• Cart Abandon revenue lifted +16%

3. Improved customer coverage = more chances to convert

These results validated the original audit hypothesis:

“Removing suppression barriers increases volume and enables multiple touch points amid inbox saturation.”

High-intent shoppers often qualify for multiple flows simultaneously (ex: product back in stock and price drops). Previously, they received only one email. After updating logic, they received the right message for each behavioral moment.

What this demonstrates in my consulting work

1. I build efficient, revenue-maximizing lifecycle systems

   • This work shows how operational decisions—like exclusions and frequency caps—can dramatically influence revenue performance.

2. I translate data into meaningful lifecycle improvements

   • I don’t optimize flows in isolation. I evaluate how all lifecycle programs interact and ensure they work together rather than siloed or against each other.

3. I treat suppression logic as a strategic lever

   • Many brands over-suppress because they underestimate customer tolerance or fear over-messaging. My work balances deliverability, customer experience, and revenue opportunity.

4. I validate through data, not assumptions

   • Each change was monitored weekly and benchmarked against pre-change performance to ensure improvements were real and sustained.

Conclusion

By removing outdated and overly restrictive suppression rules, I was able to meaningfully increase triggered email volume and revenue across multiple high-intent behavioral email programs. This initiative created a stronger foundation for future optimization across design, messaging, personalization, and timing—and allowed the brand to fully capitalize on the behavioral signals customers were already providing.

If you want a CRM or lifecycle audit for your brand, drop me a message and let’s start the conversation.