Overview
Most email marketers have limited visibility into what happens after shoppers click through an email and land on the online store. Metrics such as opens, clicks, and click-through rates are easy to track, but they only measure engagement before the purchase journey begins. What happens next — how shoppers interact with the products you feature — is where real monetization occurs.
The Visibility Gap
A common assumption is that promoting best-selling products automatically leads to the best results. But this is often a misconception.
When a product gets more exposure, it naturally sells more, creating a self-fulfilling prophecy that reinforces its “best seller” label. Over time, brands end up promoting the same set of products again and again — not because data proves they are the most profitable, but because they’ve historically sold the most.
This cycle hides a critical truth: best sellers aren’t always the most effective revenue drivers for email marketing. Some of the highest-performing products may never reach enough shoppers to demonstrate their potential because they haven’t been featured in campaigns.
Why Product Performance Matters
To make smarter decisions about what to promote, marketers need to understand how products actually perform when viewed by shoppers coming from email. Uplift modeling provides this visibility by comparing how the same products perform with email-driven traffic versus organic visitors who were not influenced by a campaign.
Key metrics to track include:
Item Conversion Rate (ICR): Measures how often a product view results in a purchase.
Average Order Value (AOV): Indicates whether a product lifts or lowers the total cart value when purchased.
Revenue Gain / Lift: Quantifies the incremental revenue impact of featuring a product in email compared to its organic performance.
These metrics reveal which products are driving incremental value — not just sales volume. A product with strong conversion and AOV lift can be a better revenue contributor than a popular item with flat performance when featured in emails.
Breaking the “Best Seller Bias”
Promoting best-selling products feels safe, but it can trap marketers in a loop where exposure dictates perceived demand. This Best Seller Bias limits discovery and hides opportunities for higher profitability.
The goal is to identify products that:
Convert efficiently when shown to email shoppers.
Increase average order value by encouraging larger purchases.
Show uplift in performance metrics relative to organic traffic.
By identifying and promoting these products — even if they aren’t top sellers yet — marketers can unlock underutilized revenue potential and reduce wasted sends on low-impact items.
Creating the Optimization Feedback Loop
Using insights from uplift modeling, you can establish a continuous improvement cycle for product selection in campaigns:
Discover: Identify products with strong ICR and AOV lift based on uplift modeling analysis.
Feature: Include these products in upcoming campaigns and automated flows to expand their reach.
Measure: Monitor how these products perform for email traffic versus organic visitors.
Refine: Adjust product selection based on measured uplift to maximize incremental revenue.
This loop transforms product selection from a guessing game into a data-driven optimization process that improves every send, campaign, and lifecycle flow over time.
Additional Angles to Consider
Lifecycle Context
Product performance varies by lifecycle stage.
Acquisition campaigns should highlight products that convert easily and appeal to new shoppers.
Retention campaigns should promote products that lift order value and reinforce brand affinity.
By mapping product selection to lifecycle intent, you maximize the relevance and profitability of each email.
Personalization Synergy
Combining uplift insights with personalized recommendations amplifies results.
Once you know which products perform best, Email Pulse can stream personalized versions of them directly into emails through the InMail Shop block — ensuring each recipient sees the most relevant high-performing items based on their behavior and buying signals.
Seasonality and Timing
Top-performing products change throughout the year.
Use uplift analysis before peak periods like BFCM to identify which products historically deliver strong conversion and order value lift during high-traffic windows. Re-evaluate after each season to capture evolving shopper preferences.
Automated Flow Optimization
High-performing products shouldn’t be limited to campaigns.
Integrate them into automated flows — such as browse abandonment, post-purchase upsell, and win-back sequences — where they can continue to drive incremental revenue passively.
Attribution Clarity
Uplift modeling removes the ambiguity of attribution.
Instead of relying on best-seller lists or platform-reported conversions, you’ll see which products are actually lifted by email exposure. This gives you confidence that your monetization gains are real and repeatable.
Key Takeaway
Best-selling products tell you what has sold.
Top-performing products, revealed through uplift modeling, tell you what should be promoted next.
By featuring these data-proven products in your email campaigns and flows, you create a continuous feedback loop that increases engagement, raises average order value, and compounds revenue growth over time. This is how data-driven product selection becomes one of the most effective ways to monetize your email channel.