Why this analysis is needed
Email is one of the highest-ROI marketing channels. Yet, most email marketers manage performance using only email-level metrics like opens and clicks. This leaves them with very limited visibility into what happens once shoppers land on the online store - causing them to miss opportunities to maximize the incremental revenue impact of their email campaigns.
This analysis uses uplift modeling to compare email campaign performance in the online store against organic shoppers, who serve as the control group.
The logic behind use of uplift modeling to analyze campaign performance is very simple:
Unlike with the organic traffic where shoppers are anonymous, in email marketing the profile and prior behavior of shoppers is well known
This enables marketers to control of who to target, how to message, and what to offer
Therefore, online shoppers from email campaigns should overperform organic shoppers
The uplift modeling makes it possible to see:
Which campaigns resonate with your target audience and drive incremental revenue
Which campaigns have growth potential and which ones drag revenue down
Actionable insights you can apply in the next BFCM Week
How the analysis was performed
The following are building blocks of the analysis:
Input data is processed to calculate metrics below:
Revenue: Total revenue generated by the campaigns during the selected time interval
Revenue per Day: Average revenue per day by the campaigns during the selected time interval
RPV (Revenue per Visit): Average revenue generated per session from the campaigns
RPV Lift: Percentage difference between the campaign’s RPV and the site’s organic traffic RPV
ER (Engagement Rate): Percentage of all sessions that become engaged sessions
ER Lift: Percentage difference between the campaign’s Engagement Rate and the site’s organic traffic Engagement Rate
Revenue Gain: Incremental revenue attributed to campaigns, calculated from RPV Lift
Revenue per Day Gain: Average incremental revenue per day attributed to campaigns, calculated from RPV Lift
Time intervals:
Last 30 days — to show what is working right now, guiding next BFCM planning.
BFCM Week (Thanksgiving–Wednesday) — to see what worked in the prior season and whether those strategies are still relevant.
Campaign grouping based on uplift model:
Sure Things – engagement and revenue metrics above organic; clear winners.
Persuadable – revenue above organic but engagement below; profitable but need stronger engagement.
Sleeping Dogs – engagement above organic but revenue below; people pay attention but don’t buy.
Lost Causes – underperforming in both; wasted effort.
This structure ensures the analysis goes beyond vanity metrics and focuses on business outcomes.
What you can do with this data
Scale winners (Sure Things):
About: These campaigns generate incremental revenue above organic benchmarks.
Action: Use them as models for upcoming campaigns, especially during BFCM Week.Optimize profitable but weak (Persuadables):
About: These campaigns show solid revenue performance but lack engagement.
Action: improve email personalization and creative, supported by better online store personalization and buying experience.Rework high-attention but low-conversion (Sleeping Dogs):
About: These campaigns engage shoppers but fail to drive purchases, dragging down revenue growth.
Action: strengthen product recommendations, refine CTAs, and add urgency-driven offers.Cut or overhaul failures (Lost Causes):
About: These campaigns underperform in both engagement and revenue.
Action: pause them, rebuild with new offers or segmentation, or remove from rotation.
Final takeaway
This analysis equips you with a clear, actionable view of how email campaigns truly contribute to revenue in online store compared to organic shoppers. By focusing on uplift, you can:
Maximize profitable campaigns.
Redirect budget and effort away from weak performers.
Build BFCM strategies on proven winners.
The result: smarter email marketing, less wasted effort, and higher incremental revenue during your busiest season.