Email revenue per recipient

Email revenue per recipient is the average revenue a single email send earns, calculated by dividing the revenue attributed to a campaign by the number of recipients who received it. If a campaign earns 5,000 pounds and reached 50,000 inboxes, revenue per recipient is 10 pence. The figure puts every campaign on the same scale, so a small targeted send and a large broadcast can be judged side by side.

The metric matters because total revenue rewards big lists and hides efficiency. A campaign that earns more money simply because it went to more people is not necessarily a better campaign. Revenue per recipient strips list size out of the picture and asks a sharper question, which is how much value each contact you reach actually produces.

Take the revenue attributed to the campaign and divide it by the number of emails that were delivered. The two inputs must come from the same campaign and the same time window, or the ratio is meaningless. A campaign that earns 5,000 pounds from 50,000 delivered emails has a revenue per recipient of 10 pence.

The attributed revenue figure depends on your attribution model, so document which model you use and keep it consistent. Comparing a last touch campaign against a linear one distorts the ratio. Once the model is fixed, revenue per recipient becomes a clean way to rank campaigns and spot which audiences and offers carry their weight.

1. 1

   Pull attributed revenue

   Take the revenue credited to the campaign under your chosen attribution model and window.

2. 2

   Count delivered emails

   Use the number that reached an inbox, subtracting hard and soft bounces from the total sent.

3. 3

   Divide and express per email

   Divide revenue by delivered emails. The result is usually pence, so report it consistently across campaigns.

4. 4

   Hold the attribution model steady

   Compare like with like by keeping the same model and window across every campaign you benchmark.

Revenue per recipient is a ratio, so improving it means moving the parts beneath it. A metric tree breaks the number into the chain a recipient travels, from opening the email, to clicking, to buying, to how much they spend. When the ratio dips, the tree shows which step in that chain weakened rather than leaving you to guess.

KPI Tree models this chain and ties each step to the team that owns it. Decision Intelligence is the gap between a chart that says revenue per recipient fell and a team that knows the conversion rate dropped because the landing page changed. With RACI ownership on each node and a push to the accountable owner when the node moves, the conversion step has a named person who hears about the change in time to fix it.

Revenue per recipient depends on price point, purchase frequency and list quality, so the ranges below are a starting frame rather than a target. A high ticket retailer can earn pounds per email while a low price newsletter earns a few pence and still runs a healthy programme. The figures describe typical promotional sends under a last touch model.

Because the metric removes list size from the equation, you cannot improve it by sending to more people. You improve it by making each send more relevant, more likely to convert, and more valuable per order. The cards below target the steps in the chain that move the ratio.

1. 1

   Dividing by sends instead of deliveries

   Including bounced emails in the denominator understates the value of the contacts who actually received the message.

2. 2

   Chasing the ratio by shrinking the list

   Cutting your audience can lift revenue per recipient while reducing total revenue. Watch both numbers together.

3. 3

   Mixing attribution models

   Comparing a last touch campaign with a linear one distorts the ratio. Fix one model before benchmarking.

4. 4

   Reading a single campaign in isolation

   One send is noisy. Judge revenue per recipient across a run of campaigns to see a reliable trend.