Attributed revenue from one send
Chains percentage stages the way lifecycle teams model campaigns—one formula stack with a secondary KPI (RPM). Extend with holdouts or repeat purchases in Calclet.
Example scenario
A CRM manager sizes a spring clearance blast with fifty-two thousand delivered messages after suppressions, recording a thirty-eight percent unique open rate and a fourteen percent click-to-open rate on Apple Mail–adjusted opens from the ESP. Four percent of those clicked sessions convert to purchase within the seven-day attribution window and finance tags one hundred forty-two dollars blended AOV on flow-attributed receipts. The stacked funnel implies roughly nineteen thousand seven hundred sixty opens, about two thousand seven hundred sixty-six clicks, nearly one hundred eleven orders, approximately fifteen thousand seven hundred thirteen dollars in modeled attributed revenue, and near three hundred two dollars revenue per one thousand emails delivered—RPM scales straight-line when list size changes holding rates constant.
Attributed revenue from one send
Classic opens × clicks × purchases × AOV
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How to estimate attributed revenue from one email send
- Input emails delivered exactly as your ESP bills net of hard bounces so RPM denominators align with invoiceable sends.
- Slide open rate (%) using unique opens divided by delivered sends—note Apple Mail Privacy Protection inflates machine opens; some teams substitute clicks-per-delivered for Apple-heavy cohorts when modeling purchases.
- Set click rate as percent of opens (CTOR). If your dashboard reports click-through rate on delivers instead, convert mathematically or swap definitions—never mix CTOR with CTR without adjusting inputs.
- Slide purchase rate as percent of clicks from your storefront connector for the same attribution window you report to finance, then input average order value from attributed orders; compare headline attributed revenue and revenue per one thousand emails against prior sends with identical definitions.
Email funnel benchmarks for broad retail/house lists
- Unique open rate (promotional sends, healthy permissioned lists)
- Often mid-teens to high-thirties depending on subject-line fatigue, MPP inflation, and vertical; triggered mail often outperforms batch
- Click-to-open rate (CTOR) on engaged segments
- Commonly high single digits to mid-teens for retail; flash-sale creative can spike short-lived CTOR
- Purchase conversion from clicked sessions (attributed window)
- Typically low single digits for cold promos; VIP or replenishment flows skew higher when clicks are high-intent
Best use cases
- Forecasting and scenario planning
- Client education and pre-qualification
- Budget and performance decision support
Frequently asked questions
Why chain open → click → purchase instead of deliver → click → purchase?
This calculator follows ESP conventions where click rate is measured against opens (CTOR). If your ops standard uses unique clicks divided by delivered sends, replace the open stage by setting open rate to one hundred percent and reinterpret click rate as CTR-on-delivers—or rebuild the math so each multiplier references the same parent population.
MPP makes thirty-eight percent opens look fake—should I still trust open rate?
Use opens only if your segmentation already dampens phantom opens or you benchmark against historical baselines on the same ESP. For forecasting revenue, many teams anchor click and purchase stages on click-based cohorts or held-out tests rather than inflated open numerators.
Does revenue per one thousand emails change when I double list size but keep rates?
RPM stays flat because it divides revenue by sends; attributed revenue scales linearly with delivered volume. RPM shifts when engagement or AOV changes—fatigued larger lists usually degrade rates, so stress-test falling open or conversion instead of assuming constant RPM at scale.
Should AOV include discount codes applied inside the email?
Yes when finance recognizes net merchandise value on attributed orders. If your average mixes full-price and deep markdown cohorts, split sends by promo depth or use blended trailing AOV from the campaign’s attributed receipts so modeled revenue matches Shopify net sales reporting.
Glossary
Scenario modeling
Testing multiple assumptions to estimate possible outcomes before execution.
Commercial intent
User behavior indicating readiness to buy, subscribe, or request a quote.
Related calculators
Category: Email marketing & attribution modelingTopics: Attributed campaign revenue, Funnel conversion stack, Email RPM
Last reviewed: 2026-05-07
Reviewed by: Calclet Growth Team