Forecast the email revenue you're not capturing yet.
A good forecast turns "we should email more" into a dollar target you can plan against. Here is a credible way to do it: establish a baseline, size the levers that move email revenue, project the months forward, and model the incremental lift rather than the revenue your platform simply attributes to email. That last part is the one most forecasts get wrong.
A forecast turns intent into a number you can plan against
Most email plans stall on a vague "we could be doing more." A forecast replaces that with a figure: if you close the flow gaps and tighten cadence, here is the revenue email adds over the next two quarters, and here is what it costs to get there. It also sets a target you can hold the program to. The catch is that a forecast is only as honest as its inputs, and the most common mistake is forecasting from attributed revenue instead of incremental lift. We will come back to that, because it is the difference between a plan and a wish.
Baseline, levers, projection
Five steps take you from what email drives today to a credible forward number. None of it needs a data-science team; it needs a clean baseline and honest inputs.
Establish the baseline
Pick a clean, recent window with no unusual promotions, and record what email drove in it and what the store did overall. This is the number every projection builds from, so keep the source consistent. A shaky baseline makes every forecast that follows wrong.
List the levers
Name what will actually change: list growth, send cadence, flow coverage (the automated flows you are missing or under-running, like a welcome series, abandoned cart, or win-back), revenue per recipient, and seasonality. Most of the movement in an email forecast comes from a small number of these, usually flow gaps first.
Size each lever honestly
Attach a realistic lift to each lever, not a best case. A missing flow adds the revenue it would earn at a modest per-recipient rate across the audience it reaches; more cadence adds sends but with diminishing return and a deliverability ceiling. Sizing is the hard part, and it is exactly what a forecast built from your own data does precisely. Conservative inputs make a forecast you can stand behind.
Project the months forward
Roll the sized levers forward month by month, phasing them in as they would actually ship, and layering seasonality on top. The output is a curve, not a single number: what email drives if you do nothing, versus what it drives as each lever lands.
Track incremental against the baseline
Once changes are live, measure the lift as performance minus the pre-change baseline, not as the total your platform attributes to email. That keeps the forecast honest and tells you which levers actually paid, so the next forecast gets sharper.
How the numbers come together
The figures below are illustrative round numbers, not benchmarks, just to show the shape of the math. Say a store does $200,000 a month and email drives 18 percent of that today, mostly from campaigns because two core flows are missing. That 18 percent is the baseline; each row adds one lever.
| Step | Lever added | Email share of store | Email revenue / mo | Added / mo |
|---|---|---|---|---|
| Baseline | Campaigns only, two core flows missing | 18% | $36,000 | n/a |
| Quarter 1 | Add welcome and abandoned-cart flows | 22% | $44,000 | +$8,000 |
| Quarter 2 | Tighten cadence and segmentation | 25% | $50,000 | +$6,000 |
| Projection | Both phases, over two quarters | 25% | $50,000 | +$14,000 |
The forecast isn't "email doubles." It's a believable climb from 18 percent toward the healthy range, with a dollar figure on each lever. Every input is one you can defend, and the total is the sum of specific, conservative moves rather than a hopeful multiplier.
Forecast incremental lift, not attributed revenue
This is the single thing that separates a forecast you can stand behind from one that quietly overstates. Attributed revenue is what your email platform credits to email within its attribution window; it overlaps with other channels and with sales you would have made anyway. Incremental revenue is what a change actually adds, measured as performance after the change minus the pre-change baseline. Forecast the incremental number. Two habits keep it clean: measure the lift as the dollars it adds over the real pre-change baseline, not as a percentage of some smaller number picked to make it look bigger, and never sum overlapping attributed sources, because the same order gets counted twice. It is the same discipline behind reading your attributed versus incremental revenue in the first place, applied forward instead of backward.
Know the ceiling you're forecasting toward
A forecast should land somewhere believable. A useful reference: across the direct-to-consumer brands we audit, email drives a median of about 25 percent of store revenue, in line with Klaviyo's published average near 27 percent (both are email-attributed figures, and it is a small, directional sample). Practitioner guidance puts a healthy mature program roughly in the 25 to 40 percent range (the email revenue benchmark has the full bands), so treat the top of that range as a soft ceiling. If your forecast has email vaulting well past it in a couple of quarters, an input is probably too generous; if it barely moves off a low base despite real flow gaps, an input is probably too timid. The email revenue benchmark and the campaign versus flow split are the two reference points worth checking a forecast against.
The only forecast that matters is yours
A method gets you a defensible number; it cannot tell you which specific flow is missing on your store or what it is worth. That is where the value is. A free Klaviyo audit reads your baseline and your gaps and forecasts the revenue a more complete program would add, month by month, ranked by the highest-value emails you are not sending yet, each with a dollar figure and a time estimate. So instead of a spreadsheet of guesses, you get the forward number and the ordered list of moves that gets you there.
Is it safe to connect Klaviyo?
- Read-only. It can read your campaign and flow performance. It cannot send, edit, or delete anything in your account.
- No customer data stored. It works from your metrics, not your subscriber list. Names, emails, and phone numbers are never stored.
- Nothing ships without you. Built emails land as drafts for your review; nothing is pushed to Klaviyo on its own.
- Built by an operator. David Refaeli-Berman ran enterprise email at Chewy, Amazon, Overstock, and Bed Bath & Beyond.
Questions
How do you forecast email revenue?
Start from a clean baseline of what email drives today, identify the levers that will change it (list growth, send cadence, flow coverage, revenue per recipient, and seasonality), size a realistic lift for each, and project the months forward. The discipline that makes a forecast credible is modeling incremental lift, the revenue a change adds on top of the baseline, rather than the total your platform attributes to email.
What is a realistic email revenue growth target?
It depends on how much headroom you have, not on a universal number. A useful ceiling to sanity-check against: across the direct-to-consumer brands we audit, email drives a median of about 25 percent of store revenue, in line with Klaviyo's published average near 27 percent. If email is well below that on your store, the gap up toward a healthy range is your realistic headroom; once you are well into that range, further growth comes slower and from efficiency rather than filling gaps.
What is the difference between attributed and incremental revenue in a forecast?
Attributed revenue is the orders an email tool credits to email within its attribution window; it overlaps with other channels and tends to run high. Incremental revenue is the sales a change actually adds, measured as performance after the change minus the pre-change baseline. Forecast the incremental number. A forecast built on attributed totals will overstate the lift, because it counts revenue you would have captured anyway.
Which levers move email revenue the most?
For most stores the biggest is flow coverage, closing the gaps where a core automated flow is missing or half-built, because those reach people at peak intent. After that: list growth (more qualified subscribers), send cadence and segmentation (sending the right thing often enough), and revenue per recipient (better offers, timing, and relevance). Seasonality shapes the timing but not the underlying trend.
Can you forecast email revenue in Klaviyo?
Klaviyo reports your history and current performance, which is the raw material for a forecast, but projecting the forward number and attaching a dollar value to each lever is a modeling step on top of that data. A free audit does exactly that: it reads your baseline and gaps and forecasts the revenue a more complete program would add, ranked by the highest-value emails you are not sending yet.
Find out what email could really drive on your store.
A free audit forecasts the revenue you're not capturing yet, month by month, and ranks the highest-value emails to send first.
Forecast my email revenue free