· 9 min read
The cadence question: how often should you email?
The most common lifecycle question I've been asked across a decade of CRM work is 'how often should we email?'. It comes from a CEO who thinks the team emails too much. It comes from a growth lead who thinks the team emails too little. It comes from a customer-experience team who wants a blanket cap. The answer is never a single number, and most of the heat the question generates is a consequence of treating it like one.
Justin Williames
Founder, Orbit · 10+ years in lifecycle marketing
Why 'how often should we email' is the wrong question
The right cadence for user A is the wrong cadence for user B. Program-level cadence questions force an answer that's wrong for most of the audience.
The question assumes cadence is a single program-level setting — a dial you turn to find the right frequency for your list. It isn't. Cadence is an emergent property of five other decisions, each of which is a more productive conversation than the top-level one.
A user who just signed up and is in onboarding should get more mail than your average subscriber. A user who has been dormant for six months should get less. A user who's made a purchase this week has a different post-purchase sequence than a user who's never converted. The person who opens every email and clicks three a week can receive what a cold-list recipient cannot. The right cadence for user A is the wrong cadence for user B, and program-level cadence questions force an answer that's wrong for most of the audience.
The more productive version of the question: what are the inputs that determine the right cadence per cohort? Answer those, and the program-level frequency falls out as a consequence, not as an argument.
The five inputs that settle cadence
1. Lifecycle stage. Different stages tolerate different frequencies. Onboarding is intense by design — more email in the first week than in any other. Engaged users tolerate regular cadence because they're finding value. At-risk users tolerate some cadence but need higher-signal messages, not more of them. Lapsed users need specific low-density sequences, not the standard program. The Lifecycle Program Design skill covers stage-specific cadence for each canonical stage.
2. Engagement tier within a stage. Inside any stage, users vary in how much email they want. Users who open four of your last five emails can handle more than users who opened one. Tiering explicitly and shipping different cadences by tier is a far better practice than picking a single rate and applying it uniformly. Most programs that ship a single cadence either under-mail their engaged base or over-mail their light base.
3. Natural product cycle.A product that users engage with daily tolerates a different frequency than one users engage with monthly. The lifecycle program cadence should match or just slightly lead the product's usage rhythm — not impose a separate one that ignores when the user is ready for the product.
4. Deliverability headroom. If your sender reputation is strong and your list hygiene is clean, you have more room. If either is shaky, frequency compounds the problem. Most programs that "can't send more email" actually can — they just need to fix list hygiene first so the additional volume doesn't poison reputation. The deliverability guide covers the full connection between frequency and sender reputation.
5. Content inventory. You can only send as many messages as you have worth sending. Sending a second email in a week just because the schedule said so — when the content is thin — is worse than sending one good email. The cadence ceiling is set by the quality bar; the cadence floor is set by the cycle.
Frequency capping protects the base
3–5/wk
Common marketing message cap for B2C audiences.
1/day
Absolute ceiling including transactional messages.
0
Messages that cross the cap without explicit priority rules. Decide before you need to.
Even with well-designed per-cohort cadences, frequency capping at the user level is what prevents compound damage when multiple programs fire at the same user in the same window. Without a cap, a user can end up with an onboarding email, a lifecycle newsletter, a product-update broadcast, and an abandoned-cart push all in the same day — not because anyone designed it that way, but because four independent systems fired independently.
A practical cap: no more than N marketing messages per user per week, with transactional and critical-service messages exempt. N depends on your program, but three to five marketing messages per week is a common range that balances engagement and fatigue for most B2C audiences.
The harder question is priority when the cap would be exceeded. Which message gets cut when a user is about to cross the cap? The answer needs to be decided in advance and encoded in the system — onboarding beats newsletter, abandoned-cart beats promotional, transactional beats everything. Without explicit priority, the cap produces random cuts that make the program less coherent, not more.
Negative signals override all cadence rules
A user who hasn't opened any email in 30 days should receive dramatically less frequency than the cadence for their tier would normally call for — not because the cadence is wrong, but because the engagement signal is telling you the user is heading toward lapsed. Continuing to mail at the normal rate accelerates that journey.
A user who marked an email as spam, moved to junk, or hit the unsubscribe-but-didn't-complete flow is giving you an even stronger signal. These should be either suppressed outright or moved to a minimum-touch track immediately.
The principle: cadence rules define a ceiling, not a floor. The ceiling is the maximum you can mail without damage. The floor is whatever engagement signals say the user is willing to receive, and it can be much lower than the ceiling. A cadence system that ignores the floor will over-mail disengaging users and ship them straight to spam complaints.
When the question comes from the CEO
The lifecycle team rarely gets to answer cadence questions in isolation. A common pattern: a leadership stakeholder observes they're getting "too many emails from your own company" and asks the team to cut back. The ask is genuine, but it's a sample size of one. A cadence cut based on a single user's experience is usually wrong for the base.
The productive response isn't "actually our engagement rates are fine" — that reads as defensive. It's to surface the tiering: show which users are receiving how many messages, show the engagement-by-cadence data for each tier, and invite the stakeholder to look at whether their own cadence is actually aligned with their own engagement tier (usually: they opened two emails all year and are receiving three a week). The right answer is almost never "cut everyone's cadence". It's "this user's cadence doesn't match their engagement — fix the mismatch rather than the program".
Significance testing has a role here too — a cadence change deserves a proper test before being rolled out program-wide. A 20% cut that feels right but produces a 30% revenue drop is worse than the problem it was trying to fix.
Frequently asked questions
- How often should I email my marketing list?
- Cadence isn't a single program-level number — it's a per-cohort decision driven by lifecycle stage, engagement tier, product cycle, deliverability headroom, and content inventory. Picking one number to apply across the list usually under-mails engaged users and over-mails light users.
- What's a good weekly frequency cap?
- Three to five marketing messages per week is a common range for B2C audiences, with transactional and service messages exempt from the cap. The specific number depends on program design and engagement tier; the cap's main job is preventing compound damage from independent systems firing at the same user.
- How do I handle priority when messages would exceed the cap?
- Decide priority in advance and encode it in the system: transactional beats everything, abandoned-cart beats promotional, onboarding beats newsletter. Without explicit priority the cap produces random cuts and the program becomes less coherent rather than more.
- Should I email users who don't open my emails?
- Less, and declining over time. A user who hasn't opened in 30 days should be at a fraction of the normal cadence for their tier. By 90 days, they should be on minimum-touch or moving into re-engagement rather than the standard program.
- How should cadence vary by lifecycle stage?
- Onboarding is the most intense — more email in the first week than any other stage. Engaged users tolerate regular cadence. At-risk users need higher-signal messages, not more of them. Lapsed users should be on specific low-density re-engagement sequences, not the standard program.
- What's the risk of over-mailing?
- Higher complaint rates, higher unsubscribe rates, and sender reputation damage that compounds over months. The cost usually shows up 30–90 days after the frequency increase, which is why programs rarely link them. The signal to watch is complaint rate, not unsubscribe rate — complaints damage deliverability; unsubscribes don't.
- How do I respond when a CEO says 'we email too much'?
- Surface the tiering data. Show which users are receiving how many messages, show engagement by cadence tier, and usually reveal that the stakeholder's own cadence is misaligned with their engagement rather than the whole program being over-mailed. The right fix is usually better tiering, not a blanket cut.
This guide is backed by an Orbit skill
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