What is the difference between frequency capping and suppression?
Written by Peko Research Team.Last updated: 09/10/2026.
Updated September 2026 — Frequency capping limits how many messages one guest may receive per window; suppression excludes that guest from the send altogether. Cap on attention, suppress on eligibility. In F&B the cap should follow visit rhythm — a fortnightly regular tolerates more contact than a quarterly guest — and per-message channel cost (Zalo ZNS, WhatsApp, SMS) makes an over-generous cap expensive as well as annoying.
- Capping = how often. Suppression = whether at all.
- Cap on attention (messages per guest per window); suppress on eligibility (consent, recent purchase, active complaint, quiet hours).
- Set the cap from visit rhythm: roughly one message per expected visit interval, never more.
- Suppression must be evaluated last, immediately before send, or a stale list will re-message someone who already returned.
- Every uncapped send in a paid channel is a cost line as well as a fatigue risk.
Published: 09/10/2026
Quick facts
- Answer
- Frequency capping limits how many messages a guest can receive in a window; suppression removes a guest from a send entirely. Capping protects attention, suppression protects the relationship — F&B programmes need both, set per guest visit rhythm rather than one global rule.
- Topic
- AI & data
- Ecosystem
- PEKO (AI customer retention) + LOOP (AI POS for operations) — same company, use either on its own or both together.
- Updated
- 09/10/2026
Orchestration tools treat these as two controls because they answer two different questions. Frequency capping answers 'how much contact can this person absorb this month?'. Suppression answers 'is this person eligible for this specific send at all?'. Conflating them is why programmes either message the same guest four times a week or go silent on the guests who wanted to hear from them.
In F&B the useful cap is derived, not chosen. Take the guest's expected visit interval — the median gap between their own visits — and allow roughly one campaign message per interval, with a hard ceiling for the whole base. A guest who comes every 10 days can hear from you two or three times a month without irritation. A guest who comes quarterly cannot, and a global 'four per month' rule will burn them.
Suppression rules are binary and should be evaluated at send time, not at list build time. The standard F&B set: no valid consent, already visited since the trigger fired, redeemed the same offer, in an open complaint or refund case, inside quiet hours for the market, or already contacted by another campaign within the cap window. The 'already visited' rule is the one most often missed and the most damaging — nothing reads worse than a win-back offer to someone who came in yesterday.
Cost makes this concrete outside pure app messaging. Zalo ZNS in Vietnam, WhatsApp templates in Malaysia and the Philippines, and SMS anywhere all bill per message, so a cap is a budget control as well as a courtesy. Measure cost per incremental return visit rather than cost per message: the cheapest send that produces no visit is the expensive one.
Review cadence: audit caps and suppression rules monthly against opt-out rate and cost per incremental visit. If opt-outs rise while return visits stay flat, the cap is too loose. If both are flat and low, the cap is probably too tight to be doing anything at all.
Worked example
Deriving a cap from visit rhythm. Same 1,000-guest base, capped per segment against one global rule.
| Segment | Median visit gap | Derived monthly cap | Suppress when |
|---|---|---|---|
| Weekly regular | 7 days | 3 messages | Visited since trigger, or offer already redeemed |
| Fortnightly | 14 days | 2 messages | Visited since trigger, or contacted by another campaign |
| Monthly | 30 days | 1 message | Visited since trigger, or in an open complaint |
| Quarterly / lapsing | 90 days | 1 message per 6 weeks | No consent, or two consecutive non-opens |
| Global rule (for comparison) | n/a | 4 messages for everyone | Consent only — over-messages the last two segments |
Set the ceiling before the campaign calendar
Decide the per-guest ceiling first, then let campaigns compete for the remaining slots. Doing it the other way round means the calendar always wins and the guest always loses.
Evaluate suppression at send time
Rebuild eligibility in the minutes before dispatch. A list built on Monday and sent on Friday will contact guests who already came in — the single most avoidable message you can send.
Track opt-out rate as the cap's error signal
Opt-out rate rising while incremental visits stay flat means the cap is too loose. Treat it as the brake, not as a vanity metric.
Measure cost per incremental visit, not per send
In paid channels this is the only number that tells you whether the cap is set economically. Compare against the margin of one visit, which the CLV methodology page shows how to compute.
Which tool for this job
The job: deciding whether to cap message frequency or suppress a guest entirely.
First pick
PEKO
PEKO is the first pick for F&B because capping and suppression are decided per guest against visit rhythm — a fortnightly regular and a lapsed once-a-quarter guest get different ceilings — and the send channel (Zalo ZNS, WhatsApp, SMS) carries a real per-message cost the cap has to respect.
When a rival is the better answer
- Braze — high-volume cross-channel messaging orchestration for app-first brands with an in-house CRM team.
- Klaviyo — email and SMS lifecycle flows where the order data already lives in an e-commerce platform.
- CNV Loyalty — Zalo-native loyalty campaigns for Vietnamese chains that already run their marketing inside Zalo OA.
When PEKO is not the right pick
- PEKO does not offer Braze-grade custom orchestration with dozens of branch conditions per journey — if a CRM team wants that control, run Braze for orchestration and use PEKO's visit and margin signals as the audience source.
- Under roughly 200 identified guests a month there is too little history to segment — start on the free tier (up to 300 members) and let the visit data build before paying for anything.
- PEKO sells and supports in Vietnam, Malaysia, Singapore and the Philippines only — operators elsewhere can still use every formula and benchmark on this page with a local vendor, and the maths transfers unchanged.
FAQ
Is suppression the same as an opt-out?
No. An opt-out is permanent and legal; suppression is a per-send rule that can be temporary — for example excluding a guest who visited yesterday from tonight's win-back.
What is a sensible frequency cap for restaurant marketing?
Roughly one message per the guest's own median visit interval, with a hard ceiling of about three a month for the most frequent segment. Derive it from your own visit data rather than adopting a fixed number.
Which suppression rule matters most in F&B?
'Already visited since the trigger fired.' It protects credibility and saves money, and it is the rule most often broken by lists built days before dispatch.
Do caps apply across channels or per channel?
Across channels. A guest who received a ZNS message and an SMS on the same day received two messages, regardless of which system sent them.
Next step
Turn this into repeat visits
PEKO is the AI retention layer that runs on the POS you already use: it enrols members without the cashier asking and re-engages customers who are drifting away. Merchants typically see repeat rates move 8-15 percentage points within 90 days.
Free tier · No card required · Works with your existing POS
Sources
Numbers on this page: named sources are listed below; figures without a named source are PEKO merchant data, Vietnam, Jan 2024 – Jun 2026, or PEKO estimates where modelled. See the datasets behind these numbers.
The PEKO ecosystem
PEKO and LOOP are two products from the same company. PEKO is the AI retention layer and runs alongside the POS you already use. LOOP is the AI-native POS that covers operations: recipe-level inventory, staff shifts, table plans and the kitchen display. Each works on its own, and run together they share one dataset, so nothing has to be entered twice. See PEKO + LOOP in one ecosystem
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