Email Frequency Optimization

How to Use Email Frequency Optimization Effectively?

1. Set solid baselines

Use the last 4–8 weeks for open/read, CTOR and CVR. Remove spikes from flash sales or outages. Keep AOV, CPM and creative costs in the same currency you selected.

• Open/Read rate = % of delivered emails that are opened/read.
• CTOR = clicks ÷ opens; stabilizes subject-line noise.
• CVR = orders ÷ sessions from email clicks.

2. Choose your audience sensitivity

Select how fast engagement decays when you send more. Gentle peaks around 8/wk, Normal near 6/wk, and Steep around 4–5/wk.

3. Review the recommendation

Headline cadence maximizes profit/subscriber after ESP & creative costs and applies a soft guardrail beyond 5/wk (Standard mode).

• Use the curve to see trade‑offs at nearby frequencies.
• Read the chips: Reads/sub, Profit/sub, and Unsubs/1k.

4. Test safely in production

Adopt the A/B plan: split your list, ramp one step at a time, and hold changes for multiple sends.

• Primary KPI: profit per 1,000 subs; watch Unsubs/1k and complaints.
• Pause increases if placement drops or complaints rise.

5. Improve inputs; not just volume

• Lift opens with better subjects/preview text (see Subject Line Tester).
• Upgrade segmentation and dynamic content to raise CTOR.
• Clarify on‑site offers and checkout to raise CVR.

6.) Re-run periodically

Re-optimize after seasonality shifts, major promotions, list hygiene changes, or platform migrations.

How Email Frequency Optimization Calculator is different from Email Campaign Frequency Fatigue Checker?

These two calculators solve complementary, but fundamentally different, problems.

Email Frequency Optimization calculator is a growth tool: it models the relationship between send frequency and response rate (reads/clicks/revenue) to find the cadence that delivers the most total outcomes per week, i.e., “sweet spot.” It leans on historic data or split tests to fit a curve where total outcome = frequency × per-send rate, then recommends the peak (for some apparel data this was ~6.21/wk).

By contrast, Email Campaign Frequency Fatigue Checker is a safety tool: it evaluates short-term fatigue risk and list health using signals like unsubscribe %, complaints, opens, targeting level, and content mix, compares your planned cadence to a tolerance threshold, and returns a Green/Yellow/Red risk score with a safe frequency cap for next 30 days.

In practice, teams use Fatigue Checker first to establish guardrails; if risk is low, they then use Optimization calculator to push for maximum results without crossing into burnout.

Key differences at a glance:

• Primary question: Optimization asks “What cadence maximizes total clicks/revenue?”; Fatigue asks “Are we burning out our audience right now?”
• Objective function: Optimization maximizes outcomes (peak of frequency × rate); Fatigue minimizes risk (unsubs, complaints, engagement decay).
• Inputs:
  • Optimization: requires response-vs-frequency data (historical or A/B splits), optionally revenue per send.
  • Fatigue: planned emails/week, avg unsubscribe %, avg open %, segmentation level, content mix; advanced: complaint %, bounce %, recent change, new-subscriber share, open-trend; optional list size.
• Math/logic:
  • Optimization: curve fitting or incremental testing to locate the peak; outputs a best-frequency estimate (e.g., ~6.21/wk in one vertical).
  • Fatigue: weighted risk scoring + hard rules; compares monthly frequency to a tolerance T derived from targeting & content; outputs risk band and safe cap.
• Time horizon: Optimization = medium-term growth (8–12 weeks of testing typical); Fatigue = near-term safety (next 30 days).
• Outputs:
  • Optimization: recommended “sweet spot,” likely impact, and a plan to move toward it.
  • Fatigue: Green/Yellow/Red badge, risk score, safe cap (week & month), drivers, formulas, and watchouts.
• Risk posture: Optimization is more aggressive (pursues the peak); Fatigue is conservative (protects deliverability & retention).
• How to use together: Run Fatigue first to set guardrails; if Green/low Yellow, use Optimization to climb toward the peak without exceeding the safe cap.

Credits and notes: This Email Frequency Optimization Calculator is based on test run by Tim Watson at Zettasphere.