Forecast the Trade-off: Zomato's SMS Frequency Cap vs Revenue
Objective: Given a table of messages-per-month, revenue-per-message, and cumulative opt-out rate, forecast the send frequency that maximizes net revenue without breaching the lesson's 3.5% industry-average opt-out benchmark.
You're the CRM lead at Zomato modeling how many SMS sends per month the loyalty segment can absorb before opt-outs erode the list faster than incremental sends generate revenue.
Given send-frequency test data for 2, 4, 6, and 8 messages/month, calculate net revenue at each level (gross revenue minus projected list-value lost to opt-outs) and recommend a cap with the automated-flow-first reasoning the lesson argues for.
Before you start
What you'll need
Free path (everything below is enough to finish)
Free, chart-building and formula-driven scenario comparison need nothing more
Paid upgrades (optional, faster/deeper)
Automated triggers, the highest-revenue-per-recipient sends in this forecast, require flow automation to run reliably
No access? Send automated triggers manually to small test segments and log results in Sheets
The process
2 steps
Step 01 of 02
The lesson's Step 3 caps most ecommerce SMS programs at 4-6 messages/month, warning that beyond that ceiling opt-outs spike and reach degrades, citing a 3.5% industry-average opt-out benchmark from the lesson's Bushbalm example.
The test data shows opt-out rate holds near 1.2% through 4 sends/month, then jumps to 4.8% at 8 sends/month. Where does the curve break?
Procedure
- Import frequency-test.csv with columns: sends/month, opt-out rate, revenue/message
- Plot opt-out rate against sends/month and locate where the curve bends upward sharply
- Mark any frequency level above the 3.5% opt-out benchmark as over the safe cap
2 sends/mo: 0.6% opt-out 4 sends/mo: 1.2% opt-out 6 sends/mo: 2.9% opt-out 8 sends/mo: 4.8% opt-out <- exceeds 3.5% benchmark
Healthy
The recommended frequency sits at or below the point where opt-out rate crosses the 3.5% benchmark.
Unhealthy
Recommending 8 sends/month because gross revenue is highest there, ignoring that opt-out rate has already broken the safe threshold.
What this means
Gross revenue per send is the wrong optimization target once opt-out rate compounds against future list value.
So what do I do about it?
| Symptom | Action | Effort |
|---|---|---|
| The frequency recommendation is based on gross revenue alone | Cross-check the recommended frequency against the 3.5% opt-out benchmark before finalizing | 30 min |
Step 02 of 02
The lesson states automated flows (cart, browse, post-purchase) beat broadcast sends by 3 to 10x on revenue per recipient, so a frequency cap should be spent on automation first, broadcasts second.
Of your 4 allowed monthly sends, the current plan is 4 broadcasts and 0 automated flows. Does that match where the revenue actually comes from?
Procedure
- Tag each historical send as 'broadcast' or 'automated flow'
- Compare average revenue/recipient for each tag
- Reallocate the monthly send budget to prioritize automated triggers before adding broadcast sends
Broadcast avg: ₹8/recipient Automated flow avg (cart/browse/post-purchase): ₹41/recipient (5.1x higher) Recommendation: keep 2-3 automated triggers always-on, cap broadcasts at 1-2/month
Healthy
The monthly send budget is weighted toward automated triggers, with broadcasts filling the remaining cap.
Unhealthy
Spending the full frequency cap on broadcasts and treating automated flows as optional extras.
What this means
The cap isn't a budget to fill with broadcasts, it's a ceiling that automation should claim first.
So what do I do about it?
| Symptom | Action | Effort |
|---|---|---|
| The send plan is 100% broadcast with no automated triggers | Move cart, browse, and post-purchase triggers into the plan before adding any broadcast | 30 min |
Final deliverable
A frequency-vs-revenue model recommending a monthly send cap, with the send budget split between automated triggers and broadcasts, and a written justification citing the opt-out benchmark.
See a reference example
Instacart, SMS frequency model (excerpt) Recommended cap: 4 sends/month (1.2% opt-out, under the 3.5% benchmark) Budget split: 3 automated triggers (cart, browse, post-purchase) + 1 broadcast/month Projected net revenue: ₹1.94/recipient higher than the current 6-broadcast plan after accounting for opt-out list erosion
Success criteria
You're done when you can:
- Frequency recommendation stays at or under the 3.5% opt-out benchmark
- Model compares net revenue, not just gross revenue, across frequency levels
- Send budget prioritizes automated triggers over broadcasts