How the Forecast is calculated.
Source-of-truth for every number that drives the Keaz Forecast. We deliberately err on the safe side — real Keaz programs typically outperform what you see here.
1 · Principles
The Forecast is built on five rules. They apply to every number on the page.
- Inputs come from the merchant. Constants come from us. What you type is your own data — defaults are illustrative.
- Defaults stay conservative. Where a number can be defended at "low" or "high," we pick low.
- The bottom number is a range, not a point. A range survives a reality check.
- Soft cap on uplift. No headline output exceeds 95% uplift, ever.
- Quarterly recalibration. Every constant is reviewed against real Keaz customer data, every quarter.
2 · Reachability — every number
The Reachability calculator answers: "How much of my audience is hiding behind WhatsApp, and what's it worth?"
2.1 · Inputs the merchant types in
Everything in this table is the merchant's own data. The calculator's job is to expose what these numbers mean together.
| Variable | Default | Where you find it |
|---|---|---|
| All customer contacts (T) | 12,000 | Shopify Admin → Customers |
| Vertical | Beauty | Your shop's category |
| Annual revenue | €500k–€2M | Shopify Admin → Reports → Sales |
| Phone at checkout | Optional | Shopify Admin → Settings → Checkout |
2.2 · Constants — and why we chose them
The four numbers below are not tunable in the public calculator. Each is set conservatively.
Conversion lift on customers reached by both email and WhatsApp, vs email alone. WhatsApp messages are delivered-to-read at 90%+ on the WhatsApp Business Platform — well above email's reported 30–40% open band. Published case studies routinely report 5–7× CVR uplift; we choose 1.6× at the lower bound of the revenue-per-recipient uplift range. It's defensible across verticals and leaves real Keaz programs room to outperform.
Share of phone-captured contacts that actively engage with WhatsApp marketing (opens + clicks). Aggregated benchmarks for unsegmented WhatsApp broadcasts sit at 15–25%. Intent-driven, segmented sends reach 35%+. We use 30% as a mid-range default that assumes reasonable segmentation but not full optimisation.
Share of customers that fill in the phone field when it's optional, over 90 days. The standard Shopify optional-phone capture rate sits in the 25–35% band without popups, incentives, or Smart Activation. Keaz typically lifts this further — the calculator stays at the lower bound to be conservative.
Share of customers with a captured phone when the field is required at checkout. A required field on a completed checkout is captured ~100% by definition. We model 90% to account for guest checkouts that bypass phone capture on some payment methods, historic customers from before the policy change, and a small share of checkout drop-off attributable to the new friction.
| Bucket | Formula | Plain English |
|---|---|---|
| Email-engaged | (E ÷ T) × open rate | Customers email actually reaches |
| WA-reachable | phone-capture × active-rate | Customers WhatsApp actually reaches |
| Both | email-engaged × WA-reachable | The overlap — reached by both |
| Email-only | email-engaged − both | Email reaches, WhatsApp doesn't |
| WhatsApp-only · NEW | WA-reachable − both | WhatsApp reaches, email doesn't |
| Out of reach | 1 − the rest | Neither channel reaches them today |
2.4 · Output: total additional revenue
The numerator captures two sources of new revenue: the new audience converting at the lifted rate, and the overlap audience converting incrementally better. The denominator is the email-only baseline. Soft-capped at 95% for credibility.
additional_revenue_% = (new_audience × CVR_email+WA + overlap × CVR_uplift)
÷ (email_engaged_share × CVR_email)3 · Money on the table — every number
The Money-on-the-Table calculator answers: "If I do nothing, how much revenue am I losing each month, and where exactly?" The number is expressed as a percentage of annual revenue, per month. Mature WhatsApp programs in DTC e-commerce typically contribute 6–18% of total store revenue annually. Our ranges are calibrated to land in the lower half of that band.
monthly_gap_low = annual_revenue × vertical_rate_low_monthly monthly_gap_high = annual_revenue × vertical_rate_high_monthly monthly_gap_mid = average(low, high) yearly_gap_mid = monthly_gap_mid × 12
3.1 · Vertical rates
Eight verticals, each with a monthly low/high % of annual revenue. The annualised range is shown for context. All rates assume: the shop sells DTC on Shopify · email is the existing primary marketing channel · WhatsApp is added as a second channel (not replacing email).
| Vertical | Monthly Low | Monthly High | Annualised | Why |
|---|---|---|---|---|
| Pet | 1.10% | 1.60% | 13.2–19.2% | Highest repeat frequency · subscription-style replenishment fits WhatsApp re-order reminders extremely well. |
| Beauty | 0.86% | 1.34% | 10.3–16.1% | Lower AOV than fashion, but strong repeat purchase + review-driven discovery. Keaz wins on retention. |
| Food & Beverage | 0.86% | 1.34% | 10.3–16.1% | High frequency, low AOV, very predictable replenishment cadence. |
| Health | 0.80% | 1.20% | 9.6–14.4% | Routine-driven replenishment · high re-order share, moderate AOV. |
| Fashion | 0.90% | 1.40% | 10.8–16.8% | High AOV combined with strong brand loyalty · highest revenue-per-recipient on launches and VIP previews. |
| Kids & Baby | 0.66% | 1.10% | 7.9–13.2% | Strong repeat, but age-stage transitions reduce LTV ceiling per customer. |
| Jewelry | 0.60% | 0.96% | 7.2–11.5% | Highest AOV, but lowest frequency · most revenue from launch + VIP, less from recurring flows. |
| Home & Living | 0.48% | 0.80% | 5.8–9.6% | Lowest frequency category · recurring flows contribute less, but Cart Recovery still pulls weight on high-AOV carts. |
3.2 · Flow split — where the money is hiding
Of the monthly gap (mid value), the calculator splits the contribution across four flows.
| Flow | Share | Effectiveness | What it does |
|---|---|---|---|
| Cart Recovery | 40% | High | WhatsApp reminder for abandoned carts. Largest single lever — high intent, short decision window. |
| Welcome series | 25% | High | Conversational sequence after first paid order. Highest per-recipient revenue. |
| Re-Order Reminder | 20% | Medium | Time-triggered nudge based on last order date. Strongest in replenishment categories. |
| Sleeping contacts | 15% | Medium | Re-permissions historic customers · recovers an otherwise dormant pool. |
The split is intentionally a gap-allocation, not a flow-by-flow forecast. Its job is to make the size and shape of the opportunity visible — not to predict a specific flow's performance for a specific shop.
4 · Glossary
Key terms used across the Forecast and this methodology.
| Term | Definition |
|---|---|
| CCC | Customer Contact Coverage — share of last-12-month active Shopify customers reachable on WhatsApp (have a phone on file). |
| MCC | Marketing Contact Coverage — share of email subscribers also reachable on WhatsApp. |
| CVR | Conversion rate — share of an audience that completes a purchase from a touchpoint. |
| AOV | Average order value. |
| DTC | Direct-to-consumer brand — sells through its own Shopify store, not retailers. |
| Reached / Reachable | Share of customers a channel can deliver to and have engagement with. |
| Smart Activation | Keaz feature that re-permissions historic Shopify customers for WhatsApp marketing — throttled to 2 runs per year. |
5 · Calibration
Every number here is reviewed quarterly against real Keaz program data. As the customer base grows, defaults are re-anchored against:
- The median CCC/MCC of Keaz-installed shops, per vertical.
- The actual revenue contribution share of WhatsApp vs email on shops where both run side-by-side.
- The actual flow contribution split observed in Keaz's own attribution.
When real data overrides a default in this document, the new value is set at most equal to the data point — leaving headroom for the calculator to remain conservative as Keaz's program matures.