Subscription Growth Analysis

Subscription Growth Analysis

Produces a same-period MoM subscription health report covering MRR, churn, net growth, and product/country mix — both windows spanning the same number of days for a like-for-like comparison.

Step 0 — Setup

Org ID: Retrieve via list_organizations if not already known. Ask if multiple exist.

Date windows — use the same logic as the other pillar skills:

today     = current date
cm_start  = first day of current month  →  cm_end = today
lm_start  = first day of prior month    →  lm_end = prior month day matching today
            (cap lm_end at last day of prior month if today's day > prior month's length)

State windows and offer custom dates:

"Comparing May 1–19 vs April 1–19. Want to use different dates instead?"

If called by the orchestrator, accept windows directly — don't re-prompt.

Step 1 — Fetch all data

Batch A — 10 calls in parallel

Batch B — 4 more calls in parallel (after Batch A)

Paginate while has_more_page: true. Use API total fields for period-level sums (activations, cancellations) — do not aggregate rows when pagination may truncate.

Step 2 — Compute subscription metrics

2a. Active subscribers and MRR

2b. Activations and cancellations

2c. Churn rate

monthly_churn_CP = cancellations_CP / active_subs_PP × 100
monthly_churn_PP = cancellations_PP / (active_subs at start of PP — use PP live subs)

Standard SaaS convention: denominator is start-of-period active subs (use PP's live count as the CP denominator).

Note for dashboard: if CP is a partial month, label as "period churn rate (N-day window)" rather than "monthly" to avoid over-stating.

2d. MRR decomposition (if available)

Call ZohoBilling_get_mrr_insights_report for CP. If it returns data, extract:

• New MRR (new activations)
• Expansion MRR (upgrades / add-ons)
• Contraction MRR (downgrades)
• Churned MRR (cancellations)
• Net MRR movement

If the report returns empty or is unavailable, skip this section — don't estimate.

2e. Product breakdown

From calls #7–10, build a per-product table for top 10 products by CP activations.

For each product:

• Activations CP and PP
• Cancellations CP and PP
• Net growth CP = act_CP − can_CP
• Net growth PP = act_PP − can_PP
• MoM net growth Δ

Compute top-product activation concentration = (product_1_act / total_act_CP) × 100.

Flag products with:

• Net negative growth in CP (cancellations > activations)

• 20% MoM drop in activations

• Zero PP history (new product launch in CP)

2f. Country breakdown

From calls #11–14, apply the same analysis as 2e for top 10 countries by CP total activity (activations + cancellations).

For each country:

• Activations CP and PP
• Cancellations CP and PP
• Net growth CP and PP
• MoM net growth Δ

Compute top-country activation concentration = (country_1_act / total_act_CP) × 100.

Flag:

• Countries with net negative growth (shrinking markets)
• Countries new in CP (emerging markets — zero PP history)
• "Others" bucket if > 15% of activations (unattributed addresses)

Step 3 — Produce the analysis output

## Subscription Growth — <period_label_cm> vs <period_label_lm>

### Key Metrics
| Metric | <PP label> | <CP label> | Δ |
|---|---|---|---|
| Active subscribers | N | N | +N (+N%) |
| MRR | $X | $Y | +$Z (+N%) |
| ARPU | $X | $Y | +$Z |
| Activations | N | N | +N (+N%) |
| Cancellations | N | N | +N |
| Net growth | +N | +N | +N |
| Period churn rate | N% | N% | +Npp |

**MRR: <direction and magnitude>. Net growth: <direction and magnitude>.**

### MRR Decomposition (if available)
| Component | CP |
|---|---|
| New MRR | +$X |
| Expansion | +$X |
| Contraction | -$X |
| Churned | -$X |
| **Net MRR** | **+$X** |

### Product Performance (Top 10 by CP Activations)
| Product | Act PP | Act CP | Can CP | Net CP | MoM Net Δ |
|---|---|---|---|---|---|
...
_Top-product concentration: N% of activations from "<product name>"_

### Country Performance (Top 10 by CP Activity)
| Country | Act PP | Act CP | Can CP | Net CP | MoM Net Δ |
|---|---|---|---|---|---|
...
_Top-country concentration: N% of activations from "<country>"_
Growing: <list>   Shrinking: <list>

Output contract (for orchestrator)

{
  "pillar": "subscriptions",
  "metrics": {
    "active_subs_cp": <number>,
    "active_subs_pp": <number>,
    "mrr_cp": <number>,
    "mrr_pp": <number>,
    "mom_mrr_pct": <number>,
    "activations_cp": <number>,
    "activations_pp": <number>,
    "cancellations_cp": <number>,
    "net_growth_cp": <number>,
    "net_growth_pp": <number>,
    "period_churn_rate_cp_pct": <number>,
    "arpu_cp": <number>,
    "arpu_pp": <number>,
    "top_product_concentration_pct": <number>,
    "top_country_concentration_pct": <number>
  },
  "mrr_decomposition": {"new": ..., "expansion": ..., "contraction": ..., "churned": ..., "net": ...},
  "top_products": [{"name": "...", "activations_cp": ..., "net_cp": ..., "net_pp": ...}],
  "top_countries": [{"name": "...", "activations_cp": ..., "net_cp": ..., "net_pp": ...}],
  "flags": ["<shrinking markets>", "<product net negative>", "<concentration risk>"]
}

Edge cases

• New org (< 1 month old): PP will be empty. Analyse CP only; note it.
• Products with zero PP data: label as "new product" — don't compute Δ%.
• Churn > 100%: impossible; if it appears, warn and skip churn scoring — denominator likely wrong.
• MRR = 0 for free plans: exclude from ARPU; count them separately as "free subscribers."
• "Others" country: include if top 10, flag as unattributed.
• MRR decomposition unavailable: skip the section entirely.