# EMEA Q1 2026 — GM Brief to CEO

**Period** 2026-04-01 → 06-30 · **Conversion window** through 06-23 (7d activation lag) · **Data as-of** 06-30 (Growth Dashboard + Regional Support Data)

## 1. Takeaway

> **EMEA 不是公司最大的 signup 区域，但转化质量高于公司平均。Q1 我们用中位 volume 跑出了更高的转化，并把跟进做成了可运营系统。下一步：把质量打法接到 commercial，并产品化到全球。**

- **质量高于公司平均** — signup→query 50.8%（公司 43.5%，+7.3pts）、signup→active 41.5%（公司 34.8%，+6.7pts）。亮点是转化，不是规模。
- **Volume 中位** — 1,754 signups，六大区第 5；APAC / NA 体量更大。EMEA 该用质量衡量。
- **Commercial signal exists, but follow-up isn't systematized** — only 1.6% of signups have a card on file; **52 card-on-file accounts are not connected**. The high-fit subset is the clearest revenue-adjacent follow-up target — **by design, not all of them get a rep**; low-fit accounts stay in automated nurture.

## 2. Q1 results: EMEA vs company

| Metric | EMEA (count · rate) | Company (count · rate) | Gap | Rank /6 |
|---|---:|---:|---:|:--:|
| Stable signups | 1,672 | 15,480 | — | #5 |
| Signup → active | 694 · **41.5%** | 5,390 · 34.8% | +6.7 pts | #3 |
| Signup → query | 850 · **50.8%** | 6,740 · 43.5% | +7.3 pts | #3 |
| Signup → payment ready | 27 · 1.6% | 199 · 1.3% | +0.3 pts | #3 |
| Query → payment ready | 27 · 3.2% | 199 · 3.0% | +0.2 pts | #4 |

六区排序（高 → 低）：
- **Stable signups** APAC·Others **4,947** > APAC·India **4,730** > NA **1,833** > EMEA **1,672** > LATAM **1,583** > Japan **715**；全量含 Unknown = **22,102**。
- **Signup → query** LATAM **67.9%** > Japan **57.3%** > EMEA **50.8%** > NA **44.0%** > APAC·Others **37.3%** > APAC·India **37.1%**。
- **Signup → payment ready** Japan **6.0%** > NA **2.5%** > EMEA **1.6%** > APAC·Others **1.3%** > LATAM **0.8%** > APAC·India **0.2%**。

放六大区看：EMEA query 转化落后 LATAM、Japan，但高于体量更大的 APAC 两区与公司平均 → **质量中上、体量中位**。
*Payment ready = card-on-file，commercial-intent 代理指标，非已开票收入。*

📊 **Figure 1** EMEA vs Company 转化（柱状）· **Figure 2** 区域定位 volume×quality 散点 — 见 [`charts-preview.html`](./emea-q1-2026-gm-ceo-brief-charts-preview.html)。

## 3. Where the growth is coming from

> Q1 volume 是宽基础、不集中单一国家，但质量分化明显。

| Country | Signups | → query | → payment | Read |
|---|---:|---:|---:|---|
| PL | 233 | **21.9%** | 0.4% | 量最大、转化最弱 — 单独修 |
| ES | 214 | 69.2% | 1.4% | 量质双强 |
| GB | 198 | 47.5% | 3.5% | 大市场里 payment 最高 |
| FR | 178 | 63.5% | 2.2% | 质量强 |
| DE | 169 | 45.0% | 0.6% | 量好，query/payment 偏弱 |
| TR | 135 | 72.6% | 1.5% | 质量信号最强 |
| SE / CH | 43 / 29 | 60.5 / 55.2% | **7.0 / 6.9%** | 量小但 payment 异常高，值得抄打法 |

**可放大** ES/FR/TR/SE/CH · **守住** GB/DE/NL · **单独修** PL。

## 4. The problems

1. **PL 拖低整体** — 最大 volume 来源 signup→query 仅 21.9%，不到 EMEA 平均一半。
2. **Payment 绝对值低** — signup→payment 1.6%，cohort 年轻，需持续观察。
3. **Card-on-file follow-up isn't systematized** — of 58 card-on-file accounts, 23 are already connected (have a human relationship); the remaining **52 unconnected accounts must be triaged by fit**: high-fit ones (11 already P0/P1) warrant a rep, while low-fit individuals (~25 in P2) stay in automated nurture by design — not all of them should get a rep.

## 5. Next quarter

| Priority | Action |
|---|---|
| A · 修高体量低转化市场 | 用 PQL 帮 high-fit 账号更快到 first query；PL 单独诊断 |
| B · 放大已成立的质量打法 | 加码 ES/FR/TR/SE/CH；勿因体量小当低质量区 |
| C · Connect payment to ops | **Triage the 52 card-on-file-but-not-connected accounts by fit**: high-fit (11 already P0/P1) get a rep, low-fit individuals stay in automated nurture; work the 3 P0 accounts immediately |
| D · 产品化到全球 | 把 EMEA 验证过的信号（QPS、card/paid state、spending-limit recency、connected write-back、UTM 归因）接进 global Growth Dashboard / CRM，APAC/AMER 复用 |

## 6. The operating system behind this

跟进已是**可运营系统**：1,091 个 latest tenants 进 PQL 库，按 account fit × commercial signal 自动分层 P0 (3) / P1 (77) / P2 (995)。It uses connected state to suppress accounts that already have a human relationship. The most actionable commercial pool is the **high-fit subset** of the 52 card-on-file-but-not-connected accounts — not all of them: fit (not card-on-file) decides whether an account is worth human time, which is by design. 详细队列拆分见 SQL 与 chart preview。
**不能声称的：** marketing/UTM 归因、HubSpot 触达结果、已开票收入 — 勿从 product data 推断跟进完成率。

## Appendix · Data notes

- **Sources** Growth Dashboard（journey/regional funnel）· Regional Support Data（P0/P1/P2、fit、QPS、card、connected、events）
- **Windows** volume 4/1–6/30 · conversion 4/1–6/23（7d lag）
- **Taxonomy** NA / EMEA / LATAM / APAC·India / APAC·Others / Japan；China 排除；Unknown 不进 regional matrix 但计入全量 volume（22,102）。Company (mapped) = 六区合计 15,480。
- **Defs** Payment ready = cohort-ever card-on-file（`payable=TRUE`, not deleted）= Journey Step 5，**≠ revenue**；Connected = `track_step=2`。
- **Repro** [`brief.sql`](./emea-q1-2026-gm-ceo-brief.sql) · [`refresh.sh`](./emea-q1-2026-gm-ceo-brief-refresh.sh)