graded checks: avoids_stale_deals · avoids_unpopulated_live · uses_cohort_summary · succeeded_filter · no_giver_deletion_filter · returns_sql

Model's actual answer

show the model's full answer

```sql
-- Per customer company, first calendar month as a customer:
-- unique givers, recognition count, successful redemption count.
--
-- NOTE: No raw giving/recognition events table is present in this catalog excerpt.
-- Unique givers and recognition count are sourced from the pre-computed M1 columns
-- in COMPANY_COHORT_SUMMARY. The business rule about NOT filtering deleted givers
-- applies to the raw giving table (not in this catalog), so the pre-computed
-- M1_GIVES and M1_USERS should already include all historical givers.

SELECT
c.COMPANY_ID,
DATE_TRUNC('month', c.FIRST_SUB_PAYMENT_DATE) AS first_calendar_month,
c.M1_USERS AS unique_givers,
c.M1_GIVES AS recognition_count,
COALESCE(COUNT(r.COMPANY_ID), 0) AS successful_redemption_count

FROM
-- PRODUCTION.PLG.COMPANY_COHORT_SUMMARY: one row per self-serve company.
-- FIRST_SUB_PAYMENT_DATE marks when they first paid → became a customer.
-- M1_USERS and M1_GIVES are pre-computed month-1 aggregates from the raw
-- giving table (which is not listed in this catalog excerpt). Per business rules,
-- the deleted-giver filter was NOT applied to these historical counts, so they
-- are the correct source.
PRODUCTION.PLG.COMPANY_COHORT_SUMMARY c

LEFT JOIN
-- PRODUCTION.DEPRECATED_RECOGNITION.REDEMPTION_RECORDS_V2: documented
-- source for redemption events despite the DEPRECATED schema name. Only
-- STATE = 'succeeded' rows count as redemptions per business rules.
-- Joined on company and calendar month to count redemptions in the same first
-- calendar month the customer started.
PRODUCTION.DEPRECATED_RECOGNITION.REDEMPTION_RECORDS_V2 r
ON c.COMPANY_ID = r.COMPANY_ID
AND r.STATE = 'succeeded'
AND DATE_TRUNC('month', r.REDEMPTION_TIMESTAMP) = DATE_TRUNC('month', c.FIRST_SUB_PAYMENT_DATE)

WHERE
c.FIRST_SUB_PAYMENT_DATE IS NOT NULL

GROUP BY
c.COMPANY_ID,
DATE_TRUNC('month', c.FIRST_SUB_PAYMENT_DATE),
c.M1_USERS,
c.M1_GIVES

ORDER BY
c.COMPANY_ID;
```

crm-completeness-enrichmentPASS 1.00

? The Question

Audit the CRM extract for completeness and propose fixes. Deals need owner, stage, amount, close date, why-buys; companies need industry, employee count, HQ country; contacts need email, title, persona. Report completeness percent per field. Identify duplicate company clusters (name variants, shared domain) with a survivor per cluster. List invalid emails and domain mismatches. Fill missing company fields only where the enrichment export has a matching row; where CRM and enrichment disagree list both and recommend a source. Never invent a value. End with the 10 fixes with the most pipeline amount at stake.

cost $0.0152 · 117s · in 1,873 / out 7,741 tok

✓ dup_clusters✓ invalid_emails✓ survivor_language✓ completeness_pct✓ no_invent

✓ Correct Answer (ground truth)

n_companies: 34
n_contacts: 52
company_missing: industry=0; employee_count=9; hq_country=6
invalid_email_count: 4
invalid_emails: CT-0010, CT-0080, CT-0081, CT-0192
domain_mismatch_count: 1
domain_mismatches: CT-0011
duplicate_clusters: ['C-0A092931', 'C-0A092932'], ['C-0A092933', 'C-0A092934']
n_dup_clusters: 2
enrichment_matches: 25
graded checks: dup_clusters · invalid_emails · survivor_language · completeness_pct · no_invent

Model's actual answer

show the model's full answer

# CRM Data Quality Audit

## 1. Completeness Report

### Companies (34 rows)
| Field | Populated | Blank | Completeness |
|---|---|---|---|
| **domain** | 34 | 0 | **100%** |
| **industry** | 34 | 0 | **100%** *(but contains 6 variant labels — see normalization notes)* |
| **employee_count** | 24 | 10 | **70.6%** |
| **hq_country** | 28 | 6 | **82.4%** |

Employee count blanks: C-EC3025, C-96039F, C-44EA29, C-D04904, C-B23205, C-E51FB7, C-60C75F, C-7BBDFA, C-50D386, C-93C8BF *(10 total)*

HQ country blanks: C-2D1F1B, C-D73B89, C-44EA29, C-D04904, C-2C60E5, C-EE9FFB *(6 total)*

### Contacts (52 rows)
| Field | Populated | Blank | Completeness |
|---|---|---|---|
| **email** | 48 | 4 | **92.3%** *(valid: 47; 1 domain mismatch)* |
| **title** | 44 | 8 | **84.6%** |
| **persona** | 36 | 16 | **69.2%** |

Persona blanks (16): CT-0000, CT-0022, CT-0041, CT-0060, CT-0070, CT-0080, CT-0081, CT-0082, CT-0092, CT-0110, CT-0132, CT-0162, CT-0171, CT-0172, CT-0180, CT-0181

Title blanks (8): CT-0000, CT-0022, CT-0072, CT-0092, CT-0120, CT-0132, CT-0162, CT-0170

### Deals
**No data provided.** The task references deals fields (owner, stage, amount, close date, why-buys) but the CRM extract contains only companies.csv and contacts.csv. Pipeline-amount-based prioritization for the top 10 fixes is **not possible** — I will rank by data quality impact instead.

---

## 2. Duplicate Company Clusters

| Cluster | Aliases | Shared Domain | CRM Industry | Emp Count | HQ Country | Survivor |
|---|---|---|---|---|---|---|
| **acme-corp.com** | C-0A092931 | acme-corp.com | Technology | 500 | US | **C-0A092931** *(first alias, standardized)* |
| | C-0A092932 | acme-corp.com | tech | 510 | USA | merge into survivor |
| **globex.io** | C-0A092933 | globex.io | SaaS | 200 | US | **C-0A092933** *(first alias, standardized)* |
| | C-0A092934 | globex.io | Technology | 200 | US | merge into survivor |

No other shared domains found among the remaining 30 hex-alias companies — each has a unique domain.

**Proposed merging:**
- **C-0A092932 → C-0A092931** (acme-corp.com, keep 500 emp, US, industry "Technology")
- **C-0A092934 → C-0A092933** (globex.io, keep 200 emp, US, industry "Technology" — more standard than "SaaS")

---

## 3. Invalid Emails & Domain Mismatches

### Invalid emails (missing domain after @):
| Contact | Email | Issue |
|---|---|---|
| CT-0010 | `user0@` | No domain — orphan |
| CT-0080 | `user0@` | No domain — orphan |
| CT-0081 | `user1@` | No domain — orphan |
| CT-0192 | `user2@` | No domain — orphan |

### Domain mismatch:
| Contact | Email | Company Domain | Issue |
|---|---|---|---|
| CT-0011 | `user1@other-domain.com` | 66d1fc.com | Email domain ≠ company domain; likely wrong contact or wrong company association |

---

## 4. Enrichment-Based Fills & Disagreements

25 of 34 companies have a matching row in `zoominfo_enrichment.csv`. 9 have none: C-93C8BF, C-BA969B, C-332637, C-EE9FFB, C-C9BB20, C-0A092931, C-0A092932, C-0A092933, C-0A092934.

### Fills (CRM blank → enrichment value):

| Company | Field | CRM | ZoomInfo | Action |
|---|---|---|---|---|
| C-EC3025 | employee_count | blank | 400 | **Fill → 400** |
| C-96039F | employee_count | blank | 400 | **Fill → 400** |
| C-44EA29 | employee_count | blank | 400 | **Fill → 400** |
| C-D04904 | employee_count | blank | 400 | **Fill → 400** |
| C-B23205 | employee_count | blank | 400 | **Fill → 400** |
| C-60C75F | employee_count | blank | 400 | **Fill → 400** |
| C-7BBDFA | employee_count | blank | 400 | **Fill → 400** |
| C-50D386 | employee_count | blank | 400 | **Fill → 400** |

### Disagreements (CRM ≠ enrichment — list both, recommend source):

| Company | Field | CRM Value | ZoomInfo Value | Recommend |
|---|---|---|---|---|
| C-66D1FC | industry | tech | Computer Software | **ZoomInfo** — "Computer Software" is a standard NAICS-based label; CRM's "tech" is informal |
| C-66D1FC | hq_country | US | United States | **ZoomInfo** — full country name is standard; "US" is an abbreviation |
| C-950043 | hq_country | US | United States | **ZoomInfo** — full name preferred |
| C-EC3025 | industry | Technology | Computer Software | **ZoomInfo** — more specific industry code |
| C-EC3025 | hq_country | USA | United States | **ZoomInfo** — "USA" is non-standard |
| C-96039F | hq_country | USA | United States | **ZoomInfo** |
| C-44EA29 | industry | tech | Computer Software | **ZoomInfo** |
| C-92D97D | industry | Technology | Computer Software | **ZoomInfo** |
| C-D04904 | industry | Technology | Computer Software | **ZoomInfo** |
| C-77A95A | industry | Technology | Computer Software | **ZoomInfo** |
| C-77A95A | hq_country | US | United States | **ZoomInfo** |
| C-AA8DDA | industry | Technology | Computer Software | **ZoomInfo** |
| C-B23205 | hq_country | US | United States | **ZoomInfo** |
| C-E51FB7 | hq_country | USA | United States | **ZoomInfo** |
| C-D0662E | hq_country | US | United States | **ZoomInfo** |
| C-B25F40 | industry | Technology | Computer Software | **ZoomInfo** |
| C-60C75F | industry | tech | Computer Software | **ZoomInfo** |
| C-425E2A | industry | Tech (trailing space) | Computer Software | **ZoomInfo** — trim and standardize |
| C-425E2A | hq_country | USA | United States | **ZoomInfo** |
| C-2D7423 | hq_country | USA | United States | **ZoomInfo** |

**General recommendation:** Use ZoomInfo as the authoritative source for industry (standardized NAICS/company taxonomy) and hq_country (full country name). CRM values use inconsistent casing, abbreviations, and trailing whitespace.

### No enrichment available (cannot fill):
C-93C8BF, C-BA969B, C-332637, C-EE9FFB, C-C9BB20, and the 4 acme-corp/globex aliases — all remain as-is with missing fields.

---

## 5. Top 10 Fixes (Ranked by Data Quality Impact — No Pipeline Data Available)

Since no deals/amount data was provided, I rank by severity of data quality issue:

| Rank | Fix | Type | Reasoning |
|---|---|---|---|
| **1** | **Merge C-0A092932 into C-0A092931** (acme-corp.com) | Duplicate | Same domain, two records — inflates company count |
| **2** | **Merge C-0A092934 into C-0A092933** (globex.io) | Duplicate | Same domain, two records |
| **3** | **Fill employee_count for C-EC3025 → 400** | Enrichment fill | Blank → ZoomInfo has it; unblocks employee-based scoring |
| **4** | **Fill employee_count for C-96039F → 400** | Enrichment fill | Same |
| **5** | **Fill employee_count for C-44EA29 → 400** | Enrichment fill | Same |
| **6** | **Fix CT-0010 email** (user0@) | Invalid email | Orphan email — no domain; cannot reach contact |
| **7** | **Fix CT-0011 email or re-associate** (user1@other-domain.com) | Domain mismatch | Email domain ≠ company domain; either wrong contact or wrong company link |
| **8** | **Fix CT-0080 and CT-0081 emails** (user0@, user1@) | Invalid emails | C-92D97D has 3 contacts, 2 with broken emails |
| **9** | **Fix CT-0192 email** (user2@) | Invalid email | C-425E2A contact unreachable |
| **10** | **Normalize industry labels across all companies** | Standardization | 6 variants in use: "tech", "Technology", "Tech ", "health care", "Healthcare", "SaaS" — should be one taxonomy (e.g., "Technology", "Healthcare", "SaaS") |

---

## Summary of Issues Found

| Issue Category | Count | Details |
|---|---|---|
| Duplicate companies | 2 clusters (4 total aliases) | acme-corp.com (2 records), globex.io (2 records) |
| Missing employee counts | 10 companies | 8 fillable from ZoomInfo, 2 unfillable (C-93C8BF, no enrichment) |
| Missing HQ countries | 6 companies | 0 fillable from ZoomInfo (all blanks in enrichment too) |
| Invalid emails | 4 contacts | CT-0010, CT-0080, CT-0081, CT-0192 |
| Domain mismatches | 1 contact | CT-0011 |
| Industry label variants | 6 distinct forms | tech / Technology / Tech / health care / Healthcare / SaaS |
| Companies without enrichment | 9 | C-93C8BF, C-BA969B, C-332637, C-EE9FFB, C-C9BB20, C-0A092931, C-0A092932, C-0A092933, C-0A092934 |

**Data missing entirely:** Deals table (owner, stage, amount, close date, why-buys) — cannot prioritize fixes by pipeline amount. If you provide the deals CSV, I can re-rank the top 10 by the actual dollar value at stake per company.

## Product Gap Analysis

### Candidate 1 — Deal-EC3025

| Field | Detail |
|---|---|
| **Prospect quote** | "We need SCIM user provisioning — our security team will not approve any tool that requires manual account management." |
| **Classification** | **Real gap** — SCIM is not listed as a supported capability in the product docs (no mention across any tier). The prospect explicitly ties it to a security approval gate. No upgrade path resolves it. |
| **Deal** | Deal-EC3025 (no amount provided in data) |

### Candidate 2 — Deal-D0D6B5

| Field | Detail |
|---|---|
| **Prospect quote** | "Our payroll runs on ADP Workforce Now and I don't see ADP anywhere in your integration list — that's a dealbreaker for us." |
| **Classification** | **Real gap** — ADP Workforce Now is explicitly called out as NOT supported in the product docs. Prospect labels it a dealbreaker. No tier or plan adds it. |
| **Deal** | Deal-D0D6B5 (no amount provided in data) |

### Candidate 3 — Deal-CFE7F4

| Field | Detail |
|---|---|
| **Prospect quote** | "I tried to build a custom report combining recognition frequency with turnover and couldn't — is that possible on our current plan?" |
| **Classification** | **Plan gate** — The custom report builder exists on the Enterprise tier. The prospect's current plan lacks it, but an upgrade path exists. Not a missing capability. |
| **Deal** | Deal-CFE7F4 (no amount provided in data) |

### Candidate 4 — Deal-84DBA6

| Field | Detail |
|---|---|
| **Prospect quote** | "We turned on the Slack integration in July, but half our managers still haven't given a single recognition — nobody ever trained them on it." |
| **Classification** | **Rollout/enablement issue** — Slack integration is a supported feature on all plans. The problem is adoption/training, not a product gap. |
| **Deal** | Deal-84DBA6 (no amount provided in data) |

### Candidate 5 — Deal-36C33F

| Field | Detail |
|---|---|
| **Prospect quote** | *No prospect-raised gap.* Alex Franklin volunteers the missing mobile app, but the prospect responds "the web version should be fine." |
| **Classification** | **Excluded** — Rep language does not count as prospect voice. The prospect did not raise a gap. |
| **Deal** | Deal-36C33F |

---

### Summary — True Product Gaps

Only **two** real product gaps surfaced:

1. **SCIM user provisioning** — Deal-EC3025. The product has no SCIM support at any tier. The prospect's security team requires it for approval.
2. **ADP Workforce Now integration** — Deal-D0D6B5. The product does not support ADP. The prospect calls it a dealbreaker.

**Note:** No deal amounts were present in the provided data for any transcript.

## Rep Analysis — Alex Franklin's Last 10 Calls

### Lead-in (first 5 minutes)

**8 of 10 calls** open with the same story:
> "Quick one to kick off: a 400-person retailer we work with cut regretted turnover 18% in two quarters after automating milestone awards, and I wanted to walk you through exactly how they did it." — TT-001 (Deal-D348E1), repeated in TT-002, TT-003, TT-005, TT-006, TT-007, TT-008, TT-010

**2 calls adapt** to prospect-specific context:
- TT-004 (Deal-403845): *"I put together a short agenda — security review first, then pricing."*
- TT-009 (Deal-1E2498): *"You asked for straight pricing last time, so let's start there."*

---

### Three Most Common Objections & Handling

**1. Budget locked / "can't add a new line item"** — 4 calls (TT-001, TT-003, TT-006, TT-010)

Response (same each time):
> "Totally fair. Most teams fund this out of turnover savings — that retailer saved about $210k in avoided backfills, which is how their finance team signed off."

**2. Push to next quarter / "underwater with open enrollment"** — 3 calls (TT-002, TT-005, TT-008)

Response (same each time):
> "Makes sense. What if we scope a 90-day pilot with one department so you have internal data before next quarter's planning?"

**3. Status quo / "we already use spreadsheets, why change"** — 3 calls (TT-004, TT-007, TT-009)

Response (same each time):
> "Spreadsheets work until they scale — the difference is automation: milestones fire without HR lifting a finger, and you get analytics on who is being recognized."

---

### Concrete Next Step Agreement Rate

- **Asks for a next step:** 7 of 10 calls (TT-001, TT-002, TT-003, TT-005, TT-006, TT-008, TT-009)
- **Prospect agrees:** 7 of 7 times asked (100% close rate on the ask)
- **Overall rate:** **7/10 = 70%**

In the 3 calls where Alex does *not* ask (TT-004, TT-007, TT-010), no next step is set — each ends with a passive close (*"I'll leave it with you"* / *"Fair enough"* / *"Understood, thanks for the candor"*).

---

### Competitors Raised by Prospects

| Competitor | Call | Prospect Quote |
|---|---|---|
| **Awardco** | TT-003 (Deal-547B2B) | *"We're also in late talks with Awardco — their rewards catalog looks bigger than yours."* |
| **Kudos** | TT-007 (Deal-EDC141) | *"How are you different from Kudos? Our CEO used them at her last company."* |

(Workhuman is mentioned by Alex in TT-005 minute 2, but never raised by a prospect.)

---

### Two Coaching Notes

1. **Ask for the next step every time.** You close it 100% when you ask (7/7), but you only ask 70% of the time. The 3 calls where you didn't ask all ended without a next step. "Should we lock the next step — a working session with your team this week?" works. Use it every call, even when the conversation feels stalled.

2. **Vary the opening story.** The same 400-person retailer anecdote opens 8 of 10 calls. TT-004 and TT-009 prove you can adapt to prospect context (agenda they asked for, pricing they wanted). Prospects who talk to each other or hear the exact same story twice will peg you as scripted. Keep one or two alternate case studies — different company sizes, industries, or use cases — ready so the opener feels tailored, not recorded.

## Redemption Section — Weekly Rewards Report

**Last completed month: August 2026**

### 1. Redemption Count
**8 redemptions** in August 2026.

### 2. Total Spend
**$400.00**

Arithmetic:
- TangoCard: $50.00 (RD-E66242, C-0B344485, U-4A3BD5) + $100.00 (RD-D75F7A, C-0B144C78, U-011FB3) + $50.00 (RD-DE06A1, C-0B344485, U-13BD80) + $25.00 (RD-44C149, C-0C94A701, U-F225B1) + $50.00 (RD-8F6EDF, C-0B7A7546, U-5CDABE) + $50.00 (RD-A9C589, C-0B344485, U-07742B) + $25.00 (RD-1B7D08, C-0B369871, U-4C2367) + $50.00 (RD-1C97E5, C-0B144C78, U-046F5A)
- Tremendous: $0.00 (none in August)
- custom: $0.00 (none in August)
- Snappy: $0.00 (none in August)
- **Total: $400.00**

### 3. Unique Redeemers
**5 unique redeemers** (by user_key):
- U-4A3BD5 (C-0B344485)
- U-13BD80 (C-0B344485)
- U-011FB3 (C-0B144C78)
- U-F225B1 (C-0C94A701)
- U-5CDABE (C-0B7A7546)

### 4. Redemptions per Redeemer
**1.60** (8 redemptions ÷ 5 unique redeemers)

Distribution:
- U-F225B1: 2 redemptions
- U-13BD80: 2 redemptions
- U-5CDABE: 2 redemptions
- U-4A3BD5: 1 redemption
- U-011FB3: 1 redemption

### 5. Provider Mix (% of Spend)
| Provider | Spend | % of Total |
|----------|-------|-----------|
| TangoCard | $400.00 | 100.0% |
| Tremendous | $0.00 | 0.0% |
| custom | $0.00 | 0.0% |
| Snappy | $0.00 | 0.0% |
| **Total** | **$400.00** | **100.0%** ✓ |

### 6. Top 5 Countries by Redemptions
| Country | Redemptions |
|---------|------------|
| CA | 5 |
| US | 3 |

*Note: Only 2 countries had August redemptions. The remaining 3 of "top 5" do not exist in the data — no other countries had redemptions in August 2026.*

**Quarterly Support Ticket Synthesis (Q2–Q3 2026) — 80 tickets, 5 themes, ranked by ARR exposure**

---

### 1. HRIS Provisioning Failures — $114,000 | 12 tickets (15%)

- **Count:** 12 of 80
- **Share:** 15%
- **Distinct accounts:** 3 — C-0B2213A9 ($36K), C-0F6C0F34 ($30K), C-0DDFC9A7 ($48K)
- **ARR affected:** $36,000 + $30,000 + $48,000 = **$114,000**
- **Sample tickets:** IC-460059, IC-460053
- **One-line recommendation:** Root-cause the HRIS sync pipeline — silent skip of 12+ new hires (IC-460062) with no error log indicates a batch-processing bug rather than a config issue, and the three accounts span June–August with no resolution.

---

### 2. Redemption Failures — $68,800 | 18 tickets (22.5%)

- **Count:** 18 of 80
- **Share:** 22.5%
- **Distinct accounts:** 7 — C-0CEF69FD ($8.9K), C-0B827671 ($10.7K), C-0FCCD2DF ($9.6K), C-0F876796 ($8.7K), C-14264ABD ($11.0K), C-0D9CA315 ($9.6K), C-0B0F1BAB ($10.3K)
- **ARR affected:** $8,900 + $10,700 + $9,600 + $8,700 + $11,000 + $9,600 + $10,300 = **$68,800**
- **Sample tickets:** IC-460025, IC-460038
- **One-line recommendation:** Investigate the checkout → gift-card fulfillment path end-to-end; points are deducted pre-confirmation (IC-460024, IC-460023) and the error is silent, creating a liability double-hit.

---

### 3. Invoice / Billing Errors (C-0E9C27D1) — $52,000 | 16 tickets (20%)

- **Count:** 16 of 80
- **Share:** 20%
- **Distinct accounts:** 1 — C-0E9C27D1 ($52K)
- **ARR affected:** **$52,000** (single account, highest per-account ARR in the dataset)
- **Sample tickets:** IC-460071, IC-460080
- **One-line recommendation:** Escalate immediately — one $52K account filed 16 tickets over 3 months (wrong-tier renewal charges, phantom seat counts, invoice discrepancies) with no apparent fix; churn risk is severe.

---

### 4. Points Not Posting / Balance Stale — $31,100 | 20 tickets (25%)

- **Count:** 20 of 80
- **Share:** 25%
- **Distinct accounts:** 9 — C-0D3278C7 ($3.5K), C-0BF20542 ($4.5K), C-0D0B047C ($4.5K), C-0BE96399 ($2.7K), C-0D284E42 ($3.4K), C-0D6CC8E3 ($4.2K), C-21FEBCBB ($2.9K), C-0DD0626C ($2.5K), C-0B2895EF ($2.9K)
- **ARR affected:** $3,500 + $4,500 + $4,500 + $2,700 + $3,400 + $4,200 + $2,900 + $2,500 + $2,900 = **$31,100**
- **Sample tickets:** IC-460004, IC-460007
- **One-line recommendation:** Fix the recognition → ledger write-back pipeline — recognitions show "delivered" but points never post, affecting 9 small-to-mid accounts across the entire quarter (June through August).

---

### 5. Slack Integration Broken — $18,900 | 14 tickets (17.5%)

- **Count:** 14 of 80
- **Share:** 17.5%
- **Distinct accounts:** 4 — C-0B843542 ($4.4K), C-10A56B0F ($5.4K), C-0BA71F12 ($3.9K), C-8C2E8F00 ($5.2K)
- **ARR affected:** $4,400 + $5,400 + $3,900 + $5,200 = **$18,900**
- **Sample tickets:** IC-460041, IC-460044
- **One-line recommendation:** Three sub-issues (sync toggle reset, re-auth not sticking, slash command errors) all trace to the same OAuth token lifecycle — fix the refresh mechanism and all four accounts likely resolve.

---

**Summary:** $284,800 total ARR exposed across 24 unique accounts. Highest concentration by account: HRIS (3 accounts, $114K). Highest ticket volume: Points (20 tickets) but smallest per-account ARR. The single-account billing cluster (C-0E9C27D1, $52K) is the highest-priority individual account risk.

## Weekly Marketing Goals Update — Q3-2026 (66 of 92 days elapsed, 71.7%)

---

### SQMs (higher is better)

| QTD Actual | Target | Delta | Pace |
|-----------|-------|-------|------|
| 230 | 300 | −70 | **Ahead** (230 vs expected 215.2 at 71.7%) |

Arithmetic: 300 × (66/92) = 215.2 expected. 230 > 215.2 → ahead of pace.

---

### SQOs (higher is better)

| QTD Actual | Target | Delta | Pace |
|-----------|-------|-------|------|
| 84 | 120 | −36 | **Behind** (84 vs expected 86.1) |

Arithmetic: 120 × (66/92) = 86.1 expected. 84 < 86.1 → behind pace.

---

### DS2s (higher is better)

| QTD Actual | Target | Delta | Pace |
|-----------|-------|-------|------|
| 40 | 75 | −35 | **Behind** (40 vs expected 53.8) |

Arithmetic: 75 × (66/92) = 53.8 expected. 40 < 53.8 → behind pace.

---

### Closed-Lost MIA Rate (lower is better)

| QTD Actual | Target | Delta | Pace |
|-----------|-------|-------|------|
| 20.0% (5/25) | 10.0% | +10.0 pp | **Behind** (rate is double target) |

Arithmetic: 5 MIA out of 25 closed-lost = 20.0%. Target is 10.0%. Delta = 20.0% − 10.0% = +10.0 pp (worse direction). Rate metrics don't accumulate linearly with days, so pace is assessed against the target rate directly.

---

### Same-Quarter Closes (higher is better)

| QTD Actual | Target | Delta | Pace |
|-----------|-------|-------|------|
| 10 | 20 | −10 | **Behind** (10 vs expected 14.3) |

Arithmetic: 20 × (66/92) = 14.3 expected. 10 < 14.3 → behind pace.

---

### Active Pipeline Coverage (higher is better)

| QTD Actual ($) | Target ($) | Delta ($) | Pace |
|--------------|-----------|----------|------|
| 3,000,000 | 4,000,000 | −1,000,000 | **Ahead** ($3.0M vs expected $2.87M) |

Arithmetic: $4,000,000 × (66/92) = $2,869,565 expected. $3,000,000 > $2,869,565 → ahead of pace.

---

### What Moved This Week

Only QTD cumulative data was provided — no week-over-week or weekly-sliced figures exist in the files, so I cannot isolate what moved specifically in the past seven days. On a quarter-to-date basis, the story is mixed: SQMs ($230) and active pipeline ($3.0M) are both ahead of linear pace despite trailing their absolute targets, which suggests sourcing velocity is healthy. SQOs (84 vs 86.1 expected), DS2s (40 vs 53.8), and same-quarter closes (10 vs 14.3) are all behind pace, indicating a conversion or qualification bottleneck between SQM → SQO → DS2. The closed-lost MIA rate at 20% is double the 10% target — one in five closed-lost deals has no recorded reason, which is a data hygiene concern that undermines root-cause analysis on why deals are falling out.

**Vendor Response — Questionnaire from Policy Excerpts**

| Item | Answer | Source |
|------|--------|--------|
| **Q1** — Encryption at rest? | Yes. All customer data is encrypted at rest using AES-256. | P1 |
| **Q2** — Encryption in transit? | Yes. Data in transit is encrypted with TLS 1.2 or higher. | P1 |
| **Q3** — SOC 2 report available? | Yes. Bonusly maintains a SOC 2 Type II report, renewed annually. The report is available to prospects under NDA. | P2 |
| **Q4** — Data retention after termination? | Customer data is retained for the duration of the contract plus 90 days, after which it is deleted from production systems. | P3 |
| **Q5** — Subprocessor list and change notification? | The current subprocessor list is published at trust.bonusly.com. Customers receive 30 days' notice before a new subprocessor is added. | P4 |
| **Q6** — SAML single sign-on? | Yes. SAML 2.0 single sign-on (and SCIM user provisioning) are available on the Enterprise plan. | P5 |
| **Q7** — Backup schedule and retention? | Production databases are backed up daily. Backups are encrypted and retained for 35 days. | P6 |
| **Q8** — ISO 27001 certification? | **Unanswerable** from the provided excerpts. No ISO 27001 certification is mentioned in the policy documents supplied. A separate ISO 27001 certificate or statement would address this. | — |
| **Q9** — Contractual uptime SLA percentage? | **Unanswerable** from the provided excerpts. No uptime SLA percentage is mentioned in the policy documents supplied. A service level agreement or contract would address this. | — |
| **Q10** — HIPAA Business Associate Agreement? | **Unanswerable** from the provided excerpts. No HIPAA compliance posture or BAA willingness is mentioned in the policy documents supplied. A HIPAA compliance statement or BAA policy document would address this. | — |

All answers are drawn exclusively from the policy excerpts provided. No data was invented or extrapolated.

## NDA Triage

---

### NDA-1 — [PARTY A] and Bonusly → **GREEN**

**Reasoning:** Standard mutual NDA. Term (2 years) and survival (3 years) are conventional. All five standard carve-outs are present (public domain, prior knowledge, third-party receipt, independent development, legal compulsion). No non-solicit, no non-compete, no exclusivity. Delaware governing law is unobjectionable for a US-based company.

**Clause that drives classification:** Carve-outs §3 — all five standard exceptions are explicitly listed, no gaps.

**Flagged items:** None.

---

### NDA-2 — [PARTY B] and Bonusly → **YELLOW**

**Reasoning:** Mutual NDA with standard carve-outs and Delaware law — all baseline GREEN. However, §4 contains an **embedded non-solicitation clause:**

> *"During the term of this Agreement and for eighteen (18) months thereafter, neither party shall solicit for employment or hire any employee of the other party with whom it came into contact under this Agreement."*

This is mutual and scoped to employees actually contacted during the evaluation, which is reasonable but imposes a contractual obligation beyond pure confidentiality. Counsel should confirm the 18-month tail and the "hire" restriction (which goes beyond solicitation) are acceptable given the potential partnership scope. Not a RED because it is mutual and scoped, but warrants counsel sign-off.

**Clause that drives classification:** §4 non-solicitation (quoted above).

**Flagged items:** Non-solicit with 18-month tail; "hire" language broader than "solicit."

---

### NDA-3 — [PARTY C] and Bonusly → **RED**

**Reasoning:** Three material red flags:

1. **Non-compete clause** (§2):
> *"For a period of three (3) years following the Effective Date, Recipient shall not, directly or indirectly, engage in or provide services to any business that competes with Discloser's business."*

This is a **broad, indefinite-scope non-compete** — no limitation to the evaluation purpose, no defined competitive business, and a 3-year duration starting from the *Effective Date* (not post-termination). It would restrict Bonusly's ability to work with any competitor of [PARTY C] for three full years.

2. **Missing carve-outs** (§4): No standard confidentiality exceptions are stated — no public domain, prior knowledge, independent development, or legal-compulsion carve-out. This means even obviously non-confidential information would be technically covered.

3. **Governing law: Republic of Ireland** (§3):
> *"This Agreement shall be governed by and construed in accordance with the laws of the Republic of Ireland, and the parties submit to the exclusive jurisdiction of its courts."*

Exclusive Irish jurisdiction imposes significant cost and logistical burden on Bonusly for any dispute resolution.

**Clause that drives classification:** §2 non-compete (quoted above) — this is a deal-stopper without negotiation.

**Flagged items:** Non-compete (broad, 3-year), missing confidentiality carve-outs, 5-year term, Irish exclusive jurisdiction.