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

Looking at the catalog, I need to determine which tables have giving/recognition metrics and respect the documented constraints.

Key observations:
- V2_LIVE.OBJECTS_DEALS: unpopulated — cannot use
- PRODUCTION.HUBSPOT.DEALS: stale (last sync 2023-03) — cannot use
- COMPANY_COHORT_SUMMARY: only table with M1 giving/redemption aggregates (M1_USERS, M1_GIVES, M1_REDEMPTIONS)
- No raw giving-events table is listed in the catalog, so pre-aggregated M1 fields are the only path
- The deleted-givers filter must NOT be applied — but since we use pre-aggregated M1 fields (no per-row giver filtering), this constraint is inherently satisfied
- No raw redemption-events table columns are documented beyond STATE, so M1_REDEMPTIONS from the cohort is the usable source

```sql
/*
First calendar month as a customer — per-company giving metrics.
Uses ONLY tables documented in the catalog.
Tables avoided: V2_LIVE.OBJECTS_DEALS (unpopulated),
PRODUCTION.HUBSPOT.DEALS (stale, last sync 2023-03).
No deleted-givers filter applied (would understate historical giving counts).
Redemptions: M1_REDEMPTIONS is pre-filtered to STATE = 'succeeded'
per the cohort summary aggregation.
*/
SELECT
COMPANY_ID,
DATE_TRUNC('MONTH', SIGNUP_DATE) AS first_calendar_month_as_customer,
M1_USERS AS unique_givers,
M1_GIVES AS recognition_count,
M1_REDEMPTIONS AS successful_redemption_count
FROM
/* Self-serve cohort: one row per company. Only catalog source with
pre-aggregated first-month giving (M1_USERS, M1_GIVES, M1_REDEMPTIONS).
M1_* fields cover the calendar month containing SIGNUP_DATE. */
PRODUCTION.PLG.COMPANY_COHORT_SUMMARY
WHERE
SIGNUP_DATE IS NOT NULL
ORDER BY
first_calendar_month_as_customer,
COMPANY_ID;
```

Caveats worth noting:

1. COMPANY_COHORT_SUMMARY covers self-serve (PLG) companies only. Sales-originated customers are not represented here — their giving activity would require a giving-events table that is not in the catalog.

2. M1_USERS is described as active users in month 1. It is the closest proxy for "unique givers" available, but in a recognition platform some users may receive without giving. If a dedicated giving-events table exists outside this catalog excerpt, it would give a more precise unique-giver count.

3. M1_REDEMPTIONS is pre-aggregated. For finance-grade redemptions, the catalog points to PRODUCTION.DEPRECATED_RECOGNITION.REDEMPTION_RECORDS_V2 with STATE = 'succeeded', but that table's column list is not documented here, so a join is not safely constructable from the catalog alone.

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 $0.0042 · 76s · in 3,918 / out 12,761 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 Completeness Audit

---

## SCOPE NOTE

No deals.csv was provided. The audit covers companies.csv (34 records), contacts.csv (52 records), and zoominfo_enrichment.csv (25 records). Without deal data, I cannot rank fixes by pipeline amount at the end; I rank by severity/count instead and flag what's needed.

---

## 1. COMPLETENESS BY FIELD

### Companies (34 rows)

| Field              | Populated | Total | %      |
|--------------------|-----------|-------|--------|
| company_alias      | 34        | 34    | 100.0% |
| domain             | 34        | 34    | 100.0% |
| industry           | 34        | 34    | 100.0% |
| employee_count     | 25        | 34    | 73.5%  |
| hq_country         | 27        | 34    | 79.4%  |

**employee_count blank (9):** C-EC3025, C-96039F, C-44EA29, C-D04904, C-B23205, C-60C75F, C-7BBDFA, C-50D386, C-93C8BF

**hq_country blank (7):** C-2D1F1B, C-D73B89, C-44EA29, C-D04904, C-2C60E5, C-60C75F, C-EE9FFB

### Contacts (52 rows)

| Field       | Populated | Total | %      | Notes                    |
|-------------|-----------|-------|--------|--------------------------|
| contact_key | 52        | 52    | 100.0% |                          |
| company_alias| 52       | 52    | 100.0% |                          |
| email       | 52        | 52    | 100.0% | 4 present but invalid (no domain) |
| title       | 40        | 52    | 76.9%  | 12 blank                 |
| persona     | 37        | 52    | 71.2%  | 15 blank                 |
| domain      | 52        | 52    | 100.0% |                          |

**title blank (12):** CT-0000, CT-0022, CT-0072, CT-0080, CT-0081, CT-0092, CT-0120, CT-0121, CT-0122, CT-0132, CT-0141, CT-0170

**persona blank (15):** CT-0000, CT-0022, CT-0041, CT-0060, CT-0070, CT-0081, CT-0082, CT-0092, CT-0110, CT-0132, CT-0162, CT-0171, CT-0172, CT-0180, CT-0181

### Deals

MISSING ENTIRELY — no deals.csv was provided. Cannot audit owner, stage, amount, close_date, or why_buys. Cannot rank fixes by pipeline amount. This is the single largest gap in the extract.

---

## 2. DUPLICATE COMPANY CLUSTERS

### Cluster 1 — acme-corp.com

| Alias       | industry    | employee_count | hq_country |
|-------------|-------------|----------------|------------|
| C-0A092931  | Technology  | 500            | US         |
| C-0A092932  | tech        | 510            | USA        |

Same domain. Employee count disagrees (500 vs 510). Industry disagree (Technology vs tech — cosmetic). Country disagree (US vs USA — cosmetic).
**Survivor: C-0A092931** (higher employee_count = 500? No, C-0A092932 has 510). Actually ZI has no row for acme-corp.com, so use the higher-confidence record. C-0A092932 has 510 employees and a fuller ZI-style signal. However, neither has a ZI row to arbitrate.
**Recommendation: Survivor = C-0A092931** (entered first; keep the lower alias number, merge 510 emp count from C-0A092932 since it's higher). Industry → "Technology". hq_country → "US".

### Cluster 2 — globex.io

| Alias       | industry    | employee_count | hq_country |
|-------------|-------------|----------------|------------|
| C-0A092933  | SaaS        | 200            | US         |
| C-0A092934  | Technology  | 200            | US         |

Same domain, same employee count, same country. Only industry differs (SaaS vs Technology).
**Survivor: C-0A092933** (entered first; keep "SaaS" as more specific).
**Recommendation: Merge, drop C-0A092934.**

### No other shared domains found. No name-variant clusters detected across the remaining 30 company aliases.

---

## 3. INVALID EMAILS

Four contacts have emails missing the domain portion (truncated after @):

| contact_key | email      | company_alias |
|-------------|------------|---------------|
| CT-0010     | user0@     | C-66D1FC      |
| CT-0080     | user0@     | C-92D97D      |
| CT-0081     | user1@     | C-92D97D      |
| CT-0192     | user2@     | C-425E2A      |

Fix: append the company domain (e.g., user0@66d1fc.com for CT-0010) — but confirm with source data first; these may be test/placeholder records.

---

## 4. DOMAIN MISMATCHES (email domain vs. company domain)

| contact_key | email                | company_alias | company domain | mismatch               |
|-------------|----------------------|---------------|----------------|------------------------|
| CT-0011     | user1@other-domain.com | C-66D1FC    | 66d1fc.com     | other-domain.com ≠ 66d1fc.com |

This is the only mismatch. One contact in C-66D1FC has an email from an entirely different domain. Verify whether this contact actually belongs to C-66D1FC or is a separate entity.

---

## 5. ENRICHMENT FILL — MISSING COMPANY FIELDS

Only populated where ZoomInfo has a matching domain row AND the CRM field is blank.

### employee_count — 8 fills available

| Alias       | CRM (blank) | ZI value | Fill? |
|-------------|-------------|----------|-------|
| C-EC3025    | blank       | 400      | YES   |
| C-96039F    | blank       | 400      | YES   |
| C-44EA29    | blank       | 400      | YES   |
| C-D04904    | blank       | 400      | YES   |
| C-B23205    | blank       | 400      | YES   |
| C-60C75F    | blank       | 400      | YES   |
| C-7BBDFA    | blank       | 400      | YES   |
| C-50D386    | blank       | 400      | YES   |
| C-93C8BF    | blank       | — (no ZI row) | NO |

### hq_country — 1 fill available, 6 unfillable

| Alias       | CRM (blank) | ZI value      | Fill? |
|-------------|-------------|---------------|-------|
| C-60C75F    | blank       | United States | YES   |
| C-2D1F1B    | blank       | blank (ZI also empty) | NO |
| C-D73B89    | blank       | blank (ZI also empty) | NO |
| C-44EA29    | blank       | blank (ZI also empty) | NO |
| C-D04904    | blank       | blank (ZI also empty) | NO |
| C-2C60E5    | blank       | blank (ZI also empty) | NO |
| C-EE9FFB    | blank       | — (no ZI row) | NO |

---

## 6. CRM vs. ZOOMINFO DISAGREEMENTS

### Industry disagreements (CRM value ≠ ZI value)

All share the same pattern: CRM uses a generic label, ZI uses "Computer Software."

| Alias       | CRM industry | ZI industry       | Recommend |
|-------------|--------------|-------------------|-----------|
| C-66D1FC    | tech         | Computer Software | ZI (more specific) |
| C-EC3025    | Technology   | Computer Software | ZI        |
| C-44EA29    | tech         | Computer Software | ZI        |
| C-92D97D    | Technology   | Computer Software | ZI        |
| C-D04904    | Technology   | Computer Software | ZI        |
| C-77A95A    | Technology   | Computer Software | ZI        |
| C-AA8DDA    | Technology   | Computer Software | ZI        |
| C-B25F40    | Technology   | Computer Software | ZI        |
| C-60C75F    | tech         | Computer Software | ZI        |
| C-425E2A    | Tech (trailing space) | Computer Software | ZI + trim trailing space |

**10 disagreements.** Recommend standardizing to ZI "Computer Software" for all, or creating a controlled vocabulary.

### Industry normalization (cosmetic, same meaning)

CRM uses "tech", "Tech " (trailing space), and "Technology" interchangeably. ZI calls them all "Computer Software." Similarly "health care" (CRM) matches "health care" (ZI). These are not disagreements per se, but the trailing space in "Tech " for C-425E2A, C-BA969B, C-93C8BF, C-C9BB20 is a data-cleaning issue.

### employee_count disagreements

None. Where both CRM and ZI have values, they agree exactly (e.g., 900, 1500, 50, 340, 120, 400 all match).

### hq_country disagreements

None where both have values. Disagreements are cosmetic: CRM uses "US", "USA", and "United States" interchangeably; ZI uses "United States" and "UK". Recommend normalizing to ISO 3166-1 alpha-2 (US, CA, GB).

---

## 7. TOP 10 FIXES BY SEVERITY (pipeline $ unavailable)

Ranked by number of affected records and data-quality risk. Without deals.csv, dollar amounts cannot be assigned.

| # | Fix | Records affected | Why critical |
|---|-----|-----------------|--------------|
| 1 | **Provide deals.csv** | All deals | Cannot audit owner, stage, amount, close_date, why_buys, or rank anything by pipeline. This is the #1 gap. |
| 2 | **Merge duplicate cluster: acme-corp.com** (C-0A092931 ↔ C-0A092932) | 2 companies + any linked contacts/deals | Shared domain = same legal entity. If deals exist against both, pipeline is double-counted. Survivor: C-0A092931; merge emp_count=510, industry=Technology, hq_country=US. |
| 3 | **Merge duplicate cluster: globex.io** (C-0A092933 ↔ C-0A092934) | 2 companies + any linked contacts/deals | Same risk as above. Survivor: C-0A092933; merge industry=SaaS. |
| 4 | **Fix 4 truncated emails** (CT-0010, CT-0080, CT-0081, CT-0192) | 4 contacts | Emails with no domain are undeliverable. Append company domain or remove record. |
| 5 | **Resolve domain mismatch** CT-0011 (user1@other-domain.com in C-66D1FC) | 1 contact | Contact may belong to a different company or be a personal email. Verify ownership. |
| 6 | **Fill 8 blank employee_count fields** from ZoomInfo | 8 companies (C-EC3025, C-96039F, C-44EA29, C-D04904, C-B23205, C-60C75F, C-7BBDFA, C-50D386) | All 8 confirmed at 400 employees via ZI. Straightforward fill. |
| 7 | **Fill C-60C75F hq_country** from ZoomInfo ("United States") | 1 company | Only hq_country fill available from ZI; the other 6 blanks have no ZI source. |
| 8 | **Standardize industry taxonomy** — collapse "tech"/"Tech "/"Technology" → "Computer Software" (or chosen label) | 10 companies | Inconsistent industry tags break reporting, segmentation, and territory assignment. |
| 9 | **Fill 12 blank contact titles** and **15 blank personas** from source system | 27 contact fields across 15-18 contacts | Persona is required for deal-threading analysis. Without it, champion/economic buyer mapping fails. No ZI enrichment available for contacts — source from CRM activity logs or manual review. |
| 10 | **Normalize hq_country** to ISO codes (US/USA/United States → US; UK → GB) and trim trailing whitespace on industry ("Tech " → "Tech") | ~34 companies | Cosmetic but causes downstream filter/group-by errors in BI tools. |

---

## SUMMARY STATISTICS

| Metric | Value |
|--------|-------|
| Total companies | 34 (2 duplicate pairs → 32 unique entities) |
| Total contacts | 52 |
| Companies missing employee_count | 9 (8 fillable from ZI, 1 not) |
| Companies missing hq_country | 7 (1 fillable from ZI, 6 not) |
| Contacts missing title | 12 (23.1%) |
| Contacts missing persona | 15 (28.8%) |
| Invalid emails | 4 (7.7%) |
| Domain mismatches | 1 (CT-0011) |
| Duplicate company clusters | 2 (acme-corp.com, globex.io) |
| Industry disagreements CRM↔ZI | 10 |
| Deals file | NOT PROVIDED |

**Overall company field completeness (5 fields): 153/170 = 90.0%**
**Overall contact field completeness (6 fields, counting invalid emails as populated): 289/312 = 92.6%**
**Overall contact field completeness (6 fields, excluding invalid emails): 285/312 = 91.3%**

Here's the analysis.

## Line-by-line classification

**1. SCIM user provisioning — Deal-EC3025, $ unknown**
Prospect quote: "We need SCIM user provisioning — our security team will not approve any tool that requires manual account management."
Product docs: SCIM is explicitly listed as NOT currently supported.
Classification: REAL GAP. SCIM is absent from the product entirely. This is not gated to any tier — it simply does not exist. A security team making it a hard requirement means the product cannot meet the buyer's procurement criteria at any price.

**2. ADP Workforce Now integration — Deal-D0D6B5, $ unknown**
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."
Product docs: Supported HRIS integrations are Workday, BambooHR, Gusto, Rippling. ADP is explicitly listed as NOT supported.
Classification: REAL GAP. ADP Workforce Now is one of the largest payroll/HRIS platforms in the US mid-market. It is absent from the supported list entirely. No tier or upgrade path addresses it. Prospect called it a dealbreaker.

**3. Custom report combining recognition frequency with turnover — Deal-CFE7F4, $ unknown**
Prospect quote: "I tried to build a custom report combining recognition frequency with turnover and couldn't — is that possible on our current plan?"
Product docs: Custom report builder is Enterprise-only. The prospect is presumably not on Enterprise.
Classification: PLAN GATE, not a product gap. The feature exists on a higher tier. The rep's response (offer upgrade path) is appropriate. This is a pricing/packaging question, not a missing capability.

**4. Slack integration low adoption / no manager training — Deal-84DBA6, $ unknown**
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."
Product docs: Slack integration exists on all plans. The gap described is adoption and enablement.
Classification: ROLLOUT / ENABLEMENT ISSUE. The product capability exists. The problem is lack of training for managers. The rep's offer to run a manager enablement session is the right fix.

**5. Native mobile app for hourly workers — Deal-36C33F, $ unknown**
Prospect quote: "Good to know. The web version should be fine for our office staff for now."
This was raised by the rep (Alex Franklin), not the prospect. The prospect explicitly accepted the workaround.
Classification: NOT A PROSPECT-RAISED GAP. The rep disclosed it proactively. The prospect did not object and accepted the web version. Per instructions, rep language does not count as prospect voice. Not eligible for the summary.

---

## Summary of true product gaps

| # | Gap | Deal | Prospect role | Quote |
|---|---|---|---|---|
| 1 | SCIM user provisioning missing entirely | Deal-EC3025 | IT Security Lead | "We need SCIM user provisioning — our security team will not approve any tool that requires manual account management." |
| 2 | ADP Workforce Now integration missing entirely | Deal-D0D6B5 | HRIS Manager | "Our payroll runs on ADP Workforce Now and I don't see ADP anywhere in your integration list — that's a dealbreaker for us." |

show the model's full answer

## Alex Franklin — Last 10 Calls: Sales Pattern Analysis

---

### WHAT HE LEADS WITH (MINUTES 0-5)

8 of 10 calls open identically with the 400-person retailer 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."

The two exceptions:
- 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 AND HOW HE HANDLES THEM

**1. Budget locked (4 of 10 calls — TT-001, TT-003, TT-006, TT-010)**

Prospect: "Honestly, budget is locked until next fiscal year — I can't add a new line item right now."

Rep response (consistent across all four):
> "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. Revisit next quarter (3 of 10 calls — TT-002, TT-005, TT-008)**

Prospect: "This is good, but can we revisit it next quarter? Open enrollment starts in October and we're underwater."

Rep response (consistent across all three):
> "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 / spreadsheet (3 of 10 calls — TT-004, TT-007, TT-009)**

Prospect: "We already do recognition with a spreadsheet and quarterly gift cards — why would we change?"

Rep response (consistent across all three):
> "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."

---

### NEXT-STEP AGREEMENT RATE

A concrete, date/time-locked next step was agreed in 7 of 10 calls = **70%**.

All seven were identical: "Yes, Thursday at 2pm works — send the invite and I'll bring our HRIS manager."

Three calls with NO agreed next step:
- TT-004 (Deal-403845): Rep said "Understood — I'll leave it with you." (prospect deferred to budget committee)
- TT-007 (Deal-EDC141): Rep said "Fair enough." (prospect said no urgency)
- TT-010 (Deal-84DBA6): Rep said "Understood, thanks for the candor." (prospect said wait for committee)

---

### COMPETITORS RAISED BY PROSPECTS

Two, from two different calls:

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

Note: Workhuman was mentioned by the rep (not the prospect) in TT-005, Deal-C61CF7 at minute 2.

---

### COACHING NOTES

**1. De-risk the opener.** Eight of ten calls open with the exact same verbatim 400-person retailer story. Pattern recognition is a liability — a prospect on a mutual-references call or a second meeting will notice the script. Tie the opening to something specific to each account (their industry, their stated pain from the invite call) rather than defaulting to the same case study every time.

**2. Follow up on committee deferrals.** In two of the three calls with no next step (TT-004, TT-010), the prospect names a committee as the decision-maker. Both times the rep accepts "I'll leave it with you" without asking to join the committee meeting, send a one-pager, or schedule a follow-up date. This turns a warm lead into a dead zone. Every committee deferral should produce at least one concrete asset delivery or calendar commitment.

REDEMPTIONS -- August 2026 (last completed month)
====================================================

Redemption count:  48
Total spend:       $3,536.00
Unique redeemers:  46
Redemptions per redeemer: 1.04 (48 / 46)

Arithmetic: 2 redeemers each made 2 redemptions --
  U-0D807F (C-0B511454): $50.00 Tremendous (AU) + $352.00 custom (AU)
  U-4A0FE6 (C-0F5E249E): $200.00 Tremendous (US) + $75.00 Snappy (US)

PROVIDER MIX (% of $3,536.00 spend)
----------------------------------------------------
  Tremendous  $1,145.00   32.4%
  custom      $1,057.00   29.9%
  Snappy      $  834.00   23.6%
  TangoCard   $  500.00   14.1%
----------------------------------------------------
  Total       $3,536.00  100.0%

TOP 5 COUNTRIES BY REDEMPTION COUNT
----------------------------------------------------
  US   31
  CA    7
  GB    2
  SG    2
  AU    2
----------------------------------------------------

Notes:
- CA (7 redemptions) ranks second by count but has 0% of custom spend (custom redemptions from CA total $254.00 via C-0BBE3E60, which is CA, so CA does carry custom). CA's redemptions include TangoCard ($250 across 5 redemptions), Snappy ($47), and custom ($254).
- Tremendous leads provider spend despite TangoCard having the most individual redemptions (11 vs. Tremendous's 23), because Tremendous carries higher-value redemptions ($200, $150, $100).
- All four providers were active in August.

Here is the synthesis. 80 tickets, 24 unique accounts, $284,800 total ARR at risk. Ranked by ARR exposure, not volume.

=========================================================================
QUARTER SUPPORT TICKET THEME ANALYSIS (Jun 1 - Aug 29, 2026)
=========================================================================

THEME 1: HRIS Sync & Provisioning Failures
  Rank: #1 by ARR exposure
  Count: 12  |  Share: 15.0%  |  Distinct accounts: 3  |  ARR: $114,000
  Pattern: BROAD (multi-account, high-ARR concentration)
  Accounts:
    C-0DDFC9A7 ($48,000) — 3 tickets
    C-0B2213A9 ($36,000) — 7 tickets (heaviest repeater in this theme)
    C-0F6C0F34 ($30,000) — 2 tickets
  Sample ticket IDs: IC-460059, IC-460060
  What the text says: New hires are silently dropped from HRIS syncs; provisioning
    logs show no errors. Across three enterprise accounts totaling $114K ARR, this
    is the highest-stakes failure mode — HR cannot onboard employees into the
    platform and the system provides no diagnostic signal.
  Recommendation: Treat as P1. Instrument provisioning pipeline with heartbeat
    monitoring and alert on zero-new-hire diff vs. HRIS export within 48 hrs.

------------------------------------------------------------------------

THEME 2: Billing & Invoice Errors
  Rank: #2 by ARR exposure
  Count: 16  |  Share: 20.0%  |  Distinct accounts: 1  |  ARR: $52,000
  Pattern: SINGLE-ACCOUNT CONCENTRATION (not noise — highest per-account ticket load)
  Account:
    C-0E9C27D1 ($52,000) — all 16 tickets
  Sample ticket IDs: IC-460071, IC-460069
  What the text says: Repeated seat-count overcharges ("charged for 200 seats but
    we license 150"), wrong-tier renewal pricing, and an unresolved invoice
    discrepancy across at least three billing cycles. The same account filed 16
    tickets over June–August, escalating from "feedback" to "urgent."
  Recommendation: Pause this account's next invoice, assign a billing operations
    owner to audit seat counts vs. contract, and issue credit. This single account
    alone is 20% of all tickets this quarter.

------------------------------------------------------------------------

THEME 3: Redemption & Checkout Failures
  Rank: #3 by ARR exposure
  Count: 13  |  Share: 16.2%  |  Distinct accounts: 5  |  ARR: $48,900
  Pattern: BROAD (5 accounts, $8.7K–$11K range)
  Accounts:
    C-14264ABD ($11,000) — 3 tickets
    C-0B827671 ($10,700) — 4 tickets
    C-0FCCD2DF ($9,600) — 1 ticket
    C-0CEF69FD ($8,900) — 3 tickets
    C-0F876796 ($8,700) — 2 tickets
  Sample ticket IDs: IC-460025, IC-460030
  What the text says: The checkout UI spins indefinitely, redemption fails at the
    final step, and gift card emails/code never arrive. Employees see their points
    deducted but receive nothing. This is the core value-exchange moment breaking
    down for mid-market accounts.
  Recommendation: Instrument checkout timeout/error logging end-to-end. Prioritize
    a retry-or-reverse path so points are returned within minutes of a failed
    redemption, not on manual CS intervention.

------------------------------------------------------------------------

THEME 4: Gift Card Error + Points Deduction
  Rank: #4 by ARR exposure
  Count: 5  |  Share: 6.2%  |  Distinct accounts: 4  |  ARR: $38,200
  Pattern: BROAD (4 accounts)
  Accounts:
    C-0B0F1BAB ($10,300) — 1 ticket
    C-0FCCD2DF ($9,600) — 2 tickets
    C-0D9CA315 ($9,600) — 1 ticket
    C-0F876796 ($8,700) — 1 ticket
  Sample ticket IDs: IC-460024, IC-460023
  What the text says: Gift card order errors out, but points are deducted anyway.
    This is distinct from Theme 3 (which is UX/timeout failures) — here the
    transaction partially commits: the user loses points without receiving value.
    This is a trust and financial-integrity issue.
  Recommendation: Wrap gift-card issuance in a transactional rollback: if the
    card order fails, reverse the point deduction atomically. Escalate to finance
    for manual point credits on all historical occurrences.

------------------------------------------------------------------------

THEME 5: Points Not Posting / Balance Not Updating
  Rank: #5 by ARR exposure
  Count: 20  |  Share: 25.0%  |  Distinct accounts: 9  |  ARR: $31,100
  Pattern: BROAD (9 accounts, all under $5K ARR — widest spread)
  Accounts:
    C-0BF20542 ($4,500) — 2 tickets
    C-0D0B047C ($4,500) — 2 tickets
    C-0D6CC8E3 ($4,200) — 3 tickets
    C-0D3278C7 ($3,500) — 3 tickets
    C-0D284E42 ($3,400) — 3 tickets
    C-21FEBCBB ($2,900) — 1 ticket
    C-0B2895EF ($2,900) — 1 ticket
    C-0BE96399 ($2,700) — 3 tickets
    C-0DD0626C ($2,500) — 2 tickets
  Sample ticket IDs: IC-460004, IC-460001
  What the text says: Recognitions appear delivered but points never arrive in the
    recipient's balance — individually or across whole teams, sometimes days late.
    The highest-volume theme (25% of all tickets) but spread across nine small
    accounts ($2.5K–$4.5K each). This is the broadest breadth signal: the points
    ledger has a systemic latency or drop issue that hits many accounts at the
    lower end of the book.
  Recommendation: Audit the recognition-to-balance write path for async failures
    or queue backlogs. The breadth (9 accounts) suggests a platform-level bug, not
    per-account config. Flag for engineering regression review.

------------------------------------------------------------------------

THEME 6: Slack Integration Failure
  Rank: #6 by ARR exposure
  Count: 14  |  Share: 17.5%  |  Distinct accounts: 4  |  ARR: $18,900
  Pattern: BROAD (4 accounts)
  Accounts:
    C-10A56B0F ($5,400) — 4 tickets
    C-8C2E8F00 ($5,200) — 1 ticket
    C-0B843542 ($4,400) — 3 tickets
    C-0BA71F12 ($3,900) — 6 tickets (heaviest repeater)
  Sample ticket IDs: IC-460047, IC-460046
  What the text says: Recognitions stop posting to Slack channels; the sync toggle
    resets itself; re-authentication doesn't stick; slash commands error out for
    entire teams. The integration is functionally broken for four accounts across
    multiple failure modes (sync, auth, slash commands).
  Recommendation: Audit Slack OAuth token refresh and webhook registration for
    these four accounts. The "toggle resets itself" symptom points to a
    server-side config not persisting.

=========================================================================
CROSS-THEME SUMMARY
=========================================================================
Total tickets:  80
Unique accounts: 24
Total ARR at risk: $284,800 (sum of 24 unique account ARR values)

Broad patterns (multi-account, systemic):
  1. HRIS provisioning — 3 accounts, $114K ARR
  2. Redemption/checkout — 5 accounts, $48.9K ARR
  3. Gift card point deduction — 4 accounts, $38.2K ARR
  4. Points not posting — 9 accounts, $31.1K ARR
  5. Slack integration — 4 accounts, $18.9K ARR

Single-account concentration (not noise — high severity):
  6. Billing & invoice — 1 account (C-0E9C27D1), $52K ARR, 16 tickets

Top 3 action items by ARR impact:
  1. HRIS provisioning: $114K at risk across 3 enterprise accounts; silent
     failures with no diagnostic signal — instrument and alert.
  2. C-0E9C27D1 billing: $52K account generating 20% of all tickets this
     quarter; pause next invoice, audit, and credit.
  3. Redemption/checkout: $48.9K across 5 accounts; add transactional
     rollback so failed redemptions return points automatically.

## Q3-2026 Weekly Marketing Goals Update

Quarter: Q3-2026 | Days elapsed: 66 of 92 (71.7%)

```
METRIC              QTD ACTUAL   TARGET    DELTA        % OF TARGET   PACE
─────────────────────────────────────────────────────────────────────────────
SQMs                    230        300      -70          76.7%        AHEAD
SQOs                     84        120      -36          70.0%        BEHIND
DS2s                     40         75      -35          53.3%        BEHIND
CL MIA Rate            20.0%      10.0%    +10.0pp         —          BEHIND
Same-Qtr Closes          10         20      -10          50.0%        BEHIND
Active Pipeline       $3.00M      $4.00M  -$1.00M        75.0%        AHEAD
```

**Pace method:** QTD actual ÷ full-quarter target vs. 66 ÷ 92 (71.7% of quarter elapsed). At or above → on/ahead; below → behind.

**Arithmetic details:**
- SQMs: 230 / 300 = 76.7% ≥ 71.7% → ahead by ~5pp of target pace
- SQOs: 84 / 120 = 70.0% < 71.7% → behind by ~1.7pp
- DS2s: 40 / 75 = 53.3% < 71.7% → behind by ~18.4pp (most at-risk)
- CL MIA rate: 5 / 25 = 20.0% vs 10% cap → double the threshold; lower is better, so this is running badly behind
- Same-quarter closes: 10 / 20 = 50.0% < 71.7% → behind by ~21.7pp (also significantly at-risk)
- Pipeline: $3.00M / $4.00M = 75.0% ≥ 71.7% → ahead by ~3.3pp

**What moved this week:**

Top-of-funnel remains healthy — SQMs are tracking ahead of pace at 76.7% of target with 26 days left, and active pipeline coverage cleared 75% of goal, so inbound volume and deal accumulation are holding up. The conversion funnel is where pressure is building: SQOs sit at 70.0%, just below pace, signaling that MQL-to-SQO qualification is slightly lagging despite the SQM surplus. The two biggest red flags are DS2s at only 53.3% of target (requiring ~35 more in 26 days — roughly 1.3 per day vs. the 0.72/day we've averaged) and same-quarter closes at 50.0%, which means we need 10 more closes in the remaining 26 days versus the 10 we managed in the first 66 — a 2.6× acceleration that will be difficult without pulling forward late-stage deals. Closed-lost MIA rate at 20% is double the 10% ceiling, meaning 1 in 5 lost deals are disappearing without a trace — this signals a process gap in lost-deal follow-up that is inflating the loss count and masking the real closeable pipeline.

**Risk summary:** 3 of 6 metrics are behind pace. DS2s and same-quarter closes are materially behind and will require intervention (deal acceleration, close-date pulls, or forecast revision) to hit quarter. SQMs and pipeline give some buffer, but the conversion gap from SQMs → SQOs → DS2s → closes needs to tighten in the final 4 weeks.

Here's your weekly GTM digest — all numbers sourced from the extracts, no invented facts.

---

**GTM Weekly Digest — Week of Aug 31, 2026**

Marketing put up 46 SQMs this week against a target of 52, coming in at 88.5% of goal. The webinar channel was the standout, driving 18 of those 46 SQMs — roughly 39% of total weekly volume from a single channel. Paid search held steady on cost efficiency at $150 per SQM, keeping that engine predictable as we look at scaling spend. The gap to target is 6 SQMs worth addressing next week.

Sales converted 14 SQOs and opened 9 DS2 meetings, building solid momentum deeper in the funnel. New pipeline creation hit $310,000 for the week — a strong top-of-funnel to mid-funnel conversion story. Three deals closed same-quarter, reinforcing that the pipeline is moving through to revenue and not just sitting in stage. The 14 SQOs and 9 DS2s together signal healthy qualification discipline.

CS saved 2 renewals this week, keeping committed ARR on the books. Team NPS moved to 61, a healthy indicator that customer sentiment remains strong heading into Q4. Three open red-flag accounts carry into next week — those are the ones to get ahead of before they become renewal risks. The renewal saves plus NPS momentum show the team is balancing firefighting with proactive relationship work.

PLG added 412 new signups with activation at 31%, meaning roughly 128 accounts moved beyond first touch into meaningful product engagement. Thirty-eight companies hit the aha moment of 10 recognition gives, which is our strongest predictor of long-term retention. The gap between 412 signups and 38 aha-moment companies (about 9.2%) tells us there's still room to improve the onboarding path from signup to repeated recognition behavior — that's the leverage point for next week.

partner-digest-sectionPASS 1.00

? The Question

Write the partner digest for the period. Every partner in the roster appears once: active plays get status with numbers, quiet partners get one line. Partner-sourced pipeline count and amount must match the deal data. Nothing omitted, nothing added.

cost $0.0005 · 9s · in 1,240 / out 960 tok

✓ all_partners✓ pipeline_amount✓ quiet_one_line

✓ Correct Answer (ground truth)

roster: partner_name=Apex Rewards Co; status=active | partner_name=HRCloud Partners; status=active | partner_name=CultureBridge; status=active | partner_name=WorkWell Group; status=active | partner_name=Recogniq; status=quiet | partner_name=KudosWave; status=quiet … (+2 more)
per_partner_pipeline: {"Apex Rewards Co": {"count": 2, "amount": 275000}, "HRCloud Partners": {"count": 1, "amount": 140000}, "CultureBridge": {"count": 2, "amount": 135000}}
partner_sourced_pipeline: count=5; amount=550000
quiet_partners: Recogniq, KudosWave, PeopleFirst Advisors, TotalPerk
active_no_deals: WorkWell Group
rule: every roster partner named exactly once; quiet partners get one line; no partners outside roster.
graded checks: all_partners · pipeline_amount · quiet_one_line

Model's actual answer

show the model's full answer

PARTNER DIGEST — 2026-08-24 to 2026-09-04

============================================================
ACTIVE PARTNERS
============================================================

APEX REWARDS CO
  Status: Active
  Activities: Co-webinar locked for 09-15. Two sourced opps confirmed with UTM Source = Partner.
  Deals: 2
    Deal-DDAAF2 — $180,000
    Deal-2CF33E — $95,000
  Partner-sourced pipeline: 2 deals / $275,000

HRCloud PARTNERS
  Status: Active
  Activities: Integration referral closed security review; opp moved to DS2. One sourced opp logged.
  Deals: 1
    Deal-F1CDA5 — $140,000
  Partner-sourced pipeline: 1 deal / $140,000

CULTUREBRIDGE
  Status: Active
  Activities: Lunch-and-learn produced two sourced opps, both early stage.
  Deals: 2
    Deal-096E1D — $60,000
    Deal-067213 — $75,000
  Partner-sourced pipeline: 2 deals / $135,000

WORKWELL GROUP
  Status: Active
  Activities: Wants to restart joint playbook in Q4. Planning call booked for 09-09. No sourced deals this period.
  Deals: 0
  Partner-sourced pipeline: 0 deals / $0

============================================================
QUIET PARTNERS
============================================================

RECOGNIQ — No activity, no sourced deals.
KUDOSWAVE — No activity, no sourced deals.
PEOPLEFIRST ADVISORS — No activity, no sourced deals.
TOTALPERK — No activity, no sourced deals.

============================================================
ROSTER TOTALS
============================================================
  Active partners: 4 of 8
  Quiet partners: 4 of 8
  Total partner-sourced deals: 5
  Total partner-sourced pipeline: $550,000
    Apex Rewards Co:   2 deals / $275,000
    HRCloud Partners:  1 deal  / $140,000
    CultureBridge:     2 deals / $135,000
    WorkWell Group:    0 deals / $0

rfp-answer-from-policyPASS 1.00

? The Question

Answer the 10 questionnaire items from the policy excerpts only. Cite the excerpt id for every answer. Where the excerpts do not answer the question, mark it unanswerable and say what document would; do not guess. Tone: vendor response, direct.

cost $0.0004 · 7s · in 1,197 / out 797 tok

✓ answered_count✓ unanswerable_flagged✓ citations✓ no_guess

✓ Correct Answer (ground truth)

answered_count: 7
answer_map: {"Q1": ["P1"], "Q2": ["P1"], "Q3": ["P2"], "Q4": ["P3"], "Q5": ["P4"], "Q6": ["P5"], "Q7": ["P6"]}
unanswerable: Q8, Q9, Q10
valid_citation_ids: P1, P2, P3, P4, P5, P6, P7, P8
rule: unanswerable items must be flagged and the document that would answer them named; do not guess.
graded checks: answered_count · unanswerable_flagged · citations · no_guess

Model's actual answer

show the model's full answer

Below are the 10 questionnaire responses. Each answer cites the policy excerpt(s) used. Three items are unanswerable from the provided excerpts.

---

Q1 — Encryption at rest
Yes. 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
Yes. Bonusly maintains a SOC 2 Type II report, renewed annually. The report is available to prospects under NDA. [P2]

Q4 — Data retention after contract 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
A current list of subprocessors is maintained 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 — Production 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 excerpt addresses ISO 27001. This would be answered by Bonusly's compliance certifications document or trust.bonusly.com certifications page.

Q9 — Contractual uptime SLA percentage
Unanswerable from the provided excerpts. No excerpt specifies an uptime SLA. This would be answered by the Master Service Agreement (MSA) or Service Level Agreement (SLA) exhibit.

show the model's full answer

NDA TRIAGE
==========

NDA-1 — [PARTY A] / Bonusly        → GREEN
Standard mutual NDA. Mutual confidentiality, reasonable 2-year term, 3-year
survival, all five customary carve-outs present (§3(a)–(e)), Delaware governing
law, no non-solicits, no non-competes, explicit no-license and no-exclusivity
language. Nothing outside standard template.

NDA-2 — [PARTY B] / Bonusly        → YELLOW (counsel review)
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." (§4) — 18-month post-term tail is aggressive and can restrict
hiring; counsel should confirm employee-contact scope and negotiate down or
limit to named individuals.

NDA-3 — [PARTY C] / Bonusly        → RED (full legal review)
Three distinct red flags in a single agreement:

  1. Embedded non-compete — "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."
     (§2) — Three-year blanket non-compete is unreasonably broad and likely
     unenforceable in many jurisdictions; in-house and outside counsel must
     assess.

  2. No carve-outs stated — "No confidentiality carve-outs are stated in this
     Agreement." (§4) — Absence of standard exceptions (public domain, prior
     knowledge, independent development, legal compulsion) creates overbroad
     exposure.

  3. One-way obligation — Confidentiality runs only toward [PARTY C], not
     mutual, shifting all risk to Bonusly. Combined with Irish governing law
     (§3), enforcement of carve-outless, one-way terms in a foreign court
     compounds legal risk.

Bottom line: Do not sign NDA-3 without material redline.