openai/gpt-5.6-luna-pro

Definitions:
- DS2+ = deals in DS2, DS3, DS4, or DS5.
- Why-buys compliant = at least 15 characters, not a placeholder; LONG(n) counts as compliant.
- Regression = any earlier-stage timestamp later than a later-stage timestamp.
- Missing DS1 = blank t_ds1.

Why-buys hygiene:
- Overall: 96 of 118 DS2+ deals non-compliant = 96 ÷ 118 = 81.4%.
- Bryce Harmon: 14 of 17 = 14 ÷ 17 = 82.4%.
- Dana Mercer: 19 of 23 = 19 ÷ 23 = 82.6%.
- Alex Franklin: 44 of 56 = 44 ÷ 56 = 78.6%.
- Cole Ingram: 18 of 21 = 18 ÷ 21 = 85.7%.
- Farid Osman: 1 of 1 = 1 ÷ 1 = 100.0%.

Other hygiene:
- Deals with no DS1 timestamp: 0.
- Deals with regressed stage timestamps: 0.

Process fixes:
1. Make substantive why-buys mandatory before a deal can enter DS2; reject blanks, placeholders, and values under 15 characters.
2. Require t_ds1 when a deal is created or before any stage advancement; add a validation report for existing missing timestamps.
3. Enforce chronological stage-entry timestamps with a validation rule that blocks regressions and flags corrections for review.

Resolved deals: 155

Unmatched owner IDs: None. Every owner ID in the open-deals extract matched an owner in owners.csv.

Deals assigned to archived/deactivated owners: None.
- Archived owners in owners.csv — 1520255671: Gavin Porter; 77260721: Hugo Lindqvist — do not appear in the open-deals extract.

Total pipeline by resolved owner:

- Bryce Harmon (owner_id 119337721): 35 deals  
  $24,000 + $19,656 + $13,500 + $7,000 + $2,520 + $240,000 + $99,000 + $72,000 + $70,000 + $63,600 + $45,000 + $1 + $21,000 + $23,400 + $13,680 + $5,502 + $8,160 + $1 + $11,400 + $1 + $36,000 + $31,500 + $6,000 + $10,800 + $30,275 + $17,400 + $12,600 + $18,000 + $37,440 + $18,828 + $2,880 + $36,000 + $20,880 + $10,920 + $25,200 = $1,054,144.00

- Alex Franklin (owner_id 84342457): 67 deals  
  Sum of 67 deal amounts = $624,310.00

- Dana Mercer (owner_id 83155923): 23 deals  
  Sum of 23 deal amounts = $339,275.00

- Cole Ingram (owner_id 83155924): 22 deals  
  Sum of 22 deal amounts = $288,161.43

- Farid Osman (owner_id 716654662): 7 deals  
  $1,249 + $1 + $1 + $1 + $2,880 + $1 + $1 = $4,134.00

- Elena Sinclair (owner_id 701163055): 1 deal  
  Deal-57FF13: $2,100 = $2,100.00

(a) Orphans: 30 Gong rows

Arithmetic:
- Total Gong rows: 67
- Gong rows matching a `deal_id` in `deals_open`: 37
- Orphans: 67 − 37 = 30

Sample orphan aliases:
- Deal-3F86A0
- Deal-9897FA
- Deal-422BA6
- Deal-344163
- Deal-B038F0

(b) Duplicate conversation keys: 0 rows

For every Gong row, `calls_90d` equals `distinct_conversation_keys`; therefore, no duplicate conversation keys are indicated.

(c) Open deals at DS3 or later with at least one logged call: 25 of 74, or 33.78%

Arithmetic:
- Open deals at DS3 or later: 74
- Those with a matching Gong row: 25
- Share: 25 ÷ 74 = 33.78%

```sql
-- Chosen because this is the documented one-row-per-self-serve-company source
-- containing M1 users, gives, and redemptions; stale and unpopulated alternatives
-- are intentionally not used.
SELECT
    DATE_TRUNC('MONTH', FIRST_SUB_PAYMENT_DATE) AS first_calendar_month_as_customer,
    M1_USERS AS unique_givers,
    M1_GIVES AS recognition_count,
    M1_REDEMPTIONS AS successful_redemption_count
-- Chosen because PRODUCTION.PLG.COMPANY_COHORT_SUMMARY is the cataloged source
-- for customer cohort metrics and already provides the M1 measures.
FROM PRODUCTION.PLG.COMPANY_COHORT_SUMMARY
WHERE FIRST_SUB_PAYMENT_DATE IS NOT NULL;
```

CRM completeness audit

Deals

deals.csv was not provided, so deal completeness and pipeline amount at stake cannot be calculated.

| Required field | Completeness |
|---|---:|
| Owner | Not available |
| Stage | Not available |
| Amount | Not available |
| Close date | Not available |
| Why-buys | Not available |

Companies

34 company records.

| Field | Complete | Completeness |
|---|---:|---:|
| Industry | 34/34 | 100.0% |
| Employee count | 25/34 | 73.5% |
| HQ country | 30/34 | 88.2% |

Arithmetic:
- Employee count: 25 ÷ 34 × 100 = 73.5%
- HQ country: 30 ÷ 34 × 100 = 88.2%

Contacts

52 contact records.

| Field | Complete/valid | Completeness |
|---|---:|---:|
| Email populated | 52/52 | 100.0% |
| Email valid syntax | 48/52 | 92.3% |
| Title | 43/52 | 82.7% |
| Persona | 40/52 | 76.9% |

Arithmetic:
- Valid email syntax: 48 ÷ 52 × 100 = 92.3%
- Title: 43 ÷ 52 × 100 = 82.7%
- Persona: 40 ÷ 52 × 100 = 76.9%

Duplicate company clusters

1. Shared domain: acme-corp.com
- C-0A092931: Technology, 500 employees, US
- C-0A092932: tech, 510 employees, USA
- Proposed survivor: C-0A092931
- Reason: retain the first CRM alias; preserve C-0A092932’s employee count and normalized-value differences for review.
- Conflicts: industry and employee count differ; US and USA are country-label variants.

2. Shared domain: globex.io
- C-0A092933: SaaS, 200 employees, US
- C-0A092934: Technology, 200 employees, US
- Proposed survivor: C-0A092933
- Reason: retain the first CRM alias; preserve the conflicting industry value for review.
- Conflict: industry differs.

Invalid emails

- CT-0010 — C-66D1FC — user0@
- CT-0080 — C-92D97D — user0@
- CT-0081 — C-92D97D — user1@
- CT-0192 — C-425E2A — user2@

Domain mismatches

- CT-0011 — C-66D1FC
  - Email domain: other-domain.com
  - Company domain: 66d1fc.com

Enrichment fills

The following CRM fields are blank and have a matching nonblank value in zoominfo_enrichment.csv:

| Company | Field | CRM value | Enrichment value |
|---|---|---|---|
| C-EC3025 | employee_count | blank | 400 |
| C-96039F | employee_count | blank | 400 |
| C-44EA29 | employee_count | blank | 400 |
| C-D04904 | employee_count | blank | 400 |
| C-B23205 | employee_count | blank | 400 |
| C-60C75F | employee_count | blank | 400 |
| C-60C75F | hq_country | blank | United States |
| C-7BBDFA | employee_count | blank | 400 |
| C-50D386 | employee_count | blank | 400 |

Blank fields not filled because the matching enrichment value is also blank or no matching enrichment row exists:

- C-2D1F1B — hq_country; enrichment is blank.
- C-D73B89 — hq_country; enrichment is blank.
- C-44EA29 — hq_country; enrichment is blank.
- C-2C60E5 — hq_country; enrichment is blank.
- C-93C8BF — employee_count; no matching enrichment row.
- C-EE9FFB — hq_country; no matching enrichment row.
- C-C9BB20 — no matching enrichment row.
- C-0A092931 — no matching enrichment row.
- C-0A092932 — no matching enrichment row.
- C-0A092933 — no matching enrichment row.
- C-0A092934 — no matching enrichment row.

CRM/enrichment disagreements

Recommend ZoomInfo for substantive enrichment fields where it provides a value, subject to business verification. Standardize country labels rather than treating equivalent labels as substantive conflicts.

| Company | Field | CRM value | Enrichment value | Recommendation |
|---|---|---|---|---|
| C-66D1FC | industry | tech | Computer Software | Use ZoomInfo’s Computer Software, pending business confirmation. |
| C-66D1FC | hq_country | US | United States | Standardize to one country format; values are equivalent labels. |
| C-EC3025 | industry | Technology | Computer Software | Use ZoomInfo’s Computer Software, pending business confirmation. |
| C-EC3025 | hq_country | USA | United States | Standardize to one country format; values are equivalent labels. |
| C-44EA29 | industry | tech | Computer Software | Use ZoomInfo’s Computer Software, pending business confirmation. |
| C-D04904 | industry | Technology | Computer Software | Use ZoomInfo’s Computer Software, pending business confirmation. |
| C-60C75F | industry | tech | Computer Software | Use ZoomInfo’s Computer Software, pending business confirmation. |
| C-425E2A | industry | Tech | Computer Software | Use ZoomInfo’s Computer Software, pending business confirmation. |
| C-425E2A | hq_country | USA | United States | Standardize to one country format; values are equivalent labels. |

Recommended fixes

1. Repair the four invalid email values:
   - CT-0010
   - CT-0080
   - CT-0081
   - CT-0192
2. Investigate and correct the domain mismatch for CT-0011.
3. Fill C-EC3025 employee_count with 400.
4. Fill C-96039F employee_count with 400.
5. Fill C-44EA29 employee_count with 400.
6. Fill C-D04904 employee_count with 400.
7. Fill C-B23205 employee_count with 400.
8. Fill C-60C75F employee_count with 400 and hq_country with United States.
9. Fill C-7BBDFA employee_count with 400.
10. Fill C-50D386 employee_count with 400.
11. Resolve the acme-corp.com duplicate cluster.
12. Resolve the globex.io duplicate cluster.
13. Resolve industry conflicts between CRM and ZoomInfo.
14. Standardize country labels such as US, USA, and United States.
15. Obtain enrichment data for companies without matching enrichment rows.

Top 10 fixes by pipeline amount at stake

Cannot be calculated because deals.csv, including deal amounts, was not provided. No pipeline ranking or amount should be inferred from the company or contact extracts.

Classifications (90 deals)

| Deal alias | Primary category | Side |
|---|---|---|
| Deal-DB0AAC | timing | buyer |
| Deal-F7F635 | competitor | buyer |
| Deal-AC944F | no decision | unknown |
| Deal-214060 | no decision | unknown |
| Deal-91A056 | timing | buyer |
| Deal-29326C | timing | buyer |
| Deal-5DB9B0 | other | unknown |
| Deal-831B7B | timing | buyer |
| Deal-F97C37 | competitor | buyer |
| Deal-13E9CF | no decision | buyer |
| Deal-39E25C | timing | buyer |
| Deal-7ED004 | pricing | buyer |
| Deal-21B045 | no decision | unknown |
| Deal-B3ABED | timing | buyer |
| Deal-422BA6 | competitor | buyer |
| Deal-ED9AE7 | timing | buyer |
| Deal-988493 | no decision | unknown |
| Deal-381C8C | competitor | unknown |
| Deal-F308CA | no decision | unknown |
| Deal-F1E8A6 | competitor | unknown |
| Deal-B6AC09 | timing | buyer |
| Deal-70F704 | no decision | unknown |
| Deal-E6E80A | timing | buyer |
| Deal-B038F0 | timing | buyer |
| Deal-4664E1 | no decision | unknown |
| Deal-175756 | timing | buyer |
| Deal-E74A73 | no decision | buyer |
| Deal-DDAB52 | competitor | buyer |
| Deal-ACE061 | competitor | unknown |
| Deal-BB78F3 | timing | buyer |
| Deal-D48E0B | no decision | unknown |
| Deal-15DA99 | timing | buyer |
| Deal-F4AF5D | timing | buyer |
| Deal-79B7A1 | timing | buyer |
| Deal-583ADB | no decision | unknown |
| Deal-8E27DA | no decision | buyer |
| Deal-2D2F8D | competitor | unknown |
| Deal-E0441F | champion left | unknown |
| Deal-7CB44D | no decision | unknown |
| Deal-0F96AA | competitor | buyer |
| Deal-1BCA50 | competitor | buyer |
| Deal-7CC678 | competitor | unknown |
| Deal-FAC17C | no decision | buyer |
| Deal-242273 | competitor | buyer |
| Deal-50E5D8 | no decision | buyer |
| Deal-A2C349 | competitor | buyer |
| Deal-9F176A | timing | buyer |
| Deal-7B2236 | pricing | buyer |
| Deal-AFA56C | no decision | unknown |
| Deal-C7156E | competitor | buyer |
| Deal-C33D91 | pricing | buyer |
| Deal-9048EB | product gap | Bonusly |
| Deal-5E64CE | timing | buyer |
| Deal-8A0992 | competitor | buyer |
| Deal-D0C698 | competitor | buyer |
| Deal-69CF3D | timing | buyer |
| Deal-ECBF89 | timing | buyer |
| Deal-3618CC | product gap | Bonusly |
| Deal-EECC02 | competitor | unknown |
| Deal-5AD03E | pricing | buyer |
| Deal-D1A623 | timing | buyer |
| Deal-413C56 | timing | buyer |
| Deal-47F1A1 | competitor | buyer |
| Deal-BF2A98 | competitor | buyer |
| Deal-2A292B | other | buyer |
| Deal-D1AABF | no decision | unknown |
| Deal-FEDBCB | timing | buyer |
| Deal-1E7DA9 | competitor | buyer |
| Deal-2BBA21 | no decision | unknown |
| Deal-286F9C | product gap | Bonusly |
| Deal-7FBAC6 | no decision | buyer |
| Deal-369281 | competitor | buyer |
| Deal-386F6E | no decision | unknown |
| Deal-9FCD0D | competitor | buyer |
| Deal-55867E | timing | buyer |
| Deal-DAFB82 | pricing | buyer |
| Deal-2FEDDB | timing | buyer |
| Deal-64B19A | competitor | buyer |
| Deal-3F86A0 | no decision | unknown |
| Deal-096750 | no decision | unknown |
| Deal-F325A5 | no decision | buyer |
| Deal-ABD14C | other | buyer |
| Deal-79E61A | no decision | unknown |
| Deal-8A119B | pricing | buyer |
| Deal-AE7C4E | no decision | unknown |
| Deal-DAB4F1 | no decision | unknown |
| Deal-B4B50F | no decision | unknown |
| Deal-981AD4 | product gap | Bonusly |
| Deal-DC77FE | product gap | Bonusly |
| Deal-5885B9 | no decision | unknown |

Category counts

- No decision: 29
- Timing: 23
- Competitor: 22
- Pricing: 8
- Product gap: 5
- Other: 2
- Champion left: 1
- Total: 90

Side split

- Buyer: 59
- Unknown: 27
- Bonusly: 4
- Total: 90

Structured-tag disagreements

15 deals have a structured `closed_lost_tag` that clearly disagrees with the free-text reason.

Two patterns most worth acting on

1. No decision and timing dominate: 52 of 90 deals, or 29 + 23. Many describe pauses, delayed reconnects, deprioritization, or lack of engagement. These should be separated into actionable timing versus true no-decision statuses so follow-up and forecasting are more accurate.

2. Competitor losses are substantial: 22 of 90 deals. The free text repeatedly cites broader offerings, integrations or partnerships, customization, regional fit, and incumbent platforms. Competitive qualification should capture the specific product or ecosystem advantage rather than only recording “Competitor.”

{"tier_counts":{"LOCK":6,"ACTION":27,"BUILD":90,"REVIVE":5,"WATCH":16,"RISKY":12},"tier_examples":{"LOCK":["Deal-25F752","Deal-D348E1","Deal-C26D20"],"ACTION":["Deal-E53952","Deal-5408B0","Deal-9AAE5F"],"BUILD":["Deal-499BF6","Deal-D73B89","Deal-C9C286"],"REVIVE":["Deal-2D1F1B","Deal-F0EBBB","Deal-3EED2C"],"WATCH":["Deal-A5E80A","Deal-66D1FC","Deal-950043"],"RISKY":["Deal-547B2B","Deal-B7EBD1","Deal-A2B47C"]},"risky_deals":["Deal-547B2B","Deal-B7EBD1","Deal-A2B47C","Deal-2465CE","Deal-584EE5","Deal-0660B4","Deal-FD9F4E","Deal-BA571A","Deal-7BBDFA","Deal-4A13AD","Deal-690476","Deal-635B8E"],"lock_violations":0,"pipeline_shape":"The 156-deal pipeline is concentrated in BUILD: 90 deals, versus 27 ACTION, 16 WATCH, 12 RISKY, 6 LOCK, and 5 REVIVE; arithmetic: 90+27+16+12+6+5=156. Engagement evidence is mixed, with a small LOCK segment and 12 deals whose forecast category conflicts with weak or absent meeting evidence."}

[
  {
    "transcript_id": "TX-001",
    "deal_alias": "Deal-CFE7F4",
    "why-buys": [
      "Automate anniversary and birthday awards because the HR team of three cannot keep up manually."
    ],
    "pain_points": [
      "HR team of three cannot keep up with anniversary and birthday awards manually.",
      "Everything is tracked in a spreadsheet, and people slip through the cracks."
    ],
    "stakeholders": [
      "Prospect (VP People)",
      "Prospect (HR Admin)"
    ],
    "budget signal": "$40k earmarked for engagement tools this fiscal year.",
    "timeline signal": "Ideally live before open enrollment in November.",
    "competitor mentioned": "Achievers — evaluated last year but considered too heavy for a team of that size.",
    "next step": "Security review with IT lead on September 12.",
    "objections": [
      "Needs SSO and audit logs for IT approval."
    ],
    "confidence": null
  },
  {
    "transcript_id": "TX-002",
    "deal_alias": "Deal-70BB30",
    "why-buys": [
      "Tie recognition to retention for the hourly workforce."
    ],
    "pain_points": [
      "Regretted turnover among the hourly workforce is over 30%."
    ],
    "stakeholders": [
      "Prospect (Head of Total Rewards)",
      "Prospect (CFO)"
    ],
    "budget signal": "$25k pilot budget approved for this quarter.",
    "timeline signal": "Decision by the end of September.",
    "competitor mentioned": null,
    "next step": "Send the pilot agreement for routing to legal this week.",
    "objections": [
      "Workday integration has to be rock solid."
    ],
    "confidence": null
  },
  {
    "transcript_id": "TX-003",
    "deal_alias": "Deal-530B50",
    "why-buys": [
      "Make recognition visible across 12 retail locations."
    ],
    "pain_points": [
      "Store managers have zero budget autonomy for on-the-spot recognition."
    ],
    "stakeholders": [
      "Prospect (People Ops Manager)"
    ],
    "budget signal": null,
    "timeline signal": "No rush until Q1.",
    "competitor mentioned": "Bucketlist — the CEO used it at her last company and liked it.",
    "next step": "Schedule a call with the CEO; the People Ops Manager will send two times.",
    "objections": [
      "The CEO has to be sold first because she decides anything people-related."
    ],
    "confidence": null
  },
  {
    "transcript_id": "TX-004",
    "deal_alias": "Deal-180D02",
    "why-buys": [
      "Consolidate three separate recognition tools into one."
    ],
    "pain_points": [
      "They are paying for three tools, and none of them integrate with the HRIS."
    ],
    "stakeholders": [
      "Prospect (VP People)",
      "Prospect (IT Security Lead)"
    ],
    "budget signal": "If it is under $15k annually, the VP People can approve it without going to the board.",
    "timeline signal": "Procurement cycle runs six to eight weeks minimum.",
    "competitor mentioned": null,
    "next step": null,
    "objections": [
      "Security review took three months for the last vendor.",
      "The VP People gave no commitment to a follow-up with the CFO."
    ],
    "confidence": null
  },
  {
    "transcript_id": "TX-005",
    "deal_alias": "Deal-F8767A",
    "why-buys": [
      "Automate service milestones.",
      "Get analytics on recognition equity across departments."
    ],
    "pain_points": [
      "Night-shift teams feel invisible.",
      "Night-shift teams' engagement scores run 20 points lower.",
      "The executive team is skeptical after a failed rollout two years ago."
    ],
    "stakeholders": [
      "Prospect (HR Director)",
      "Prospect (People Ops Coordinator)"
    ],
    "budget signal": "$12k approved under the engagement line.",
    "timeline signal": "Need it running before the January all-hands.",
    "competitor mentioned": "Nectar — currently in a mid-pilot; the prospect would need a better experience.",
    "next step": "Present to the executive team on October 2.",
    "objections": [
      "The solution must outperform the current Nectar pilot.",
      "The executive team is skeptical after a failed rollout two years ago."
    ],
    "confidence": null
  },
  {
    "transcript_id": "TX-006",
    "deal_alias": "Deal-EE195F",
    "why-buys": [
      "Cut the administrative time required for service awards."
    ],
    "pain_points": [
      "The HR Manager spends five hours per month ordering and shipping plaques."
    ],
    "stakeholders": [
      "Prospect (HR Manager)"
    ],
    "budget signal": "Budget is not the issue; time is.",
    "timeline signal": "A Q1 start is realistic because the fiscal year resets in February.",
    "competitor mentioned": "Doing it internally.",
    "next step": "Send the one-page overview for forwarding to the COO this week.",
    "objections": [
      "The COO usually prefers building things in-house."
    ],
    "confidence": null
  }
]

1. Deal-547B2B — $11,200  
   Why close: DS5/COMMIT; redlines came back clean, signing page is out, and the VP of People said they will sign tomorrow.  
   What’s left: Signature.

2. Deal-403845 — $9,000  
   Why close: DS5/COMMIT; Slack says it is moving fine.  
   What’s left: Finance-team review/approval of the order form.

3. Deal-A2B47C — $6,360  
   Why close: DS5/COMMIT; Slack says it remains warm and is progressing through normal legal review. Its 2026-09-11 CRM close date is earlier than Deal-D348E1’s 2026-10-15 date.  
   What’s left: Complete legal review and signature.

Total: $11,200 + $9,000 + $6,360 = $26,560.

Deal-D348E1 is similarly described as warm and in normal legal review, but its later CRM close date makes it fourth. Deal-2465CE is not close despite DS5/COMMIT: Slack says the champion left, procurement froze new vendors, and it is realistically a Q4 deal.

| Deal | Amount | Prospect line | Classification |
|---|---:|---|---|
| Deal-EC3025 | Not provided | “We need SCIM user provisioning — our security team will not approve any tool that requires manual account management.” | Real gap — SCIM user provisioning is not listed as a supported capability in the product docs. |
| Deal-D0D6B5 | Not provided | “Our payroll runs on ADP Workforce Now and I don't see ADP anywhere in your integration list — that's a dealbreaker for us.” | Real gap — ADP Workforce Now is not listed as a supported integration. |
| Deal-CFE7F4 | Not provided | “I tried to build a custom report combining recognition frequency with turnover and couldn't — is that possible on our current plan?” | Plan gate — the custom report builder is available only on Enterprise. |
| Deal-84DBA6 | Not provided | “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.” | Rollout/enablement issue — Slack integration is supported, and the stated issue is lack of manager training. |

Deal-36C33F is not a prospect-raised gap: the mobile-app limitation was stated by the rep, and the prospect said the web version was sufficient.

Summary — true product gaps

- Deal-EC3025 — Amount not provided  
  “We need SCIM user provisioning — our security team will not approve any tool that requires manual account management.”  
  SCIM user provisioning is not listed as supported.

- Deal-D0D6B5 — Amount not provided  
  “Our payroll runs on ADP Workforce Now and I don't see ADP anywhere in your integration list — that's a dealbreaker for us.”  
  ADP Workforce Now is not listed as a supported integration.

Snapshot date: 2026-09-05.  
Stale threshold: more than 7 days since the latest of `last_email`, `last_call`, and `last_meeting`. Thus, contacts on or before 2026-08-28 are stale.

Bryce Harmon

| Deal alias | Stage | Amount | Days since last contact |
|---|---:|---:|---:|
| Deal-2D1F1B | DS1 | $240,000 | 86 |
| Deal-66D1FC | DS1 | $99,000 | 16 |
| Deal-950043 | DS1 | $70,000 | 19 |
| Deal-B23205 | DS1 | $45,000 | 16 |
| Deal-7BBDFA | DS3 | $37,440 | 46 |
| Deal-332637 | DS2 | $36,000 | 9 |
| Deal-1BEEBF | DS1 | $31,500 | 19 |
| Deal-C5658B | DS1 | $23,400 | 16 |
| Deal-40522D | DS3 | $21,000 | 19 |
| Deal-F0EBBB | DS3 | $11,400 | 24 |
| Deal-E25A09 | DS1 | $6,000 | 9 |
| Deal-C9C286 | DS2 | $5,502 | 9 |
| Deal-3795AD | DS2 | $1 | 8 |

13 stale deals. Total: $626,243  
Arithmetic: $240,000 + $99,000 + $70,000 + $45,000 + $37,440 + $36,000 + $31,500 + $23,400 + $21,000 + $11,400 + $6,000 + $5,502 + $1 = $626,243

Dana Mercer

| Deal alias | Stage | Amount | Days since last contact |
|---|---:|---:|---:|
| Deal-44EA29 | DS2 | $60,000 | 10 |
| Deal-E51FB7 | DS2 | $43,875 | 11 |
| Deal-B42F46 | DS1 | $27,000 | 19 |
| Deal-BA3DDC | DS3 | $23,400 | 15 |
| Deal-9DDE86 | DS2 | $20,000 | 15 |
| Deal-215CCA | DS3 | $18,900 | 17 |
| Deal-5EED42 | DS3 | $16,250 | 11 |
| Deal-57887A | DS2 | $15,000 | 8 |
| Deal-F40F04 | DS2 | $8,100 | 15 |
| Deal-7599B8 | DS3 | $7,350 | 18 |
| Deal-87DDD1 | DS1 | $5,000 | 19 |
| Deal-F336B6 | DS3 | $4,200 | 15 |
| Deal-0660B4 | DS4 | $1,920 | 16 |

13 stale deals. Total: $250,995  
Arithmetic: $60,000 + $43,875 + $27,000 + $23,400 + $20,000 + $18,900 + $16,250 + $15,000 + $8,100 + $7,350 + $5,000 + $4,200 + $1,920 = $250,995

Alex Franklin

| Deal alias | Stage | Amount | Days since last contact |
|---|---:|---:|---:|
| Deal-E73427 | DS3 | $18,000 | 10 |
| Deal-885F45 | DS2 | $9,300 | 12 |
| Deal-C2FF3C | DS1 | $8,316 | 10 |
| Deal-3EED2C | DS2 | $7,200 | No logged contact date |
| Deal-0D2F7A | DS3 | $5,100 | 12 |
| Deal-6C60D4 | DS3 | $4,800 | 12 |
| Deal-13FEBD | DS2 | $4,680 | 12 |
| Deal-9D0060 | DS3 | $3,840 | 12 |
| Deal-EE195F | DS3 | $3,120 | 8 |
| Deal-278DEC | DS3 | $2,700 | 8 |
| Deal-635B8E | DS3 | $2,600 | 18 |
| Deal-6883F3 | DS1 | $2,400 | 16 |
| Deal-4A13AD | DS3 | $2,160 | 26 |
| Deal-F67D31 | DS2 | $1,800 | 8 |
| Deal-5FDCE4 | DS3 | $1,600 | 12 |

15 stale deals. Total: $77,616  
Arithmetic: $18,000 + $9,300 + $8,316 + $7,200 + $5,100 + $4,800 + $4,680 + $3,840 + $3,120 + $2,700 + $2,600 + $2,400 + $2,160 + $1,800 + $1,600 = $77,616

Cole Ingram

| Deal alias | Stage | Amount | Days since last contact |
|---|---:|---:|---:|
| Deal-D04904 | DS2 | $58,529.25 | 11 |
| Deal-B25F40 | DS3 | $40,000 | 8 |
| Deal-813836 | DS2 | $32,175 | 11 |
| Deal-1BA595 | DS2 | $31,750 | 11 |
| Deal-CFE1E8 | DS3 | $18,000 | 11 |
| Deal-CD47A6 | DS2 | $12,168 | 11 |
| Deal-627646 | DS3 | $11,193 | 11 |
| Deal-FF809F | DS2 | $7,781.20 | 11 |
| Deal-A71728 | DS2 | $6,947.50 | 11 |
| Deal-8BC9F5 | DS2 | $5,616 | 10 |
| Deal-175395 | DS3 | $4,779.88 | 11 |
| Deal-481E24 | DS3 | $4,140 | 10 |
| Deal-2F3A66 | DS3 | $3,334.80 | 11 |
| Deal-342E96 | DS2 | $2,700 | 24 |
| Deal-E568D5 | DS3 | $1,875 | 11 |

15 stale deals. Total: $240,989.63  
Arithmetic: $58,529.25 + $40,000 + $32,175 + $31,750 + $18,000 + $12,168 + $11,193 + $7,781.20 + $6,947.50 + $5,616 + $4,779.88 + $4,140 + $3,334.80 + $2,700 + $1,875 = $240,989.63

Farid Osman

| Deal alias | Stage | Amount | Days since last contact |
|---|---:|---:|---:|
| Deal-8BA24E | DS1 | $2,880 | 8 |
| Deal-8FDCD2 | DS1 | $1 | 15 |

2 stale deals. Total: $2,881  
Arithmetic: $2,880 + $1 = $2,881

Elena Sinclair

| Deal alias | Stage | Amount | Days since last contact |
|---|---:|---:|---:|
| Deal-57FF13 | DS1 | $2,100 | No logged contact date |

1 stale deal. Total: $2,100  
Arithmetic: $2,100 = $2,100

Snapshot: 2026-09-05  
30-day window: 2026-08-07 through 2026-09-05, inclusive.  
Activity total = emails + calls + meetings. “Emails” uses `emails_30d`; `inbound_emails_30d` is not added separately.

| Rank by activities per DS2 | Rep | Emails | Calls | Meetings | Total activities | Activity mix: emails / calls / meetings | DS2 entries | Activities per DS2 entry |
|---:|---|---:|---:|---:|---:|---|---:|---:|
| 1 | Farid Osman | 17 | 0 | 4 | 21 | 17/21 = 80.95%; 0/21 = 0.00%; 4/21 = 19.05% | 1 | 21/1 = 21.00 |
| 2 | Alex Franklin | 205 | 34 | 29 | 268 | 205/268 = 76.49%; 34/268 = 12.69%; 29/268 = 10.82% | 7 | 268/7 = 38.29 |
| 3 | Cole Ingram | 104 | 0 | 0 | 104 | 104/104 = 100.00%; 0/104 = 0.00%; 0/104 = 0.00% | 1 | 104/1 = 104.00 |
| 4 | Bryce Harmon | 251 | 0 | 66 | 317 | 251/317 = 79.18%; 0/317 = 0.00%; 66/317 = 20.82% | 3 | 317/3 = 105.67 |
| 5 | Dana Mercer | 95 | 16 | 9 | 120 | 95/120 = 79.17%; 16/120 = 13.33%; 9/120 = 7.50% | 1 | 120/1 = 120.00 |
| — | Elena Sinclair | 0 | 0 | 0 | 0 | Not calculable: 0/0 | 0 | Not calculable: 0/0 |
| — | Gavin Porter | 0 | 0 | 0 | 0 | Not calculable: 0/0 | 0 | Not calculable: 0/0 |
| — | Hugo Lindqvist | 0 | 0 | 0 | 0 | Not calculable: 0/0 | 0 | Not calculable: 0/0 |

DS2 entries counted in the 30-day window:

- Farid Osman: Deal-499BF6
- Alex Franklin: Deal-3EED2C, Deal-7FA0C3, Deal-36C33F, Deal-F436DA, Deal-D1E6C2, Deal-CA5E44, Deal-92D97D
- Cole Ingram: Deal-1BA595
- Bryce Harmon: Deal-25F752, Deal-D73B89, Deal-CA7DC0
- Dana Mercer: Deal-57887A
- Elena Sinclair, Gavin Porter, and Hugo Lindqvist: no DS2 entries in the window

Most efficient rep: Farid Osman, at 21.00 activities per DS2 entry.

Highest-volume rep: Bryce Harmon, with 317 total activities.

They differ: yes.

QTD GTM Scorecard — Alex Franklin
As of 2026-09-05

Bookings vs quota
- Q3 bookings: $150,000
- Quota: $200,000
- Attainment: $150,000 ÷ $200,000 = 75.0%
- Remaining to quota: $200,000 − $150,000 = $50,000
- QTD closed-won deals: 8
- Pre-quarter closed-won deals excluded: Deal-B3E6F1, closed 2026-06-20

New vs. expansion
- New: $113,500
  - $40,000 + $35,000 + $21,000 + $11,000 + $6,500
  - New share: $113,500 ÷ $150,000 = 75.7%
- Expansion: $36,500
  - $20,000 + $12,000 + $4,500
  - Expansion share: $36,500 ÷ $150,000 = 24.3%

Active pipeline by stage
- DS1: 20 deals, $284,621
- DS2: 28 deals, $353,760
- DS3: 67 deals, $552,705
- DS4: 5 deals, $23,574
- DS5: 5 deals, $45,730
- Total active pipeline: 125 deals, $1,260,390

Rolling 90-day DS2-to-won rate
Using deals that entered DS2 from 2026-06-07 through 2026-09-05 and subsequently closed:
- Won: 8
- Lost: 27
- Closed DS2 cohort: 8 + 27 = 35
- DS2-to-won rate: 8 ÷ 35 = 22.9%

QTD win/loss counts
- Wins: 8
- Losses: 27
- Total closed: 8 + 27 = 35
- Top loss reason: Lost- Timing (1 year or more)
  - 13 losses
  - $184,681 lost amount

Activity volume — last 30 days
- Emails: 807
- Calls: 112
- Meetings: 128
- Notes: 50
- Total activities: 807 + 112 + 128 + 50 = 1,097

Coaching observations
1. Alex is at 75.0% attainment, with $50,000 remaining to quota. The current active pipeline of $1,260,390 is substantially larger than the remaining gap, but conversion execution will determine whether that coverage turns into bookings.

2. Pipeline is concentrated in DS3: $552,705 across 67 deals, or $552,705 ÷ $1,260,390 = 43.8% of active pipeline. Focus on advancing or disqualifying DS3 opportunities to prevent pipeline accumulation without sufficient progression.

3. Timing is the dominant loss pattern: 13 of 27 losses, or 48.1%, were attributed to Lost- Timing (1 year or more), totaling $184,681. Earlier timeline qualification and stronger urgency creation should be coaching priorities.

Active cutoff: 2026-07-05 (2026-09-03 minus 60 days). Active = engaged on/after 2026-07-05 and `is_former=false`.

Amount and stage are not provided, so both are unavailable. Because stage is missing, the most valuable persona to add given the stage cannot be determined.

Flagged deals:

- Deal-EC3025 — Company C-FDD0C7
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 1
    - 2 listed contacts − 1 former contact = 1 active
  - Personas present: champion
  - Personas missing: economic buyer, HR admin, IT security, finance
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: CT-6827DB, Chief People Officer, economic buyer

- Deal-92D97D — Company C-E23238
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 1
    - 2 listed contacts − 1 contact last engaged 2026-06-01, before 2026-07-05 = 1 active
  - Personas present: HR admin
  - Personas missing: economic buyer, champion, IT security, finance
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: none on file

- Deal-50D386 — Company C-EB10E4
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 2
    - 2 listed contacts − 0 excluded contacts = 2 active
  - Personas present: champion, HR admin
  - Personas missing: economic buyer, IT security, finance
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: CT-A1C4B3, Chief People Officer, economic buyer

- Deal-D0D6B5 — Company C-32918E
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 3
    - 3 listed contacts − 0 excluded contacts = 3 active
  - Personas present: champion
  - Personas missing: economic buyer, HR admin, IT security, finance
  - Flag reason: all active contacts are in one persona
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: CT-1FA4DB, Chief People Officer, economic buyer

- Deal-5BFE3B — Company C-535D36
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 2
    - 2 listed contacts − 0 excluded contacts = 2 active
  - Personas present: champion
  - Personas missing: economic buyer, HR admin, IT security, finance
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: none on file

- Deal-36C33F — Company C-077A0E
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 1
    - 3 listed contacts − 2 former contacts = 1 active
  - Personas present: IT security
  - Personas missing: economic buyer, champion, HR admin, finance
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: CT-1DB73E, Chief People Officer, economic buyer

- Deal-885F45 — Company C-5E8EFB
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 2
    - 2 listed contacts − 0 excluded contacts = 2 active
  - Personas present: economic buyer, champion
  - Personas missing: HR admin, IT security, finance
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: CT-B3F25D, IT Security Lead, IT security

- Deal-FCBE5B — Company C-737030
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 1
    - 1 listed contact − 0 excluded contacts = 1 active
  - Personas present: champion
  - Personas missing: economic buyer, HR admin, IT security, finance
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: none on file

- Deal-5408B0 — Company C-2AE3AA
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 2
    - 2 listed contacts − 0 excluded contacts = 2 active
  - Personas present: champion, HR admin
  - Personas missing: economic buyer, IT security, finance
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: CT-07FA76, Chief People Officer, economic buyer

- Deal-C6D97A — Company C-5A8FC2
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 3
    - 3 listed contacts − 0 excluded contacts = 3 active
  - Personas present: champion
  - Personas missing: economic buyer, HR admin, IT security, finance
  - Flag reason: all active contacts are in one persona
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: none on file

- Deal-F9A08A — Company C-0D15DF
  - Amount: not provided
  - Stage: not provided
  - Active contacts: 1
    - 2 listed contacts − 1 stale contact last engaged 2026-06-20 = 1 active
  - Personas present: champion
  - Personas missing: economic buyer, HR admin, IT security, finance
  - Most valuable persona to add given stage: cannot determine; stage not provided
  - Unengaged matching contact on file: CT-697541, Chief People Officer, economic buyer

Not flagged: Deal-84DBA6, Deal-4B0BEB, and Deal-D348E1. Each has at least 3 active contacts with more than one active persona.

First five minutes

- Leads with a customer outcome/case study about automated milestone awards in 8 of 10 calls (80%): “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 other two calls lead with an agenda/security review (Deal-403845) or pricing requested previously (Deal-1E2498).

Three most common objections

- Budget: 4 of 10 calls (40%; Deal-D348E1, Deal-547B2B, Deal-60C2C2, Deal-84DBA6). He reframes the purchase as funded by turnover savings and cites avoided backfill costs: “Most teams fund this out of turnover savings — that retailer saved about $210k in avoided backfills, which is how their finance team signed off.”
- Timing/capacity: 3 of 10 calls (30%; Deal-5408B0, Deal-C61CF7, Deal-D9A12F). He proposes a limited pilot to generate internal data before the prospect’s planning cycle: “What if we scope a 90-day pilot with one department so you have internal data before next quarter's planning?”
- Status quo/manual process: 3 of 10 calls (30%; Deal-403845, Deal-EDC141, Deal-1E2498). He positions automation and analytics as the reason to change: “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 rate

- 7 of 10 calls included an agreed concrete next step: Deal-D348E1, Deal-5408B0, Deal-547B2B, Deal-C61CF7, Deal-60C2C2, Deal-D9A12F, and Deal-1E2498.
- Arithmetic: 7 agreed next steps ÷ 10 calls = 70%.
- In each of those seven calls, the prospect agreed to the working session: “Yes, Thursday at 2pm works — send the invite and I'll bring our HRIS manager.”

Competitors raised by prospects

- Awardco — Deal-547B2B.
- Kudos — Deal-EDC141.
- Workhuman was mentioned by the rep, not raised by a prospect.

Coaching notes

1. The budget response is consistent and effective, but the same $210k example is repeated; tailor the financial case to each prospect’s stated approval process.
2. When prospects show no urgency or defer to a committee, the rep often accepts the stall without securing a follow-up date; ask for a specific decision checkpoint or committee debrief.

# Q3 2026 Forecast

Quarter: 2026-07-01 through 2026-09-30, inclusive.

## Forecast summary

- COMMIT: 7 deals totaling $44,729
- BEST_CASE: 24 deals totaling $203,565
- PIPELINE: 23 deals totaling $201,637.40; weighted at 0%

Weighted forecast:

$44,729 + (35% × $203,565) + (0% × $201,637.40)

= $44,729 + $71,247.75 + $0

= $115,976.75

## Excluded outside the quarter

32 deals totaling $227,575 were excluded because their close dates were after 2026-09-30:

- Deal-E51FB7 — $43,875
- Deal-B936FE — $18,000
- Deal-D9A12F — $17,000
- Deal-D348E1 — $13,770
- Deal-4062CF — $10,800
- Deal-293AF3 — $9,000
- Deal-034D49 — $9,000
- Deal-E0ADD8 — $7,920
- Deal-9F2E43 — $7,690
- Deal-FCBE5B — $7,500
- Deal-712010 — $7,200
- Deal-6691E0 — $5,700
- Deal-C61CF7 — $5,400
- Deal-600CD9 — $5,400
- Deal-A92065 — $5,400
- Deal-1D532E — $5,400
- Deal-48B656 — $5,160
- Deal-E531A6 — $4,800
- Deal-D1E6C2 — $4,400
- Deal-D9E112 — $4,300
- Deal-5AD94B — $4,000
- Deal-901332 — $3,600
- Deal-47AE31 — $3,600
- Deal-15D24F — $3,600
- Deal-766C74 — $3,300
- Deal-ED725A — $2,400
- Deal-8AD4A5 — $1,800
- Deal-D7E999 — $1,800
- Deal-ED13B0 — $1,680
- Deal-5FDCE4 — $1,600
- Deal-7FA0C3 — $1,400
- Deal-F5A622 — $1,080

## Top 5 BEST_CASE deals inside the quarter

1. Deal-2D7423 — $38,935
2. Deal-25F752 — $24,000
3. Deal-E53952 — $19,656
4. Deal-5EED42 — $16,250
5. Deal-FA32A0 — $11,116

Arithmetic:

$38,935 + $24,000 + $19,656 + $16,250 + $11,116 = $109,957

## Data quality

Many records have blank owners, including the top five BEST_CASE deals, so ownership and accountability cannot be validated. `why_buys_chars` is zero for many deals, including Deal-2D7423, Deal-25F752, and Deal-E53952, indicating missing qualification data. Forecast categories do not consistently align with stage, such as COMMIT Deal-A5E80A at DS1 and COMMIT Deal-499BF6 at DS2. The extract includes 32 deals outside the quarter, so an unattended forecast must reliably enforce the close-date filter.

Activation hypothesis result

| First-month signal group | Cohort size | Retained at 24 months | Retention rate |
|---|---:|---:|---:|
| Both signals: m1_users ≥ 5 and m1_redemptions ≥ 1 | 47 | 31 | 31 ÷ 47 = 65.96% |
| Givers-only: m1_users ≥ 5 and m1_redemptions = 0 | 49 | 23 | 23 ÷ 49 = 46.94% |
| Redemption-only: m1_users < 5 and m1_redemptions ≥ 1 | 29 | 9 | 9 ÷ 29 = 31.03% |
| Neither signal | 95 | 38 | 38 ÷ 95 = 40.00% |

Total: 47 + 49 + 29 + 95 = 220 companies.

Excluded from denominator: 0 companies. All records have the required signal fields and current_status values.

The both-signals group had higher retention than:
- Givers-only by 65.96% − 46.94% = 19.02 percentage points.
- Redemption-only by 65.96% − 31.03% = 34.93 percentage points.
- Neither by 65.96% − 40.00% = 25.96 percentage points.

Single signal with the largest retention lift: givers. Compared with neither, givers-only retention was 46.94% − 40.00% = 6.94 percentage points higher. Redemption-only was 31.03% − 40.00% = 8.97 percentage points lower.

If measuring signal presence across all companies rather than single-signal cohorts:
- Givers present: 54 ÷ 96 = 56.25%; absent: 47 ÷ 124 = 37.90%; lift = 18.35 percentage points.
- Redemption present: 40 ÷ 76 = 52.63%; absent: 61 ÷ 144 = 42.36%; lift = 10.27 percentage points.
Givers still show the larger lift.

This supports the hypothesis that companies exhibiting both first-month signals had better observed 24-month retention than each comparison group in this extract.

It does not prove that the signals caused retention. The result is observational and may reflect other differences between companies, such as customer mix, product tier, or unmeasured factors.

Reconciliation as of 2026-09-05

Totals

- CRM company ARR: $603,581.76
- Billing ARR: $604,739.28
  - Active billing MRR: $50,394.94
  - $50,394.94 × 12 = $604,739.28
- Variance, CRM minus Billing: **-$1,157.52**

Decomposition

| Bucket | Arithmetic | Variance |
|---|---:|---:|
| Status mismatch | $4,905.24 + $8,253.24 | +$13,158.48 |
| Rounding | $16.00 + $20.00 | +$36.00 |
| Missing records | -$28,449.24 + $16,497.24 | -$11,952.00 |
| Other | -$2,400.00 | -$2,400.00 |
| **Total** | $13,158.48 + $36.00 - $11,952.00 - $2,400.00 | **-$1,157.52** |

Mismatched accounts

| Company alias | Subscription | CRM ARR | Billing ARR | Difference (CRM − Billing) | Bucket | Suggested owner |
|---|---|---:|---:|---:|---|---|
| C-21629AA4 | SUB-0004 | Missing | $28,449.24 | -$28,449.24 | Missing record | CRM Operations |
| C-0D66DF9E | SUB-0005 | $23,200.00 | $23,184.00 | +$16.00 | Rounding | Finance / RevOps |
| C-0F7269D7 | SUB-0006 | $24,396.00 | $26,796.00 | -$2,400.00 | Other | Billing Operations |
| C-14D70CE0 | SUB-0008 | $18,200.00 | $18,180.00 | +$20.00 | Rounding | Finance / RevOps |
| C-0C8323BF | SUB-000E | $4,905.24 | $0.00 | +$4,905.24 | Status mismatch | Billing Operations |
| C-0DC4FB8C | SUB-000F | $8,253.24 | $0.00 | +$8,253.24 | Status mismatch | Billing Operations |
| C-0D5BBE3A | No billing subscription | $16,497.24 | Missing | +$16,497.24 | Missing record | Billing Operations |

Term-date violations

The rule requires `cf_agreement_end_date` for every subscription whose term is not 12 months.

- SUB-0002 — C-1794A52C — 24 months — `cf_agreement_end_date` missing
- SUB-0019 — C-22170CA1 — 36 months — `cf_agreement_end_date` missing

Averages across the 30 company records per month.

| KVM | 2026-08 value | 2026-07 prior | Absolute change | Relative change | Direction |
|---|---:|---:|---:|---:|---|
| Giving rate | 0.6027 | 0.6023 | 0.0004 | +0.07% | Up |
| Redemptions per user | 1.7302 | 1.7300 | 0.0002 | +0.01% | Up |
| 1:1 meetings engagement | 0.4472 | 0.4469 | 0.0003 | +0.06% | Up |
| Pulse check engagement | 0.5086 | 0.6006 | -0.0920 | -15.31% | Down |

Arithmetic: absolute change = August − July; relative change = absolute change ÷ July.

Pulse check engagement had the largest relative move: (0.5086 − 0.6006) ÷ 0.6006 = -15.31%. The enterprise segment drove it: (0.2743 − 0.5500) ÷ 0.5500 = -50.13%. The data supports `size_band` as the driver; `plan_tier` does not vary because all records are `tier_three`.

Redemption report through August 2026, the last completed month:

- Redemption count: 1,188
- Spend: $90,463.00
- Unique redeemers: 335
- Redemptions per redeemer: 1,188 ÷ 335 = 3.5463

Provider mix by spend:

- custom: $36,163.00 ÷ $90,463.00 = 39.97%
- Tremendous: $26,270.00 ÷ $90,463.00 = 29.04%
- Snappy: $16,055.00 ÷ $90,463.00 = 17.75%
- TangoCard: $11,975.00 ÷ $90,463.00 = 13.24%
- Total: 100.00% (custom share adjusted by 0.01 percentage point for rounding)

Top 5 countries by redemptions:

1. US: 754
2. CA: 85
3. AU: 58
4. NL: 53
5. GB: 51

Eligibility rules applied: health score < 60, eligible amount > $0, and renewal within 120 days of 2026-09-05 (by 2027-01-03).

Qualifying accounts

- C-0F6C0F34 — $49,707.00 at stake. Renewal is in 28 days; health score 51. Best fit: executive touch. Signal: champion_active=false. Usage is growing and utilization is 308/395 = 78.0%, so the data does not support usage revival.
- C-0B827671 — $25,365.00 at stake. Renewal is in 70 days; health score 56. Best fit: usage revival. Signal: usage_trend_3m=declining and utilization is 113/202 = 55.9%. Champion is active.
- C-0B360C78 — $35,748.00 at stake. Renewal is in 53 days; health score 57. No specific play is supported by the supplied signals: usage is growing, utilization is 246/327 = 75.2%, and champion_active=true. No commercial-concession signal is provided.
- C-0B0F1BAB — $5,494.00 at stake. Renewal is in 18 days; health score 38. Best fit: executive touch. Signal: champion_active=false. Usage is flat and utilization is 238/363 = 65.6%.
- C-0CA21961 — $16,829.00 at stake. Renewal is in 114 days; health score 58. Best fit: usage revival. Signal: very low utilization, 84/325 = 25.8%; usage trend is flat. Champion is active.
- C-0E9C27D1 — $41,235.00 at stake. Renewal is in 19 days; health score 39. No specific play is supported by the supplied signals: usage is flat, utilization is 134/157 = 85.4%, and champion_active=true. No commercial-concession signal is provided.
- C-0CEF69FD — $32,621.00 at stake. Renewal is in 77 days; health score 53. Best fit: executive touch. Signal: champion_active=false. Usage is growing and utilization is 97/136 = 71.3%.
- C-0D3278C7 — $17,602.00 at stake. Renewal is in 68 days; health score 54. Best fit: usage revival. Signals: usage_trend_3m=declining and low utilization, 126/380 = 33.2%. Champion is active.

Commercial concession

No account has a documented commercial signal supporting a commercial concession. The provided data contains eligible amounts, ARR, health, renewal timing, usage, utilization, and champion status, but no pricing, budget, discount, or contract signal. Therefore, assigning that play would require inventing evidence.

Total amount at stake

$49,707.00 + $25,365.00 + $35,748.00 + $5,494.00 + $16,829.00 + $41,235.00 + $32,621.00 + $17,602.00 = $224,601.00

At-risk accounts that do not qualify

- C-0BC71BDD — Does not qualify because churn_save_eligible_amount=$0.00, despite health score 55 and renewal in 52 days.
- C-0BA71F12 — Does not qualify because renewal is in 218 days, outside the 120-day window. Health score is 52 and amount is $6,824.00.
- C-0F6694C3 — Does not qualify because churn_save_eligible_amount=$0.00 and renewal is in 197 days. Health score is 43.
- C-0BE96399 — Does not qualify because churn_save_eligible_amount=$0.00, despite health score 54 and renewal in 54 days.
- C-0F876796 — Does not qualify because renewal is in 154 days, outside the 120-day window. Health score is 47 and amount is $19,958.00.
- C-0FCCD2DF — Does not qualify because churn_save_eligible_amount=$0.00 and renewal is in 230 days. Health score is 43.
- C-10A56B0F — Does not qualify because churn_save_eligible_amount=$0.00, despite health score 54 and renewal in 98 days.

Company: C-0DDFC9A7

Seat coverage:
- Licensed seats / headcount: 150 / 400 = 37.5%
- Uncovered headcount: 400 − 150 = 250 people

Usage health:
- Monthly active users increased from 88 in 2026-03 to 126 in 2026-08: 126 − 88 = 38 users, or 43.2%.
- August usage was 126 / 150 = 84.0% of licensed seats.

Expansion headroom:
- Seats: 400 − 150 = 250 additional seats
- Current per-seat rate: $9,000 / 150 = $60
- ARR headroom: 250 × $60 = $15,000

Contact routing:
- Maria S., People Operations Coordinator, replied. She cannot buy; she stated that budget and seat expansion sit with Dana R.
- Right buyer: Dana R., VP People.

Reply email:

Hi Maria,

Thanks for the context—and for offering to connect me with Dana. It’s great to hear the team is getting value from Bonusly. Usage reached 126 monthly active users in August, up from 88 in March.

Would you be comfortable introducing me to Dana so I can share a brief view of the usage and discuss whether expanding seats makes sense? I’m happy to keep it low-key and let her decide if it’s worth a conversation.

Best,  
Cole

Company: C-0D284E42

Complete
- Slack integration connected: 2026-08-12
- Allowance set: 2026-08-13
- Admins added: 2
- First recognition given: 2026-08-15 at 14:22

Not complete / no completion data
- HRIS integration: no completion date is provided.
- First redemption: no completion date is provided.

Early engagement signals
- Active givers increased from 3 on 2026-08-11 to 15 on 2026-09-04.
- Arithmetic: 15 − 3 = 12 additional active givers; 12 ÷ 3 × 100 = 400% increase.
- Average active givers over the 25 reported days: 214 ÷ 25 = 8.56.
- Average active givers in the first 7 days: 30 ÷ 7 = 4.29.
- Average active givers in the last 7 days: 91 ÷ 7 = 13.00.
- The data shows growing giver engagement, but it does not provide recognition counts or redemption activity.

Three things to cover
1. Confirm the HRIS integration status and address any remaining setup steps.
2. Identify and remove the blocker to the first redemption.
3. Discuss how to build on the increase in active givers and encourage continued recognition activity.

90-day renewal risk brief

Method:
- Multi-year contracts: use Chargebee date because ChurnZero multi-year renewal dates are known to be wrong.
- Non-multi-year contracts: use the shared date; both systems agree.
- Seat utilization = seats used ÷ seats × 100.
- Risk: High = utilization below 50%; Medium = utilization 50%–under 60% or declining usage; Low = utilization at least 60% with stable/increasing usage.
- Three-month trend is June → July → August 2026.

Renewals

| Company | CSM | ARR | Date used | Seat utilization | 3-month usage trend | Risk | Evidence |
|---|---|---:|---|---:|---|---|---|
| C-0B7D2C30 | Dana Mercer | $65,901 | 2026-09-15 | 274 ÷ 476 = 57.6% | 97 → 94 → 84 (-13) | Medium | Utilization is below 60% and active users declined by 13 over the last three months. Date disagreement: ChurnZero 2026-09-10 vs Chargebee 2026-09-15; Chargebee used because the contract is multi-year. |
| C-0BCDB8C2 | Cole Ingram | $54,427 | 2026-09-18 | 232 ÷ 424 = 54.7% | 127 → 118 → 110 (-17) | Medium | Utilization is below 60% and active users declined by 17. Date disagreement: ChurnZero 2027-09-18 vs Chargebee 2026-09-18; Chargebee used because the contract is multi-year. |
| C-0D2AB865 | Elena Sinclair | $38,022 | 2026-09-22 | 250 ÷ 407 = 61.4% | 125 → 117 → 109 (-16) | Medium | Active users declined by 16 despite utilization above 60%. Date disagreement: ChurnZero 2026-09-10 vs Chargebee 2026-09-22; Chargebee used because the contract is multi-year. |
| C-0BBE3E60 | Dana Mercer | $30,993 | 2026-09-26 | 74 ÷ 114 = 64.9% | 39 → 35 → 33 (-6) | Medium | Active users declined by 6. Date disagreement: ChurnZero 2027-09-26 vs Chargebee 2026-09-26; Chargebee used because the contract is multi-year. |
| C-0F5D2323 | Cole Ingram | $90,647 | 2026-09-29 | 111 ÷ 390 = 28.5% | 20 → 21 → 18 (-2) | High | Utilization is below 50%, at 28.5%, with a net decline of 2 users. Date disagreement: ChurnZero 2026-09-10 vs Chargebee 2026-09-29; Chargebee used because the contract is multi-year. |
| C-0EC6999D | Elena Sinclair | $79,419 | 2026-10-03 | 31 ÷ 112 = 27.7% | 17 → 16 → 15 (-2) | High | Utilization is below 50%, at 27.7%, and active users declined by 2. Dates agree. |
| C-0B20DB64 | Dana Mercer | $21,770 | 2026-10-07 | 214 ÷ 378 = 56.6% | 294 → 298 → 294 (0) | Medium | Utilization is below 60%, although the three-month net usage trend is flat. Dates agree. |
| C-0BBC4E7A | Cole Ingram | $56,374 | 2026-10-10 | 228 ÷ 337 = 67.7% | 142 → 141 → 139 (-3) | Medium | Active users declined by 3. Dates agree. |
| C-0FD551AB | Elena Sinclair | $48,815 | 2026-10-14 | 210 ÷ 376 = 55.9% | 123 → 122 → 126 (+3) | Medium | Utilization is below 60%, despite a net increase of 3 users. Dates agree. |
| C-0F9F8F13 | Dana Mercer | $46,230 | 2026-10-18 | 199 ÷ 352 = 56.5% | 185 → 185 → 182 (-3) | Medium | Utilization is below 60% and active users declined by 3. Dates agree. |
| C-0BC34584 | Cole Ingram | $16,740 | 2026-10-22 | 327 ÷ 494 = 66.2% | 104 → 104 → 106 (+2) | Low | Utilization is above 60% and active users increased by 2. Dates agree. |
| C-0B7A7546 | Elena Sinclair | $35,062 | 2026-10-25 | 182 ÷ 205 = 88.8% | 64 → 65 → 63 (-1) | Medium | Active users declined by 1. Dates agree. |
| C-0B369871 | Dana Mercer | $85,128 | 2026-10-29 | 317 ÷ 422 = 75.1% | 326 → 330 → 333 (+7) | Low | Utilization is above 60% and active users increased by 7. Dates agree. |
| C-0B144C78 | Cole Ingram | $30,899 | 2026-11-02 | 169 ÷ 224 = 75.4% | 101 → 101 → 106 (+5) | Low | Utilization is above 60% and active users increased by 5. Dates agree. |
| C-0FC4DBB8 | Elena Sinclair | $94,732 | 2026-11-05 | 356 ÷ 464 = 76.7% | 189 → 191 → 193 (+4) | Low | Utilization is above 60% and active users increased by 4. Dates agree. |
| C-0D5BBE3A | Dana Mercer | $39,740 | 2026-11-09 | 85 ÷ 102 = 83.3% | 88 → 90 → 91 (+3) | Low | Utilization is above 60% and active users increased by 3. Dates agree. |
| C-0FB9D5AF | Cole Ingram | $63,158 | 2026-11-13 | 144 ÷ 199 = 72.4% | 173 → 173 → 176 (+3) | Low | Utilization is above 60% and active users increased by 3. Dates agree. |
| C-0B344485 | Elena Sinclair | $64,384 | 2026-11-16 | 224 ÷ 287 = 78.0% | 238 → 240 → 244 (+6) | Low | Utilization is above 60% and active users increased by 6. Dates agree. |
| C-0CB2C1B4 | Dana Mercer | $40,628 | 2026-11-20 | 386 ÷ 473 = 81.6% | 47 → 48 → 49 (+2) | Low | Utilization is above 60% and active users increased by 2. Dates agree. |
| C-22170CA1 | Cole Ingram | $45,646 | 2026-11-24 | 251 ÷ 294 = 85.4% | 143 → 148 → 146 (+3) | Low | Utilization is above 60% and active users increased by 3. Dates agree. |

Disagreements

All five disagreements are multi-year contracts, so Chargebee was used:

- C-0B7D2C30: ChurnZero 2026-09-10 vs Chargebee 2026-09-15
- C-0BCDB8C2: ChurnZero 2027-09-18 vs Chargebee 2026-09-18
- C-0D2AB865: ChurnZero 2026-09-10 vs Chargebee 2026-09-22
- C-0BBE3E60: ChurnZero 2027-09-26 vs Chargebee 2026-09-26
- C-0F5D2323: ChurnZero 2026-09-10 vs Chargebee 2026-09-29

Summary

Total ARR renewing:

$65,901 + $54,427 + $38,022 + $30,993 + $90,647 + $79,419 + $21,770 + $56,374 + $48,815 + $46,230 + $16,740 + $35,062 + $85,128 + $30,899 + $94,732 + $39,740 + $63,158 + $64,384 + $40,628 + $45,646 = $1,048,715

ARR at risk, defined as High + Medium:

- High: $90,647 + $79,419 = $170,066
- Medium: $65,901 + $54,427 + $38,022 + $30,993 + $21,770 + $56,374 + $48,815 + $46,230 + $35,062 = $397,594
- Total ARR at risk: $170,066 + $397,594 = $567,660

1. HRIS provisioning failures — broad pattern
- Count: 12 tickets
- Share: 12 / 80 = 15.0%
- Distinct accounts: 3 — C-0B2213A9, C-0F6C0F34, C-0DDFC9A7
- ARR affected: $36,000 + $30,000 + $48,000 = $114,000
- Ticket IDs: IC-460059, IC-460060
- Recommendation: Prioritize investigation of HRIS sync and provisioning failures, including skipped hires with no provisioning-log errors.

2. Redemption and gift-card fulfillment failures — broad pattern
- Count: 18 tickets
- Share: 18 / 80 = 22.5%
- Distinct accounts: 7 — C-0CEF69FD, C-0B827671, C-0FCCD2DF, C-0F876796, C-14264ABD, C-0D9CA315, C-0B0F1BAB
- ARR affected: $8,900 + $10,700 + $9,600 + $8,700 + $11,000 + $9,600 + $10,300 = $68,800
- Ticket IDs: IC-460025, IC-460024
- Recommendation: Trace the redemption workflow from checkout through gift-card delivery and points deduction.

3. Billing and invoice discrepancies — single-account concentration
- Count: 16 tickets
- Share: 16 / 80 = 20.0%
- Distinct accounts: 1 — C-0E9C27D1
- ARR affected: $52,000 = $52,000
- Ticket IDs: IC-460071, IC-460078
- Recommendation: Assign an account-specific billing owner to resolve the recurring seat-count and renewal-tier discrepancies.

4. Points and recognition posting delays — broad pattern
- Count: 20 tickets
- Share: 20 / 80 = 25.0%
- Distinct accounts: 9 — C-0D3278C7, C-0BF20542, C-0D0B047C, C-0BE96399, C-0D284E42, C-0D6CC8E3, C-21FEBCBB, C-0DD0626C, C-0B2895EF
- ARR affected: $3,500 + $4,500 + $4,500 + $2,700 + $3,400 + $4,200 + $2,900 + $2,500 + $2,900 = $31,100
- Ticket IDs: IC-460004, IC-460016
- Recommendation: Investigate the shared recognition-to-balance posting pipeline, including delivered recognitions whose points never arrive.

5. Slack integration failures — broad pattern
- Count: 14 tickets
- Share: 14 / 80 = 17.5%
- Distinct accounts: 4 — C-0B843542, C-10A56B0F, C-0BA71F12, C-8C2E8F00
- ARR affected: $4,400 + $5,400 + $3,900 + $5,200 = $18,900
- Ticket IDs: IC-460041, IC-460047
- Recommendation: Stabilize Slack authentication, sync toggles, and slash-command handling across affected accounts.

Ranked by ARR exposure: HRIS provisioning ($114,000), redemption/gift-card fulfillment ($68,800), billing/invoice discrepancies ($52,000), points/recognition posting ($31,100), Slack integrations ($18,900).

1. C-64171065 — Technology, Mid-Market, employee_recognition, NA-East, case study: true
   - Matches 3 of 4 fields:
     - Industry: Technology
     - Size band: Mid-Market
     - Use case: employee_recognition
   - Region differs: prospect NA-West; customer NA-East.

2. C-A13C193D — Technology, Mid-Market, retention, NA-West, case study: true
   - Matches 3 of 4 fields:
     - Industry: Technology
     - Size band: Mid-Market
     - Region: NA-West
   - Use case differs: prospect employee_recognition; customer retention.

3. C-11C31562 — Manufacturing, Mid-Market, employee_recognition, NA-West, case study: true
   - Matches 3 of 4 fields:
     - Size band: Mid-Market
     - Use case: employee_recognition
     - Region: NA-West
   - Industry differs: prospect Technology; customer Manufacturing.

Trailing 6 months: March–August 2026.

Paid channel performance

| Channel | Spend | SQMs | SQOs | Cost/SQM | Cost/SQO | SQM-to-SQO | Pipeline | Pipeline/$ |
|---|---:|---:|---:|---:|---:|---:|---:|---:|
| paid_search | $36,000 | 39 | 18 | $36,000 ÷ 39 = $923.08 | $36,000 ÷ 18 = $2,000 | 18 ÷ 39 = 46.15% | $720,000 | $720,000 ÷ $36,000 = $20.00 |
| linkedin_ads | $24,000 | 24 | 8 | $24,000 ÷ 24 = $1,000 | $24,000 ÷ 8 = $3,000 | 8 ÷ 24 = 33.33% | $96,000 | $96,000 ÷ $24,000 = $4.00 |
| paid_social | $18,000 | 0 | 0 | Undefined: $18,000 ÷ 0 | Undefined: $18,000 ÷ 0 | Undefined: 0 ÷ 0 | $0 | $0 ÷ $18,000 = $0.00 |
| webinars | $9,000 | 12 | 5 | $9,000 ÷ 12 = $750 | $9,000 ÷ 5 = $1,800 | 5 ÷ 12 = 41.67% | $60,000 | $60,000 ÷ $9,000 = $6.67 |

Organic performance

| Channel | Volume | SQOs | SQO rate | Pipeline |
|---|---:|---:|---:|---:|
| organic_search | 29 | 10 | 10 ÷ 29 = 34.48% | $90,000 |

Date-order flags

- CT-000044: SQM date 2026-07-23; SQO date 2026-07-18. SQO precedes SQM.
- CT-000041: SQM date 2026-06-14; SQO date 2026-06-09. SQO precedes SQM.

SQO counts above use all nonblank SQO dates as supplied, including the two flagged rows.

Recommendation

Reallocate spend away from paid_social, which generated 0 SQMs, 0 SQOs, and $0 pipeline on $18,000 of spend. Prioritize paid_search first because it produced $20.00 of pipeline per dollar, followed by webinars at $6.67 per dollar. LinkedIn_ads produced $4.00 per dollar and should receive lower incremental priority.

Confidence: medium-low. The performance differences are substantial, but sample sizes are limited: 0 paid_social SQMs, 12 webinar SQMs, 24 LinkedIn SQMs, 39 paid-search SQMs, and 29 organic contacts. The two date-order violations also reduce confidence in the attribution data.

# Battlecard: Rivally

## One-line positioning

Rivally is a recognition platform centered on an engaging, points-based feed, with strengths in distributed European teams and multilingual support; its analytics and administrative tooling trail enterprise alternatives. [S02, S12, S16]

## Pricing

- Public pricing: Rivally Recognition Starter is listed at $7 per user/month with annual billing required, as of 2026-08-12. [S17]
- Deal-specific quote: An 800-seat prospect reported a $7 per user/month list price with a 15% discount for a three-year term on 2026-08-14. [S18]
- Conflict: A 500-seat prospect was quoted $6.50 per user/month on an annual term on 2026-06-02; this older deal-specific quote is superseded by the newer $7 list-price sources for current public pricing. [S13, S17, S18]

## Where Rivally wins

- Fast implementation: a mid-market reviewer reported setup taking under a week. [S04]
- Integrations: a reviewer said the Slack integration worked out of the box. [S04]
- European deployments: reviewers praised Rivally for distributed EU teams and multilingual support. [S12]
- EU readiness: Rivally announced generally available EU data residency and opened a Dublin office. [S15]
- Engagement: reviewers describe the recognition feed as engaging. [S02, S16]
- Support: a G2 reviewer praised support response times of under four hours. [S22]

## Where we win

- Analytics depth: an 800-seat prospect selected Bonusly over Rivally, citing analytics depth. [S25]
- Reporting: reviewers describe Rivally’s reporting dashboards as basic compared with enterprise tools. [S07]
- Administration: reviewers cite missing SCIM provisioning, painful manual user management, and a lack of bulk recognition editing. [S10, S24]
- Data portability: a reviewer reported that migration off Rivally was difficult because analytics exports are CSV-only. [S20]
- Rewards catalog: a reviewer reported that Rivally’s EMEA rewards catalog is thinner than its US catalog. [S14]

## Objections and responses

- Objection: “Rivally is better for European teams.”
  - Response: Rivally has documented strengths in distributed EU teams, multilingual support, and EU data residency. Position Bonusly around the buyer’s required analytics depth and administrative scale, which were cited as reasons one 800-seat prospect chose Bonusly. [S12, S15, S25]

- Objection: “Rivally is easier to deploy.”
  - Response: A reviewer reported setup in under a week, so validate whether the prospect’s implementation requirements are similarly simple. For larger deployments, probe SCIM, user-management, bulk-editing, and analytics requirements. [S04, S10, S24]

- Objection: “Rivally has Slack integration.”
  - Response: The old-card claim that Rivally lacks Slack integration is not supported and is contradicted by a reviewer who said the Slack integration worked out of the box. [S04]

- Objection: “Rivally has strong engagement.”
  - Response: Acknowledge that reviewers praise its recognition feed, then differentiate on analytics, reporting, administration, and data portability. [S02, S07, S16, S20]

- Objection: “Rivally is cheaper.”
  - Response: Current public pricing is listed at $7 per user/month with annual billing required. Deal-specific pricing has varied, including a $6.50 quote in June and a reported 15% discount on a three-year term in August. Compare total requirements and commercial terms rather than headline price alone. [S13, S17, S18]

## Recent changes

- Rivally launched the Rivally Pulse engagement-survey add-on on 2026-03-05. [S06]
- Rivally hired a former Workday VP EMEA to lead European expansion on 2026-05-09. [S11]
- Rivally opened a Dublin office and announced EU data residency as generally available on 2026-07-01. [S15]
- Rivally updated Recognition Starter pricing to $7 per user/month on 2026-08-12. [S17]
- Rivally announced Microsoft Teams app v2 in public preview on 2026-08-20. [S19]
- Rivally Pulse exited beta and became a separately priced, non-bundled add-on on 2026-09-01. [S23]

## Our 12-month win/loss record against Rivally

The supplied deal file contains 20 deals from 2025-09 through 2026-08: 13 wins and 7 losses.

Arithmetic: 13 wins + 7 losses = 20 total deals.  
Win rate: 13 ÷ 20 = 65%.  
Loss rate: 7 ÷ 20 = 35%.

Source limitation: `deals_with_competitor.csv` does not contain `snippet_id` values, so these deal-record claims cannot be cited with snippet IDs.

Wins:
- Deal-A9FD43
- Deal-7AA785
- Deal-44C524
- Deal-0D0CD6
- Deal-D5B790
- Deal-5C636E
- Deal-67BE14
- Deal-1B6969
- Deal-F03E7B
- Deal-072E31
- Deal-F65C8F
- Deal-E46EAB
- Deal-1D2392

Losses:
- Deal-7767F5
- Deal-5645A5
- Deal-C6FFAA
- Deal-D263E0
- Deal-935746
- Deal-9066A6
- Deal-72A02F

## Old-card claims that are unverified or corrected

- “Rivally was acquired by WorkHuman in 2025”: unverified; no supplied snippet supports this claim.
- “Rivally lacks a Slack integration”: corrected; contradicted by S04.
- “Pricing starts at $5 per user/month”: outdated; earlier pricing sources showed $5, but the newer public pricing source lists $7 per user/month. [S03, S08, S17]

New Logo Nurture
- Sent: 1,386; open rate: 490 ÷ 1,386 = 35.35%; reply rate: 90 ÷ 1,386 = 6.49%; meeting rate: 27 ÷ 1,386 = 1.95%.
- Weakest step: Step 3 (18 ÷ 428 = 4.21% reply).
- Change: Rewrite Step 3 with a single, lower-friction CTA.

Expansion Nurture
- Sent: 875; open rate: 565 ÷ 875 = 64.57%; reply rate: 59 ÷ 875 = 6.74%; meeting rate: 12 ÷ 875 = 1.37%.
- Weakest step: Step 3 (12 ÷ 275 = 4.36% reply).
- Change: Replace Step 3 with a concise expansion-specific proof point and CTA.

Cold Outbound - HR Leaders
- Sent: 1,785; open rate: 545 ÷ 1,785 = 30.53%; reply rate: 8 ÷ 1,785 = 0.45%; meeting rate: 0 ÷ 1,785 = 0.00%.
- Weakest step: Step 3 (1 ÷ 590 = 0.17% reply).
- Change: Stop the current sequence and rebuild Step 1 around tighter HR-leader segmentation.

Cold Outbound - People Ops
- Sent: 1,163; open rate: 340 ÷ 1,163 = 29.24%; reply rate: 29 ÷ 1,163 = 2.49%; meeting rate: 6 ÷ 1,163 = 0.52%.
- Weakest step: Step 3 (6 ÷ 377 = 1.59% reply).
- Change: Replace Step 3 with a direct objection-handling message.

Tracking error
- Expansion Nurture Step 2: 340 opened > 300 sent.

Reply rates under 2% and failure mode
- Cold Outbound - HR Leaders Steps 1–3: 0.83%, 0.34%, and 0.17%; failure mode is low engagement that worsens with sequence progression.
- Cold Outbound - People Ops Step 3: 1.59%; failure mode is follow-up fatigue or insufficient CTA relevance.

Audience overlap
- Duplicate contact keys appear across sequences, including CT-000301 (Expansion Nurture/New Logo Nurture), CT-000849, CT-000884, CT-000908, CT-001097, CT-001101, CT-001103, CT-001105, CT-001130, CT-001153, CT-001159, CT-001217, CT-001227, CT-001236, CT-001255, CT-001258, CT-001277, CT-001285, CT-001311, and CT-001345 across the two cold-outbound sequences.

Fix first: Cold Outbound - HR Leaders, because its overall reply rate is 0.45% and meeting rate is 0%.

Q3-2026 weekly marketing goals update (66 of 92 days elapsed; pace benchmark = 66/92 = 71.7% of target):

- SQMs: QTD actual 230; target 300; delta = 230 − 300 = -70; pace: ahead, since 230 > 300 × 66/92 = 215.2.
- SQOs: QTD actual 84; target 120; delta = 84 − 120 = -36; pace: behind, since 84 < 120 × 66/92 = 86.1.
- DS2s: QTD actual 40; target 75; delta = 40 − 75 = -35; pace: behind, since 40 < 75 × 66/92 = 53.8.
- Closed-lost MIA rate: QTD actual = 5 ÷ 25 = 20.0%; target 10.0%; delta = 20.0% − 10.0% = +10.0 percentage points; pace: behind, since 20.0% is above the 7.2% pace benchmark (10.0% × 66/92).
- Same-quarter close count: QTD actual 10; target 20; delta = 10 − 20 = -10; pace: behind, since 10 < 20 × 66/92 = 14.3.
- Active pipeline coverage against target: QTD actual = $3,000,000; target = $4,000,000; delta = $3,000,000 − $4,000,000 = -$1,000,000; pace: ahead, since $3,000,000 > $4,000,000 × 66/92 = $2,869,565.22. Current coverage is 3,000,000 ÷ 4,000,000 = 75.0% of target.

This week’s movement cannot be determined from the provided data because no week-over-week actuals or changes were provided.

Decision: treat Q3 forecast as provisional at $115,976.75: $44,729 + (35% × $203,565 = $71,247.75), from 7 COMMIT and 24 BEST_CASE deals; 23 PIPELINE deals contribute $0. 32 deals totaling $227,575 are excluded after 2026-09-30, including COMMIT Deal-D348E1 ($13,770) and 9 BEST_CASE deals ($28,240). Owner is blank on 85/86 and why-buys on 71/86, including all 7 COMMIT deals, so the forecast cannot be rep- or quota-validated and committed revenue lacks documented purchase rationale.

Subject: Following up on the 150-seat pricing

Hi,

I’m following up on my August 5 recap of the July 28 demo, including pricing for 150 seats. You had shown strong interest in automated milestone awards and the points catalog, so I wanted to check whether this is still under consideration.

Could you reply with a quick yes or no on whether this remains a priority?

Best,  
Alex

Marketing delivered 46 SQMs against a weekly target of 52, finishing 6 below target (52 − 46 = 6). Webinar generated 18 SQMs, representing 18 ÷ 46 = 39.1% of the total, while paid search held at $150 per SQM.

Sales converted 14 SQOs and set 9 DS2 meetings. The team created $310,000 in new pipeline and closed 3 same-quarter deals during the week.

CS saved 2 renewals this week, with team NPS moving to 61. Three open red-flag accounts are heading into next week, keeping focused follow-through important.

PLG added 412 new signups, with activation at 31%. Another 38 companies reached the aha moment of 10 recognition gives—an encouraging signal of meaningful product engagement.

Partner Digest | 2026-08-24 to 2026-09-04

- Apex Rewards Co — Active: 2 sourced deals totaling $275,000. Arithmetic: $180,000 + $95,000 = $275,000. Deal-DDAAF2 and Deal-2CF33 are both in DS1. Co-webinar is locked for 09-15.
- HRCloud Partners — Active: 1 sourced deal totaling $140,000. Arithmetic: $140,000 = $140,000. Deal-F1CDA5 moved to DS2 after completing the security review.
- CultureBridge — Active: 2 sourced deals totaling $135,000. Arithmetic: $60,000 + $75,000 = $135,000. Deal-096E1D and Deal-067213 are both early stage.
- WorkWell Group — Active: 0 sourced deals totaling $0 this period. Q4 joint-playbook restart is under discussion; planning call booked for 09-09.
- Recogniq — Quiet this period; no sourced pipeline reported.
- KudosWave — Quiet this period; no sourced pipeline reported.
- PeopleFirst Advisors — Quiet this period; no sourced pipeline reported.
- TotalPerk — Quiet this period; no sourced pipeline reported.

Total partner-sourced pipeline: 5 deals totaling $550,000. Arithmetic: 2 + 1 + 2 = 5 deals; $275,000 + $140,000 + $135,000 = $550,000.

Q1. Yes. Customer data is encrypted at rest using AES-256. [P1]

Q2. Yes. Data in transit is encrypted with TLS 1.2 or higher. [P1]

Q3. Yes. Bonusly maintains a SOC 2 Type II report, renewed annually. It is available to prospects under NDA. [P2]

Q4. Customer data is retained for the duration of the contract plus 90 days after contract termination, then deleted from production systems. [P3]

Q5. The current subprocessor list is published at trust.bonusly.com. Customers receive 30 days’ notice before a new subprocessor is added. [P4]

Q6. Yes. SAML 2.0 single sign-on is available on the Enterprise plan. [P5]

Q7. Production databases are backed up daily. Backups are encrypted and retained for 35 days. [P6]

Q8. Unanswerable from the provided excerpts [P1–P8]. The ISO 27001 certification status would require an ISO certification document or compliance statement.

Q9. Unanswerable from the provided excerpts [P1–P8]. The contractual uptime SLA percentage would require the applicable contract or service-level agreement.

Q10. Unanswerable from the provided excerpts [P1–P8]. Whether Bonusly will sign a HIPAA Business Associate Agreement would require the applicable legal or contractual terms.

1. ALWAYS-trigger overlap/duplication

- WARNING — MERGE — `comms-drafter` ↔ `email-drafter`
  - Both trigger on “write me an email,” “draft a follow-up,” “help me reply,” “what should I say,” “bump email,” contract follow-ups, renewals, QBRs, onboarding, and customer-facing communications.
  - Proposal: Keep `email-drafter` as the email-specific skill and narrow `comms-drafter` to non-email communications such as support, Intercom, partner, and rewards messages.

- WARNING — REVIEW — `deal-strategy-coach` ↔ `email-drafter`
  - Both cover manager-to-prospect emails, stalled-deal re-engagement, pricing follow-up, and requests to draft messaging.
  - Proposal: Make `deal-strategy-coach` diagnostic only and route all drafting to `email-drafter`.

- WARNING — MERGE — `pipeline-intelligence-report` ↔ `weekly-pipeline-report`
  - Both trigger on “pipeline report,” “pipeline update,” “pipeline summary,” “what does pipeline look like,” and pipeline performance requests.
  - Proposal: Keep `pipeline-intelligence-report` for scored deal-level intelligence and `weekly-pipeline-report` for weekly demand-generation metrics; remove shared generic phrases from both descriptions.

- WARNING — REVIEW — `next-to-close` ↔ `pipeline-intelligence-report`
  - Both can trigger on which active deals are likely to close and pipeline/forecast questions.
  - Proposal: Reserve `next-to-close` for a short ranked shortlist and `pipeline-intelligence-report` for the full scored pipeline; remove generic “pipeline” triggers from `next-to-close`.

- WARNING — TRIM_DESC — `model-selection` ↔ every other `ALWAYS` skill
  - `model-selection` says “ALWAYS run this skill at the start of every task,” while the other skills also claim unconditional or universal triggering.
  - Proposal: Make `model-selection` an orchestration policy rather than a competing user-facing trigger.

2. Circular delegation chain

- CRITICAL — MERGE — `comms-drafter` → `deal-strategy-coach` → `email-drafter` → `deal-strategy-coach`
  - `comms-drafter` routes deep strategy to `deal-strategy-coach`.
  - `deal-strategy-coach` routes manager emails to `email-drafter`.
  - `email-drafter` routes strategy and coaching back to `deal-strategy-coach`.
  - Proposal: Make `deal-strategy-coach` the diagnostic parent and `email-drafter` the terminal drafting skill. Remove the reverse handoff from `email-drafter` or make it informational only.

3. Dangling delegation targets

- CRITICAL — REVIEW — `bonusly-brand`
  - Referenced by `comms-drafter` and `email-drafter`; no corresponding file or manifest row exists.
  - Proposal: Add the skill to the manifest or remove the mandatory invocation.

- CRITICAL — REVIEW — `prospect-research-multithreading`
  - Referenced by `comms-drafter`, `deal-strategy-coach`, and `email-drafter`; no corresponding file or manifest row exists.
  - Proposal: Add the skill or replace the handoff with an existing supported workflow.

- WARNING — REVIEW — Specialist targets referenced by `analysis-validator`
  - Missing targets:
    - `bonusly-data-questions`
    - `bonusly-product-questions`
    - `bonusly-business-reporting-questions`
    - `bonusly-rewards-questions`
    - `bonusly-ppp-questions`
    - `bonusly-feature-flag-questions`
    - `bonusly-deal-desk-questions`
    - `bonusly-datadog-questions`
  - Proposal: Register these skills or remove the delegation table.

- WARNING — REVIEW — `skill-orchestrator`
  - Referenced in `analysis-validator` as a cascading file/system component, but no corresponding file or manifest row exists.
  - Proposal: Confirm whether it is an external system component; otherwise remove the reference or add it to the manifest.

4. Version conflict

- WARNING — UPDATE_BODY — `analysis-validator`
  - The skill identifies itself as `v3.6` in the header and changelog, but its required validation-trail template says `analysis-validator v3.2`.
  - Proposal: `v3.6` should survive. Update the embedded trail template from `v3.2` to `v3.6`.

5. Manifest descriptions over 1,024 characters

- INFO — REVIEW — Count: `0`
- Arithmetic: `14` manifest rows checked; `0` descriptions exceed `1,024` characters.
- Longest declared description: `1,006` characters.

6. Hardcoded page IDs, dates, or person names in skill bodies

- WARNING — UPDATE_BODY — `analysis-validator`
  - Hardcoded dates: `April 26, 2026`, `May 4, 2026`, `May 9, 2026`.
  - Hardcoded IDs: HubSpot owner IDs, deal-stage IDs, page/system references, and other numeric identifiers.
  - Hardcoded person names include `Manish`, `Amani Phipps`, `Alaina Loori`, `Dana Mercer`, `Gavin Porter`, and the listed AE, CSM, RevOps, and demand-generation roster.
  - Proposal: Move volatile dates, IDs, and personnel mappings to live references or runtime lookups.

- WARNING — UPDATE_BODY — `closed-lost-analysis`
  - Hardcoded date reference: `May 2026`.
  - Hardcoded company/deal examples include `Softheon`, `Estee Lauder`, `LIFTOFF`, `Nestlé`, `MinIO`, `Aurora Innovation`, `GCash`, `Ozinga`, `Ethos Cannabis`, and `StickerYou`.
  - Proposal: Label examples as historical fixtures or move them to a reference file; do not present them as current system facts.

- WARNING — UPDATE_BODY — `deal-strategy-coach`
  - Hardcoded Confluence page URL and page ID: `2257879045`.
  - Hardcoded pricing and ICP reference dates/values: `2026`, `April 2026`, and Q2/Q3 operational references.
  - Proposal: Replace page identifiers and time-sensitive commercial guidance with live references or versioned reference files.

- WARNING — UPDATE_BODY — `partner-digest`
  - Hardcoded Confluence cloud, space, folder, and page IDs, including `2286616609`, `2286321666`, `2265382925`, `2236940297`, `2237825028`, `2239365136`, and `2238283777`.
  - Hardcoded dates include `May 16, 2026`, `May 17, 2026`, and `June 2, 2026`.
  - Hardcoded person names include `Amani Phipps`, `Kelli`, `Jen Lee`, `Hani`, `Bryce`, and `Sara`.
  - Proposal: Resolve destinations, dates, and ownership dynamically at runtime.

- WARNING — UPDATE_BODY — `pipeline-intelligence-report`
  - Hardcoded HubSpot organization ID `1973303`, owner IDs, stage IDs, output paths, and May 2026 version/date references.
  - Hardcoded person names include `Bryce Harmon`, `Dana Mercer`, `Cole Ingram`, `Alex Franklin`, and `Gavin Porter`.
  - Proposal: Keep stable stage constants only if centrally managed; dynamically resolve owners, IDs, dates, and output locations.

- WARNING — UPDATE_BODY — `sales-forecast`
  - Hardcoded person name: `Alaina`.
  - Hardcoded dates and quarter references include `Q2`, `Q3`, `2026`, `July 9, 2026`, and `April 1 – June 30, 2026`.
  - Hardcoded Confluence page, space, cloud, and parent IDs are present.
  - Proposal: Derive the active quarter, dates, owner, and page destination at runtime.

- WARNING — UPDATE_BODY — `signalforge-feedback`
  - Hardcoded Confluence page IDs `2295136266` and `2234417154`, cloud/space IDs, and a fixed feedback-log URL.
  - Proposal: Centralize destination configuration rather than embedding IDs in the skill body.

- WARNING — UPDATE_BODY — `stale-pipeline-report`
  - Hardcoded Slack channel ID `C0561C1JCPJ`.
  - Hardcoded dates in the changelog: `June 10, 2026`.
  - Proposal: Resolve the notification channel and execution date dynamically.

- WARNING — UPDATE_BODY — `weekly-pipeline-report`
  - Hardcoded person name: `Ben Lavin`.
  - Hardcoded dates: `April 1 – June 30, 2026`, `Q2`, and `2026`.
  - Hardcoded spreadsheet IDs are also embedded.
  - Proposal: Resolve report owner, quarter, dates, and spreadsheet sources at runtime.

7. Manifest drift

- INFO — REVIEW — Files with no manifest row: `0`
- INFO — REVIEW — Manifest rows with no corresponding file: `0`
- Arithmetic: `14` manifest rows and `14` supplied skill files; all names match exactly.
- Proposal: No manifest-drift change required.

1. Acknowledge the PagerDuty alert and take incident command (IC).
   - Exact action: PagerDuty alert fired for reward-worker queue depth > 10k; acknowledge it and take IC.
   - Who: Bryce Harmon
   - Success verification: Bryce Harmon stated, “Acknowledging, taking IC.”
   - Rollback: Not applicable; no state change.
   - Trace: [M01]

2. Check the reward queue depth.
   - Exact command: `bundle exec rake sidekiq:queue_depth`
   - Who: Farid Osman
   - Success verification: The reward queue was reported at 48,213 pending jobs; normal is under 500.
   - Rollback: Not applicable; diagnostic command only.
   - Trace: [M02]

3. Inspect the dead set.
   - Exact action: Inspect the dead set for failed jobs.
   - Who: Farid Osman
   - Success verification: The dead set contained 112 jobs, all `Redis::TimeoutError` from around 13:58.
   - Rollback: Not applicable; diagnostic action only.
   - Trace: [M03]

4. Pause reward enqueueing.
   - Exact command: `bin/rails runner 'FeatureFlag.disable(:auto_recognition_enqueue)'`
   - Who: Farid Osman
   - Success verification: The thread does not state how the disabled flag was verified; needs confirmation.
   - Rollback: `bin/rails runner 'FeatureFlag.enable(:auto_recognition_enqueue)'`
   - Trace: [M04]

5. Clear the dead set.
   - Exact action: Clear out the dead set.
   - Who: Elena Sinclair
   - Success verification: The thread does not provide a verification step; needs confirmation.
   - Rollback: Not provided; needs confirmation.
   - Trace: [M05]

6. Scale the reward workers up.
   - Exact command: `kubectl scale deployment/reward-worker --replicas=6`
   - Who: Bryce Harmon
   - State before change: 3 replicas.
   - Success verification: The thread does not provide direct verification of the replica count; needs confirmation.
   - Rollback: `kubectl scale deployment/reward-worker --replicas=3`
   - Trace: [M06]

7. Monitor the reward queue.
   - Exact action: Monitor queue depth and its trend.
   - Who: Farid Osman
   - Success verification: Queue depth decreased to 9,400 and was falling at approximately 1,200 jobs per minute.
   - Rollback: Not applicable; monitoring action only.
   - Trace: [M07]

8. Verify the queue depth and error rate.
   - Exact command: `bundle exec rake sidekiq:queue_depth`
   - Who: Cole Ingram
   - Success verification: The command returned 0, and the Datadog error rate was back to baseline.
   - Rollback: Not applicable; verification command only.
   - Trace: [M08]

9. Re-enable reward enqueueing.
   - Exact command: `bin/rails runner 'FeatureFlag.enable(:auto_recognition_enqueue)'`
   - Who: Bryce Harmon
   - Success verification: 40 new jobs processed cleanly in the next 3 minutes.
   - Rollback: Not provided; needs confirmation.
   - Trace: [M09]

10. Scale the reward workers back down.
    - Exact command: `kubectl scale deployment/reward-worker --replicas=3`
    - Who: Bryce Harmon
    - State before change: 6 replicas.
    - Success verification: Queue remained stable at 0; incident was declared resolved.
    - Rollback: Not provided; needs confirmation.
    - Trace: [M10]

First error:
- 2026-09-03T14:01:12Z
- Service: `reward-service`
- Error: `Redis::TimeoutError` connecting to `redis-primary:6379`, timed out after 5 seconds.

Failure cascade:
1. `reward-service` cannot reach Redis.
2. `RewardGiveJob` retries fail in `reward-service` at 14:01:20Z, 14:01:30Z, and 14:01:40Z.
3. `sidekiq` reports `RewardGiveJob` failures and schedules retries at 14:01:40Z and 14:02:28Z.
4. The `reward` queue exceeds 10,000 jobs at 14:02:30Z.
5. `api-gateway` returns 502 upstream timeouts calling `reward-service` beginning at 14:03:05Z.
6. `web-app` reports Give form submission failures caused by the upstream 502 beginning at 14:03:30Z.
7. Redis connectivity is restored at 14:22:10Z, and the queue falls below 500 at 14:24:45Z.

Service and job involved:
- Primary failing service: `reward-service`
- Primary job: `RewardGiveJob`
- Queue/retry service: `sidekiq`
- Additional affected job: `RecognitionDigestJob`, with Redis failures recorded in `sidekiq_jobs.csv` from 14:02:36Z through 14:05:50Z.
- Downstream services: `api-gateway` and `web-app`

Datadog query to confirm the first error:
```text
service:reward-service status:error "Redis::TimeoutError" @timestamp:[2026-09-03T14:01:00Z TO 2026-09-03T14:02:00Z]
```

What the logs do not show:
- The root cause of the Redis timeout.
- Redis server-side logs, health metrics, capacity, or network evidence.
- Whether any rewards were duplicated, lost, or successfully processed after retries.
- The exact number of affected `RewardGiveJob` executions beyond the listed records.
- Request IDs linking individual web submissions to jobs.
- Why `RecognitionDigestJob` was also affected beyond the shared Redis error.
- Whether the PostgreSQL checkpoint messages were related; the provided logs show no direct connection.

- recognition_streaks_v2 — ON; controls recording a recognition streak when a give occurs. Target: `segment:beta_companies`. Export count: 42 companies.
- points_budget_guardrails — ON; controls enforcement of giver points budgets. Target: `all_companies`. Export count: 220 companies.
- slack_dm_nudges — ON; controls sending Slack direct-message nudges. Target: `segment:region_na`. Export count: 87 companies.
- redeem_flow_redesign — OFF; controls whether the company receives the V2 redeem flow instead of the V1 flow. Target: `targeted_list`. Export count: 12 companies.
- analytics_dashboard_v3 — ON; controls use of the V3 analytics dashboard. Target: `segment:tier_three`. Export count: 65 companies.
- ms_teams_app_v2 — OFF; controls installation of the V2 Microsoft Teams app. Target: `targeted_list`. Export count: 9 companies.
- legacy_give_modal — OFF; controls the legacy give modal. Target: `segment:legacy_plan`. Export count: 14 companies. No code reference in the excerpt.
- survey_boosters_q3 — ON; controls survey boosters for Q3. Target: `segment:legacy_plan`. Export count: 7 companies. No code reference in the excerpt.
- paused_offboard_cleanup — OFF; no code reference in the excerpt. No targeting rules and no targets. Export count: 0 companies.

Counts from the export:
- ON assignments: 42 + 220 + 87 + 65 + 7 = 421
- OFF assignments: 12 + 9 + 14 + 0 = 35
- Total flag-company assignments: 421 + 35 = 456

These are flag-company assignments, not a unique-company total; the export does not provide enough information to deduplicate companies across flags.

NDA-1 — GREEN: Standard mutual confidentiality, with complete carve-outs and no restrictive covenants: “Carve-outs: information that (a) is or becomes publicly available through no breach, (b) was known prior to disclosure, (c) is received from a third party without duty of confidence, (d) is independently developed, or (e) must be disclosed by law or court order.” Delaware governing law and the two-year term plus three-year survival are not unusual enough to require escalation.

NDA-2 — YELLOW: Counsel review required because it contains an embedded employee non-solicit extending beyond the NDA term: “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.” The three-year term and Delaware governing law are otherwise standard.

NDA-3 — RED: Full legal review required because it imposes a broad three-year post-effective-date 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”—and also lacks stated confidentiality carve-outs: “No confidentiality carve-outs are stated in this Agreement.” The one-way structure and exclusive Republic of Ireland jurisdiction further increase legal risk.