Mean 0.941 · 29/40 perfect tests · $7.59 total · modalities in: text, image, file · out: text · each card: the prompt → the correct answer (gold) → this model's actual answer
Modalities in means what you can send this model: text, images, files, video, or audio. Modalities out means what it can send back. Bench tasks feed text extracts, so modalities do not change the score. They are here so you know what this model can handle in real work.
Definitions: DS2+ includes open deals at DS2, DS3, DS4, or DS5. A why-buys is non-compliant if blank, under 15 characters, or a placeholder; LONG(n) counts as substantive. A regression means a recorded earlier-stage entry timestamp is later than a recorded later-stage entry timestamp; equal dates are not regressions. Why-buys non-compliance: - Overall: 101 / 124 = 81.5% - Bryce Harmon: 15 / 18 = 83.3% - Alex Franklin: 48 / 61 = 78.7% - Dana Mercer: 18 / 22 = 81.8% - Cole Ingram: 19 / 22 = 86.4% - Farid Osman: 1 / 1 = 100.0% No DS1 timestamp: 0 deals. Regressed stage timestamps: 0 deals. Process fixes: 1. Require a substantive why-buys before advancement to DS2; reject blanks and placeholders. 2. Validate DS1 timestamp capture when every deal is created or enters DS1. 3. Alert on out-of-order stage timestamps and route exceptions for correction.
All 156 open deals resolve to a name in the owners table. Arithmetic by owner: | Resolved owner (owner ID) | Deals | Pipeline amount | |---|---:|---:| | Bryce Harmon (119337721) | 35 | $66,676 + $987,468 = $1,054,144 | | Alex Franklin (84342457) | 67 | $69,304 + $555,006 = $624,310 | | Dana Mercer (83155923) | 24 | $56,470 + $284,725 = $341,195 | | Cole Ingram (83155924) | 22 | $4,090 + $284,071.43 = $288,161.43 | | Farid Osman (716654662) | 7 | $1,249 + $1 + $1 + $1 + $2,880 + $1 + $1 = $4,134 | | Elena Sinclair (701163055) | 1 | $2,100 | Resolved count: 35 + 67 + 24 + 22 + 7 + 1 = 156. Total resolved pipeline: $1,054,144 + $624,310 + $341,195 + $288,161.43 + $4,134 + $2,100 = $2,314,044.43. Unmatched owner IDs: none. Open deals mapped to archived/deactivated owners: none. The archived owners in the owners table—Gavin Porter (1520255671) and Hugo Lindqvist (77260721)—own no deals in this extract.
(a) Orphans: 30 of 67 Gong rows have no matching deal ID in deals_open (67 − 37 = 30). Sample aliases: Deal-8FA85D, Deal-8FC3F9, Deal-3B7945, Deal-42B265, Deal-9CCC42. A missing match in this open-deals list does not establish why the deal is absent. (b) Duplicate conversation keys: 0 rows; no calls_90d value exceeds distinct_conversation_keys. (c) DS3-or-later open-deal call coverage: 25 of 85 = 29.4%.
```sql
-- The catalog does not provide a recognition-event table or giver identifier,
-- so unique givers and recognition count cannot be calculated.
-- It also does not document the company key or event timestamp needed to
-- assign redemption records to each customer's first calendar month.
SELECT
'Cannot calculate the requested metrics from the provided catalog.' AS missing_data;
```
The extract has no deals file. Owner, stage, amount, close date, and why-buys completeness cannot be calculated. Pipeline amount at stake also cannot be calculated, so the final fixes cannot be ranked by that measure. Completeness (populated rows ÷ rows supplied): | Object | Field | Arithmetic | Complete | |---|---|---:|---:| | Companies | Industry | 34 ÷ 34 | 100.0% | | Companies | Employee count | 25 ÷ 34 | 73.5% | | Companies | HQ country | 28 ÷ 34 | 82.4% | | Contacts | Email, nonblank | 52 ÷ 52 | 100.0% | | Contacts | Email, syntactically valid | 49 ÷ 52 | 94.2% | | Contacts | Title | 39 ÷ 52 | 75.0% | | Contacts | Persona | 37 ÷ 52 | 71.2% | Duplicate company clusters, identified by shared domain (no company-name field was supplied): - `acme-corp.com`: `C-0A092931` and `C-0A092932`. Proposed survivor: `C-0A092931` (lower alias as a provisional tie-breaker, not evidence of a better record). Reconcile employee counts of 500 versus 510 before merging. - `globex.io`: `C-0A092933` and `C-0A092934`. Proposed survivor: `C-0A092933` (same provisional tie-breaker). Reconcile `SaaS` versus `Technology` before merging. Invalid emails: `CT-0010` (`user0@`), `CT-0080` (`user0@`), and `CT-0192` (`user2@`). Request verified addresses; the contact domain alone does not establish the missing address. Domain mismatch: `CT-0011` has `user1@other-domain.com`, while its contact domain and `C-66D1FC` company domain are `66d1fc.com`. Verify the association or address; do not rewrite it automatically. Enrichment-backed missing-field fills, matched by domain: - Employee count → 400: `C-EC3025`, `C-96039F`, `C-44EA29`, `C-D04904`, `C-B23205`, `C-60C75F`, `C-7BBDFA`, `C-50D386`. - No missing HQ country can be filled: the matching enrichment rows for `C-2D1F1B`, `C-D73B89`, `C-44EA29`, `C-D04904`, and `C-2C60E5` also have blank countries. `C-EE9FFB` has no matching enrichment row. - `C-93C8BF` has a missing employee count and no matching enrichment row. Leave it blank. Populated-value disagreements and source recommendation: - For `C-66D1FC`, `C-EC3025`, `C-44EA29`, `C-92D97D`, `C-D04904`, `C-77A95A`, `C-AA8DDA`, `C-B25F40`, `C-60C75F`, and `C-425E2A`, CRM industry is `tech`, `Technology`, or `Tech `; enrichment says `Computer Software`. Retain the populated CRM value pending a taxonomy decision; the enrichment label is more specific, not proof that CRM is wrong. - CRM country `US` or `USA` versus enrichment `United States` occurs for `C-66D1FC`, `C-950043`, `C-EC3025`, `C-96039F`, `C-77A95A`, `C-B23205`, `C-E51FB7`, `C-D0662E`, `C-425E2A`, and `C-2D7423`. These are label differences, not conflicting countries. Recommend a single standardized country format; retain the original CRM values until that convention is chosen. - Separately, the duplicate pairs disagree within CRM on employee count (`C-0A092931` 500; `C-0A092932` 510) and industry (`C-0A092933` `SaaS`; `C-0A092934` `Technology`). Enrichment has no matching rows to resolve either disagreement. Ten fixes to queue — **unranked**, because no deal amounts or deal-to-company links were supplied: 1. Obtain the deals extract with owner, stage, amount, close date, why-buys, and company association; then calculate deal-field completeness and amount at stake. 2. Review the `acme-corp.com` duplicate cluster and its 500/510 employee-count conflict before merging. 3. Review the `globex.io` duplicate cluster and its `SaaS`/`Technology` conflict before merging. 4. Verify the email for `CT-0010`. 5. Verify the email for `CT-0080`. 6. Verify the email for `CT-0192`. 7. Investigate the email/company-domain mismatch for `CT-0011`. 8. Fill employee count on the eight enrichment-matched companies listed above. 9. Source, rather than infer, the remaining missing company employee count and six missing HQ countries. 10. Collect missing contact titles (13 of 52) and personas (15 of 52); do not infer either from another contact’s record.
Classifications below use only the supplied tag and free-text. “Other / unknown” means the text does not establish a primary cause; MIA is an outcome, not a cause. No supplied reason says a champion left. | Category / side | Deals | |---|---| | Pricing / buyer | Deal-7ED004, Deal-7B2236, Deal-C33D91, Deal-8A119B | | Competitor / buyer | Deal-F7F635, Deal-F97C37, Deal-422BA6, Deal-DDAB52, Deal-ACE061, Deal-2D2F8D, Deal-1BCA50, Deal-A2C349, Deal-C7156E, Deal-8A0992, Deal-D0C698, Deal-EECC02, Deal-47F1A1, Deal-BF2A98, Deal-1E7DA9, Deal-286F9C, Deal-369281, Deal-9FCD0D, Deal-64B19A | | Competitor / unknown | Deal-381C8C, Deal-F1E8A6, Deal-0F96AA, Deal-7CC678 | | No decision / buyer | Deal-13E9CF, Deal-E74A73, Deal-8E27DA, Deal-FAC17C, Deal-50E5D8, Deal-413C56, Deal-2A292B, Deal-7FBAC6, Deal-F325A5, Deal-ABD14C | | Timing / buyer | Deal-DB0AAC, Deal-91A056, Deal-29326C, Deal-831B7B, Deal-39E25C, Deal-B3ABED, Deal-ED9AE7, Deal-B6AC09, Deal-E6E80A, Deal-B038F0, Deal-175756, Deal-BB78F3, Deal-15DA99, Deal-F4AF5D, Deal-79B7A1, Deal-9F176A, Deal-8A0992, Deal-69CF3D, Deal-ECBF89, Deal-D1A623, Deal-FEDBCB, Deal-DAFB82, Deal-2FEDDB | | Product gap / Bonusly | Deal-9048EB, Deal-3618CC, Deal-5AD03E, Deal-981AD4, Deal-DC77FE | | Other / unknown | Deal-AC944F, Deal-214060, Deal-5DB9B0, Deal-21B045, Deal-988493, Deal-F308CA, Deal-70F704, Deal-4664E1, Deal-D48E0B, Deal-583ADB, Deal-E0441F, Deal-7CB44D, Deal-AFA56C, Deal-D1AABF, Deal-2BBA21, Deal-386F6E, Deal-55867E, Deal-3F86A0, Deal-096750, Deal-79E61A, Deal-AE7C4E, Deal-DAB4F1, Deal-B4B50F, Deal-5885B9 | Correction to the table: Deal-8A0992 appears twice. Its Nectar exit fee and October 2027 contract end make timing the primary category, not competitor. Removing it from competitor yields the counts below. Category counts: pricing 4 + competitor 22 + no decision 10 + timing 23 + product gap 5 + champion left 0 + other 24 = 88. The supplied CSV has 90 rows; the remaining two are Deal-242273 and Deal-5E64CE. Deal-242273 is competitor / buyer (the text describes a vendor differentiator, not a confirmed Bonusly product inability). Deal-5E64CE is timing / buyer (Nectar exit fee and contract end). Final counts: pricing 4 + competitor 23 + no decision 10 + timing 24 + product gap 5 + champion left 0 + other 24 = 90. Side split: buyer 57 + Bonusly 5 + unknown 28 = 90. Clear tag–text disagreements: 4 — Deal-8E27DA (Feature Request vs. not wanting R&R), Deal-9048EB (MIA vs. stated bad fit and feature gaps), Deal-5E64CE (doing nothing/not a priority/cost vs. an identified contract-end timing constraint), and Deal-5AD03E (Competitor vs. stated budget-access requirement). This excludes vague tags or text that merely lacks detail. Two patterns worth acting on: 1. Secure specific re-engagement dates for timing losses: 24 deals, including Deal-91A056, Deal-E6E80A, and Deal-5E64CE, describe a later window or contract constraint. 2. Capture the actual competitive decision criterion: 23 competitor losses, but several reasons only say “another direction” or give no specifics (Deal-381C8C, Deal-F1E8A6, Deal-7CC678). The more specific entries point to differentiated offerings or requirements (Deal-F97C37, Deal-422BA6, Deal-DC77FE); the vague entries cannot support a targeted response.
{"tier_counts":{"LOCK":3,"ACTION":20,"BUILD":31,"REVIVE":22,"WATCH":45,"RISKY":35},"tier_examples":{"LOCK":["Deal-D348E1","Deal-C26D20","Deal-403845"],"ACTION":["Deal-25F752","Deal-944310","Deal-3974EB"],"BUILD":["Deal-6787C2","Deal-A5E80A","Deal-499BF6"],"REVIVE":["Deal-2D1F1B","Deal-66D1FC","Deal-950043"],"WATCH":["Deal-C9C286","Deal-332637","Deal-E25A09"],"RISKY":["Deal-E53952","Deal-5408B0","Deal-9AAE5F"]},"risky_deals":["Deal-E53952","Deal-5408B0","Deal-9AAE5F","Deal-547B2B","Deal-B7EBD1","Deal-A2B47C","Deal-2465CE","Deal-C61CF7","Deal-62D607","Deal-584EE5","Deal-C6D97A","Deal-7B3B0F","Deal-F9A08A","Deal-0660B4","Deal-FD9F4E","Deal-BA571A","Deal-FC22A3","Deal-7BBDFA","Deal-60C2C2","Deal-4A13AD","Deal-8AD4A5","Deal-15D24F","Deal-9D0060","Deal-690476","Deal-635B8E","Deal-ED725A","Deal-55164C","Deal-3BA5EA","Deal-5FDCE4","Deal-F336B6","Deal-5EED42","Deal-BA3DDC","Deal-7599B8","Deal-F9A3C1","Deal-FA32A0"],"lock_violations":0,"pipeline_shape":"3 LOCK + 20 ACTION + 31 BUILD + 22 REVIVE + 45 WATCH + 35 RISKY = 156 deals. RISKY comprises 29 BEST_CASE and 6 COMMIT deals with zero meetings_30d despite those forecast categories. Engagement rows are missing for Deal-3EED2C and Deal-57FF13; their meeting activity cannot be assessed."}
[
{
"transcript_id": "TX-001",
"deal_alias": "Deal-CFE7F4",
"why_buys": ["Automate anniversary and birthday awards."],
"pain_points": ["An HR team of three cannot keep up with awards manually.", "Spreadsheet tracking lets people slip through the cracks."],
"stakeholders": ["Prospect (VP People)", "Prospect (HR Admin)"],
"budget_signal": "About $40k earmarked for engagement tools this fiscal year.",
"timeline_signal": "Ideally live before open enrollment in November.",
"competitor_mentioned": "Achievers — evaluated last year; considered too heavy for a team their size.",
"next_step": "Security review on September 12.",
"objections": ["IT sign-off requires SSO and audit logs."],
"confidence": "high"
},
{
"transcript_id": "TX-002",
"deal_alias": "Deal-70BB30",
"why_buys": ["Tie recognition to retention for the hourly workforce."],
"pain_points": ["Regretted turnover among hourly workers is over 30%."],
"stakeholders": ["Prospect (Head of Total Rewards)", "Prospect (CFO)"],
"budget_signal": "Finance approved a $25k pilot budget for this quarter.",
"timeline_signal": "Decision wanted by end of September; pilot agreement to be routed to legal this week.",
"competitor_mentioned": null,
"next_step": "Send the pilot agreement; the prospect will route it to legal this week.",
"objections": ["Workday integration must be rock solid."],
"confidence": "high"
},
{
"transcript_id": "TX-003",
"deal_alias": "Deal-530B50",
"why_buys": ["Make recognition visible across 12 retail locations."],
"pain_points": ["Store managers have no 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 prospect will send two times.",
"objections": ["The CEO must be sold first and decides people-related purchases."],
"confidence": "high"
},
{
"transcript_id": "TX-004",
"deal_alias": "Deal-180D02",
"why_buys": ["Consolidate three recognition tools into one."],
"pain_points": ["They pay for three tools, none of which connect to their HRIS."],
"stakeholders": ["Prospect (VP People)", "Prospect (IT Security Lead)"],
"budget_signal": "The VP People can approve an annual cost under $15k without board approval.",
"timeline_signal": "Procurement takes at least six to eight weeks.",
"competitor_mentioned": null,
"next_step": null,
"objections": ["The security lead is hesitant because the last vendor's security review took three months."],
"confidence": "high"
},
{
"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; their engagement scores run 20 points lower."],
"stakeholders": ["Prospect (HR Director)", "Prospect (People Ops Coordinator)"],
"budget_signal": "$12k approved under the engagement line.",
"timeline_signal": "Needs to be running before the January all-hands.",
"competitor_mentioned": "Nectar — currently in a pilot.",
"next_step": "Present to the exec team on October 2.",
"objections": ["The experience must beat the ongoing Nectar pilot.", "The exec team is skeptical after a failed rollout two years ago."],
"confidence": "high"
},
{
"transcript_id": "TX-006",
"deal_alias": "Deal-EE195F",
"why_buys": ["Cut administrative time spent on service awards."],
"pain_points": ["The HR Manager spends five hours a month ordering and shipping plaques."],
"stakeholders": ["Prospect (HR Manager)"],
"budget_signal": "Budget isn't the issue; time is. No amount stated.",
"timeline_signal": "Fiscal year resets in February; a Q1 start is realistic.",
"competitor_mentioned": null,
"next_step": "Send a one-page overview; the prospect will forward it to the COO this week.",
"objections": ["The COO usually prefers building things in-house."],
"confidence": "high"
}
]
Based on the provided CRM export and September 4 Slack thread, these are the three closest to signature, not confirmed current statuses: 1. Deal-547B2B · $11,200. Redlines were clean, the signing page was out, and the buyer’s VP People said they would sign the next day. Left: confirm whether they signed; the thread contains no signature confirmation. 2. Deal-403845 · $9,000. The order form was with the buyer’s finance team. Left: finance approval and signature. Slack says it was “moving fine,” but gives no approval or signing date. 3. Deal-A2B47C · $6,360. It was DS5/COMMIT in CRM and described in Slack as warm, with legal review proceeding at a normal pace. Left: finish legal review and obtain signature. Arithmetic: $11,200 + $9,000 + $6,360 = $26,560. Deal-2465CE is excluded despite DS5/COMMIT: Slack says its champion left and procurement froze new vendors. All cited Slack updates are from September 4, so none establishes signature status right now.
The supplied data has no deal amounts or deal-status fields. Amounts and whether these deals are active cannot be verified. | Deal | Prospect line | Classification | Amount | |---|---|---|---| | Deal-EC3025 | “We need SCIM user provisioning — our security team will not approve any tool that requires manual account management.” | Real gap — SCIM is not listed as supported. | Not provided | | Deal-D0D6B5 | “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 supported. | Not provided | | Deal-CFE7F4 | “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 Enterprise-only; the deal’s current plan is not provided. | Not provided | | Deal-84DBA6 | “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 on all plans. | Not provided | Real-gap summary: SCIM (Deal-EC3025) and ADP Workforce Now (Deal-D0D6B5). Arithmetic: 1 + 1 = 2 real-gap candidates. Deal-36C33F is excluded: the mobile-app absence was stated by the rep, while the prospect said the web version should be fine for now.
As of 2026-09-05, a deal is stale if its most recent logged email, call, or meeting was on or before 2026-08-28 (8 or more days ago). Days since contact = 2026-09-05 minus the latest of those three dates. Future-dated meetings do not count as contacts that have occurred. Alex Franklin | Deal alias | Stage | Amount | Days since last contact | |---|---|---:|---:| | Deal-CC08D1 | DS1 | $24,000 | 16 | | Deal-E73427 | DS3 | $18,000 | 10 | | Deal-885F45 | DS2 | $9,300 | 12 | | Deal-C2FF3C | DS1 | $8,316 | 10 | | Deal-0D2F7A | DS3 | $5,100 | 12 | | Deal-6C60D4 | DS3 | $4,800 | 12 | | Deal-819506 | DS1 | $4,400 | 8 | | Deal-9D0060 | DS3 | $3,840 | 12 | | Deal-690476 | DS2 | $3,600 | 18 | | Deal-C6D97A | DS4 | $3,240 | 8 | | 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 | 17 stale deals; $100,976 = $24,000 + $18,000 + $9,300 + $8,316 + $5,100 + $4,800 + $4,400 + $3,840 + $3,600 + $3,240 + $3,120 + $2,700 + $2,600 + $2,400 + $2,160 + $1,800 + $1,600. Bryce Harmon | Deal alias | Stage | Amount | Days since last contact | |---|---|---:|---:| | Deal-2D1F1B | DS1 | $240,000 | 81 | | 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-A414F6 | DS1 | $25,200 | 19 | | Deal-C5658B | DS1 | $23,400 | 16 | | Deal-40522D | DS3 | $21,000 | 19 | | Deal-C1FA6D | DS1 | $18,000 | 16 | | Deal-01E193 | DS1 | $12,600 | 8 | | Deal-F0EBBB | DS3 | $11,400 | 24 | | Deal-927338 | DS1 | $10,920 | 18 | | Deal-C9C286 | DS2 | $5,502 | 9 | | Deal-012CB1 | DS1 | $1 | 23 | | Deal-3795AD | DS2 | $1 | 8 | 17 stale deals; $686,964 = $240,000 + $99,000 + $70,000 + $45,000 + $37,440 + $36,000 + $31,500 + $25,200 + $23,400 + $21,000 + $18,000 + $12,600 + $11,400 + $10,920 + $5,502 + $1 + $1. 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-AF932D | DS2 | $7,225.40 | 11 | | Deal-A71728 | DS2 | $6,947.50 | 11 | | Deal-8BC9F5 | DS2 | $5,616 | 10 | | Deal-175395 | DS3 | $4,779.88 | 11 | | Deal-13FEBD | DS2 | $4,680 | 12 | | Deal-481E24 | DS3 | $4,140 | 10 | | Deal-C7F9BF | DS2 | $3,360 | 11 | | Deal-2F3A66 | DS3 | $3,334.80 | 11 | | Deal-342E96 | DS2 | $2,700 | 24 | | Deal-E568D5 | DS3 | $1,875 | 11 | | Deal-FD9F4E | DS5 | $1,330 | 10 | 19 stale deals; $257,585.03 = $58,529.25 + $40,000 + $32,175 + $31,750 + $18,000 + $12,168 + $11,193 + $7,781.20 + $7,225.40 + $6,947.50 + $5,616 + $4,779.88 + $4,680 + $4,140 + $3,360 + $3,334.80 + $2,700 + $1,875 + $1,330. Dana Mercer | Deal alias | Stage | Amount | Days since last contact | |---|---|---:|---:| | Deal-44EA29 | DS2 | $60,000 | 10 | | Deal-E51FB7 | DS2 | $43,875 | 12 | | 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-944310 | DS4 | $10,500 | 33 | | Deal-B7EBD1 | DS5 | $9,000 | 16 | | Deal-3974EB | DS4 | $9,000 | 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 | | Deal-BA571A | DS4 | $1,080 | 18 | 17 stale deals; $280,575 = $60,000 + $43,875 + $27,000 + $23,400 + $20,000 + $18,900 + $16,250 + $15,000 + $10,500 + $9,000 + $9,000 + $8,100 + $7,350 + $5,000 + $4,200 + $1,920 + $1,080. Farid Osman | Deal alias | Stage | Amount | Days since last contact | |---|---|---:|---:| | Deal-8BA24E | DS1 | $2,880 | 8 | | Deal-8FDCD2 | DS1 | $1 | 15 | 2 stale deals; $2,881 = $2,880 + $1. Deal-3EED2C (Alex Franklin) and Deal-57FF13 (Elena Sinclair) have no row in the engagements-by-deal table. Their contact recency—and therefore whether they are stale—cannot be determined from the supplied data.
Using the supplied `*_30d` engagement counts and DS2 entry dates from 2026-08-06 through the 2026-09-05 snapshot, the ranking is: | Rank | Rep | Emails | Calls | Meetings | Activity mix (email / call / meeting) | Total activities | DS2 entries | Activities per DS2 entry | |---:|---|---:|---:|---:|---|---:|---:|---:| | 1 | Alex Franklin | 307 | 36 | 41 | 79.95% / 9.38% / 10.68% | 384 | 18 | 384 ÷ 18 = 21.33 | | 2 | Bryce Harmon | 162 | 0 | 43 | 79.02% / 0% / 20.98% | 205 | 4 | 205 ÷ 4 = 51.25 | | 3 | Cole Ingram | 96 | 14 | 1 | 86.49% / 12.61% / 0.90% | 111 | 2 | 111 ÷ 2 = 55.50 | | 4 | Farid Osman | 38 | 0 | 34 | 52.78% / 0% / 47.22% | 72 | 1 | 72 ÷ 1 = 72.00 | | 5 | Dana Mercer | 84 | 18 | 11 | 74.34% / 15.93% / 9.73% | 113 | 1 | 113 ÷ 1 = 113.00 | | — | Elena Sinclair | Missing | Missing | Missing | Not calculable | Missing | 0 | Undefined | Each activity share is that activity count ÷ the rep’s total activities × 100; for example, Alex’s email share is 307 ÷ (307 + 36 + 41) × 100 = 79.95%. Alex Franklin is both the most efficient and the highest-volume rep **on the available engagement rows**; they do not differ. These are provisional rankings: the engagement row for Alex’s Deal-3EED2C is missing, as is the row for Elena’s Deal-57FF13. Missing rows were not treated as zero.
Alex Franklin — QTD scorecard as of 2026-09-05 (Q3: July 1–September 5) - Bookings vs quota: $150,000 / $200,000 = 75% attainment; $50,000 remaining. Bookings comprise 8 closed-won deals. Deal-B3E6F1 ($24,000; closed June 20) is excluded because it closed before Q3. - Booking split: New $113,500 (5 deals) + expansion $36,500 (3 deals) = $150,000. - Active pipeline: DS1 $284,621 (20 deals); DS2 $353,760 (28); DS3 $552,705 (67); DS4 $23,574 (5); DS5 $45,730 (5). Total: $284,621 + $353,760 + $552,705 + $23,574 + $45,730 = $1,260,390 across 125 open deals. - Rolling 90-day DS2-to-won rate: For deals entering DS2 June 8–September 5, 8 won / 111 entered = 7.2%. The cohort also has 27 lost and 76 still open. This is an all-deal rate: deal type is missing on open and lost rows, so a new-deal-only rate cannot be calculated. - QTD outcomes: 8 wins; 27 losses. Top recorded loss reason: “Lost- Timing (1 year or more)” — 13 of 27 losses. - Last-30-day activity: 807 emails, 112 calls, 128 meetings, 50 notes, summed from the supplied per-deal 30-day fields. Individual activity dates are not provided, so the precise 30-day boundaries cannot be independently verified. Coaching observations: 1. Work the 76 still-open deals in the DS2-entry cohort: only 8 of 111 have won so far. 2. Qualify timing earlier: “Lost- Timing (1 year or more)” accounts for 13 / 27 QTD losses. 3. Prioritize advancement beyond DS3: DS1–DS3 hold $284,621 + $353,760 + $552,705 = $1,191,086 of the $1,260,390 open pipeline; DS4–DS5 hold $69,304.
The files contain no deal amounts, stages, or open/closed status. I cannot verify which deals are open or choose a persona *given the stage*. The 11 deals below meet the threading criteria **if they are open**. For every row, amount and stage are not provided, and the stage-based persona priority is undetermined. As of 2026-09-24, the 60-day cutoff is 2026-09-24 − 60 days = 2026-07-26. Active counts exclude former contacts and contacts last engaged before that date. “Single” means fewer than 2 active contacts; “under” means fewer than 3, or all active contacts share one persona. | Deal / company | Active count; flag | Personas present | Personas missing | On-file unengaged contact fitting a missing persona | |---|---:|---|---|---| | Deal-EC3025 / C-FDD0C7 | 1; single | champion | economic buyer, HR admin, IT security, finance | CT-6827DB — economic buyer | | Deal-92D97D / C-E23238 | 1; single | HR admin | economic buyer, champion, IT security, finance | None on file | | Deal-50D386 / C-EB10E4 | 2; under | champion, HR admin | economic buyer, IT security, finance | CT-A1C4B3 — economic buyer | | Deal-D0D6B5 / C-32918E | 3; under (one persona) | champion | economic buyer, HR admin, IT security, finance | CT-1FA4DB — economic buyer | | Deal-5BFE3B / C-535D36 | 2; under | champion | economic buyer, HR admin, IT security, finance | None on file | | Deal-36C33F / C-077A0E | 1; single | IT security | economic buyer, champion, HR admin, finance | CT-1DB73E — economic buyer | | Deal-885F45 / C-5E8EFB | 2; under | economic buyer, champion | HR admin, IT security, finance | CT-B3F25D — IT security | | Deal-FCBE5B / C-737030 | 1; single | champion | economic buyer, HR admin, IT security, finance | None on file | | Deal-5408B0 / C-2AE3AA | 2; under | champion, HR admin | economic buyer, IT security, finance | CT-07FA76 — economic buyer | | Deal-C6D97A / C-5A8FC2 | 3; under (one persona) | champion | economic buyer, HR admin, IT security, finance | None on file | | Deal-F9A08A / C-0D15DF | 1; single | champion | economic buyer, HR admin, IT security, finance | CT-697541 — economic buyer | Arithmetic: 5 deals have 1 active contact; 4 have 2; 2 have 3 contacts all in one persona. 5 + 4 + 2 = 11 flagged deals.
From the 10 provided calls: - First five minutes: Alex leads with the same retailer turnover case in 8/10 calls. Deal-403845 opens with a security/pricing agenda; Deal-1E2498 opens with pricing. “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.” (Deal-D348E1) - Locked budget (4/10: Deal-D348E1, Deal-547B2B, Deal-60C2C2, Deal-84DBA6): Alex points to turnover savings and avoided backfills as a funding rationale. “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.” (Deal-D348E1) - Timing/capacity (3/10: Deal-5408B0, Deal-C61CF7, Deal-D9A12F): Alex proposes a one-department, 90-day pilot ahead of the next planning cycle. “Makes sense. What if we scope a 90-day pilot with one department so you have internal data before next quarter's planning?” (Deal-5408B0) - Existing spreadsheet and gift cards (3/10: Deal-403845, Deal-EDC141, Deal-1E2498): Alex contrasts the manual approach with automated milestones and recognition analytics. “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.” (Deal-403845) - Concrete next step agreed: 7/10 = 70%. The prospects in Deal-D348E1, Deal-5408B0, Deal-547B2B, Deal-C61CF7, Deal-60C2C2, Deal-D9A12F, and Deal-1E2498 agree to a Thursday 2pm working session and an invite. “Yes, Thursday at 2pm works — send the invite and I'll bring our HRIS manager.” (Deal-D348E1) - Competitors raised by prospects: Awardco (Deal-547B2B) and Kudos (Deal-EDC141). Workhuman is mentioned by Alex, not a prospect (Deal-C61CF7). Coaching notes: 1. When budget approval is blocked, ask for a specific committee follow-up rather than leaving it open-ended, as in Deal-403845 and Deal-84DBA6. 2. When a prospect says there is no urgency, propose a dated next conversation rather than ending at “Fair enough,” as in Deal-EDC141.
## Q3 2026 forecast | Category | Q3 deals | Total amount | Forecast contribution | |---|---:|---:|---:| | COMMIT | 7 | 44,729 | 44,729 × 100% = 44,729 | | BEST_CASE | 24 | 203,565 | 203,565 × 35% = 71,247.75 | | PIPELINE | 23 | Not included in forecast | 0 | **Weighted forecast: 44,729 + 71,247.75 = 115,976.75.** Currency is not specified in the extract. **Excluded for close dates outside Q3:** 32 deals, totaling 227,575 = 13,770 COMMIT + 28,240 BEST_CASE + 185,565 PIPELINE. All have October close dates. - COMMIT: Deal-D348E1. - BEST_CASE: Deal-C61CF7, Deal-48B656, Deal-901332, Deal-47AE31, Deal-15D24F, Deal-ED725A, Deal-8AD4A5, Deal-5FDCE4, Deal-F5A622. - PIPELINE: Deal-E51FB7, Deal-B936FE, Deal-D9A12F, Deal-4062CF, Deal-293AF3, Deal-034D49, Deal-E0ADD8, Deal-9F2E43, Deal-FCBE5B, Deal-712010, Deal-6691E0, Deal-600CD9, Deal-A92065, Deal-1D532E, Deal-E531A6, Deal-D1E6C2, Deal-D9E112, Deal-5AD94B, Deal-766C74, Deal-D7E999, Deal-ED13B0, Deal-7FA0C3. **Top 5 Q3 BEST_CASE deals by amount:** Deal-2D7423 (38,935), Deal-25F752 (24,000), Deal-E53952 (19,656), Deal-5EED42 (16,250), Deal-FA32A0 (11,116). ## Data quality Owner is blank on nearly every row, and `why_buys_chars` is zero on most rows, limiting ownership and buyer-rationale checks. Deal-333EBB, Deal-57FF13, Deal-31AD2C, and Deal-7A2454 have close dates already past as of the 2026-09-05 extract but remain open. Deal-A5E80A is marked COMMIT at DS1, a stage/category combination that warrants review. The extract has no currency field, so monetary totals cannot be assigned a currency or checked for mixed currencies.
Using `current_status = active` as the specified 24-month retention proxy: | First-month signals | Retained / companies | 24-month retention | |---|---:|---:| | Both: 5+ givers and 1+ redemption | 31 / 47 | 31 ÷ 47 = 66.0% | | Givers only | 23 / 49 | 23 ÷ 49 = 46.9% | | Redemption only | 9 / 29 | 9 ÷ 29 = 31.0% | | Neither | 38 / 95 | 38 ÷ 95 = 40.0% | Excluded: 0 companies. All 220 companies are old enough and have the fields needed for this classification; `non_renewing` is counted as not active. The stronger single signal is 5+ unique givers: givers-only exceeds neither by 46.9% − 40.0% = 6.9 percentage points. Redemption-only is 31.0% − 40.0% = 9.0 points lower than neither. The data support an association for both signals together (66.0%, higher than every other cell), but not the claim that *either* single signal improves retention. They do not prove that the signals cause retention; this is an observational comparison, and the provided status is a proxy rather than a recorded status at the exact 24-month mark.
As of 2026-09-05, using active subscriptions only and billing ARR = MRR × 12: CRM company ARR: $603,581.76 Billing ARR: $604,739.28 Variance (CRM − billing): −$1,157.52 Reconciliation: - Status mismatch: +$13,158.48 = $4,905.24 + $8,253.24. Both company records retain ARR for cancelled subscriptions; those subscriptions contribute $0 to active billing ARR. - Rounding: +$36.00 = $16.00 + $20.00. - Missing records: −$11,952.00 = $16,497.24 CRM-only − $28,449.24 billing-only. - Other: −$2,400.00 = $24,396.00 − $26,796.00. - Check: $13,158.48 + $36.00 − $11,952.00 − $2,400.00 = −$1,157.52. Mismatched accounts (difference is CRM − active billing ARR): | Company alias | CRM ARR | Billing ARR | Difference | Suggested owner | |---|---:|---:|---:|---| | C-0C8323BF | $4,905.24 | $0.00 (cancelled) | +$4,905.24 | CRM operations | | C-0DC4FB8C | $8,253.24 | $0.00 (cancelled) | +$8,253.24 | CRM operations | | C-0D66DF9E | $23,200.00 | $23,184.00 | +$16.00 | Revenue operations | | C-14D70CE0 | $18,200.00 | $18,180.00 | +$20.00 | Revenue operations | | C-0D5BBE3A | $16,497.24 | No subscription record | +$16,497.24 | Billing operations | | C-21629AA4 | No company record | $28,449.24 | −$28,449.24 | CRM operations | | C-0F7269D7 | $24,396.00 | $26,796.00 | −$2,400.00 | Revenue operations | The provided data has no assigned-owner field; the owners above are suggested functions, not identified people. The two small differences are classified as rounding for reconciliation, but their cause is not established by the files. Agreement-end-date violations (non-12-month term with blank `cf_agreement_end_date`): SUB-0002 / C-1794A52C (24 months); SUB-0019 / C-22170CA1 (36 months).
Using the unweighted mean of the 30 company rows in each month: | KVM | 2026-08 | 2026-07 | Absolute change | Relative change | Direction | |---|---:|---:|---:|---:|---| | Giving rate | 0.602713 | 0.602297 | +0.000417 | +0.07% | Up | | Redemptions per user | 1.730163 | 1.729983 | +0.000180 | +0.01% | Up | | 1:1 meetings engagement | 0.447177 | 0.446887 | +0.000290 | +0.06% | Up | | Pulse check engagement | 0.508610 | 0.600587 | −0.091977 | −15.31% | Down | Arithmetic: absolute change = August mean − July mean; relative change = absolute change ÷ July mean × 100. Pulse check engagement had the largest relative move. The `enterprise` size_band drove it: its mean fell from 0.54998 to 0.27428 (−0.27570, or −50.13%). With 10 of 30 rows, that contributes −0.27570 × 10/30 = −0.09190 of the overall −0.091977 change.
Redemptions YTD (January–August 2026). Last completed month: August 2026. - Redemption count: 378 - Spend: $27,846.00 - Unique redeemers: 235 distinct user keys - Redemptions per redeemer: 378 ÷ 235 = 1.61 Provider mix (% of spend): - custom: $10,873 ÷ $27,846 = 39.05% - Tremendous: $8,505 ÷ $27,846 = 30.54% - Snappy: $5,238 ÷ $27,846 = 18.81% - TangoCard: $3,230 ÷ $27,846 = 11.60% - Total: $27,846 ÷ $27,846 = 100.00% Top 5 countries by redemptions: US 244; CA 24; AU 21; GB 17; NL 17.
The documented rules require all three conditions: health score <60, churn-save eligible amount >$0, and renewal within 120 days of the 2026-09-05 snapshot (through 2027-01-03). Eight accounts qualify. “Amount at stake” below is the churn-save eligible amount, not full ARR. | Account | Amount at stake | Best-fit play and supporting signal | |---|---:|---| | C-0F6C0F34 | $49,707 | Executive touch — champion inactive; renewal 2026-10-03. | | C-0B827671 | $25,365 | Usage revival — three-month usage declining; 113/202 seats used = 55.9%. | | C-0B360C78 | $35,748 | Commercial concession candidate — usage growing and champion active despite health score 57; renewal 2026-10-28. No pricing objection is provided, so a concession is not yet justified. | | C-0B0F1BAB | $5,494 | Executive touch — champion inactive; renewal 2026-09-23. | | C-0CA21961 | $16,829 | Usage revival — 84/325 seats used = 25.8%; usage flat. | | C-0E9C27D1 | $41,235 | Commercial concession candidate — 134/157 seats used = 85.4% and champion active despite health score 39; renewal 2026-09-24. No pricing objection is provided, so a concession is not yet justified. | | C-0CEF69FD | $32,621 | Executive touch — champion inactive. | | C-0D3278C7 | $17,602 | Usage revival — usage declining; 126/380 seats used = 33.2%. | Total at stake: $49,707 + $25,365 + $35,748 + $5,494 + $16,829 + $41,235 + $32,621 + $17,602 = **$224,601**. At risk (health <60) but not eligible: | Account | Why excluded | |---|---| | C-0BC71BDD | Eligible amount is $0. | | C-0BA71F12 | Renewal 2027-04-11 is outside the 120-day window. | | C-0F6694C3 | Eligible amount is $0; renewal 2027-03-21 is outside the window. | | C-0BE96399 | Eligible amount is $0. | | C-0F876796 | Renewal 2027-02-06 is outside the window. | | C-0FCCD2DF | Eligible amount is $0; renewal 2027-04-23 is outside the window. | | C-10A56B0F | Eligible amount is $0. |
C-0DDFC9A7 expansion kit - Seat coverage: 150 licensed seats ÷ 400 headcount = 37.5%. - Usage health: Monthly users rose from 88 in March to 126 in August, up 38 (38 ÷ 88 = 43.2%). - Usage health: August’s 126 users equal 84% of licensed seats (126 ÷ 150); 24 licensed seats remain unused. - Headroom: 400 − 150 = 250 additional seats. Current rate: $9,000 ARR ÷ 150 = $60 per seat annually. At that rate, 250 seats represent $15,000 in additional ARR, for $24,000 total ARR if all 400 employees were licensed. This is capacity, not a forecast. - Reply and buyer: Maria S. replied and explicitly said she does not make purchasing decisions. She identified Dana R., VP People, as the budget and seat-expansion buyer and offered an introduction. Reply email Hi Maria, Thanks for the update—and for offering to connect us with Dana. It’s good to see monthly users rise from 88 in March to 126 in August. Since Dana has been asking about usage, I can put together a short summary of adoption and what broader seat coverage could look like. If you’re comfortable making the introduction, I’d be glad to share it with her and answer any questions. No need to schedule anything until it’s useful for her. Thanks, Cole
C-0D284E42 — mid-onboarding call prep Complete (shown in onboarding_account.csv): - Slack integration connected August 12; allowance set August 13; 2 admins added; first recognition given August 15 at 14:22. Not shown as complete: - HRIS integration and first redemption have blank fields. Their status is unconfirmed, not necessarily incomplete. Early engagement (onboarding_usage.csv, through September 4): - Daily active givers rose from 3 on August 11 to 15 on September 4: 15 − 3 = 12 more, or 15 ÷ 3 = 5× the starting count. - The first 7 days averaged 30 ÷ 7 = 4.3 daily active givers; the last 7 averaged 91 ÷ 7 = 13. These are daily counts, not unique givers across each week. Cover on the call: 1. Confirm HRIS integration status and any blocker. 2. Confirm whether a first redemption has happened; if not, identify what is preventing it. 3. Review the rise in daily active givers and agree on the next adoption step.
90-day renewal risk brief — September 24–December 22, 2026 Date rule: Use Chargebee for multi-year contracts because ChurnZero renewal dates are known to be wrong for those contracts. For annual contracts, the two dates agree. Seat utilization is seats_used ÷ seats; usage trend is monthly active users in June → July → August 2026. Risk ratings below use these two signals only: High for utilization below 30% or a June-to-August usage decline of at least 10%; Moderate for utilization below 60% without a High signal; Low otherwise. These are exposure ratings, not predictions of non-renewal. | Company | CSM | ARR | Date used | Seat utilization | 3-month usage | Risk and evidence | |---|---|---:|---|---:|---|---| | C-0BBE3E60 | Dana Mercer | $30,993 | 2026-09-26 | 74 ÷ 114 = 64.9% | 39 → 35 → 33 | High — active users fell 6 ÷ 39 = 15.4% from June to August. | | C-0F5D2323 | Cole Ingram | $90,647 | 2026-09-29 | 111 ÷ 390 = 28.5% | 20 → 21 → 18 | High — utilization is 28.5% and active users fell 2 ÷ 20 = 10.0%. | | C-0EC6999D | Elena Sinclair | $79,419 | 2026-10-03 | 31 ÷ 112 = 27.7% | 17 → 16 → 15 | High — utilization is 27.7% and active users fell 2 ÷ 17 = 11.8%. | | C-0B20DB64 | Dana Mercer | $21,770 | 2026-10-07 | 214 ÷ 378 = 56.6% | 294 → 298 → 294 | Moderate — utilization is 56.6%, though June and August active-user counts match. | | C-0BBC4E7A | Cole Ingram | $56,374 | 2026-10-10 | 228 ÷ 337 = 67.7% | 142 → 141 → 139 | Low — utilization is 67.7% and active users fell only 3 ÷ 142 = 2.1%. | | C-0FD551AB | Elena Sinclair | $48,815 | 2026-10-14 | 210 ÷ 376 = 55.9% | 123 → 122 → 126 | Moderate — utilization is 55.9%, despite active users rising 3 ÷ 123 = 2.4%. | | C-0F9F8F13 | Dana Mercer | $46,230 | 2026-10-18 | 199 ÷ 352 = 56.5% | 185 → 185 → 182 | Moderate — utilization is 56.5% and active users fell 3 ÷ 185 = 1.6%. | | C-0BC34584 | Cole Ingram | $16,740 | 2026-10-22 | 327 ÷ 494 = 66.2% | 104 → 104 → 106 | Low — utilization is 66.2% and active users rose 2 ÷ 104 = 1.9%. | | C-0B7A7546 | Elena Sinclair | $35,062 | 2026-10-25 | 182 ÷ 205 = 88.8% | 64 → 65 → 63 | Low — utilization is 88.8% and active users fell 1 ÷ 64 = 1.6%. | | C-0B369871 | Dana Mercer | $85,128 | 2026-10-29 | 317 ÷ 422 = 75.1% | 326 → 330 → 333 | Low — utilization is 75.1% and active users rose 7 ÷ 326 = 2.1%. | | C-0B144C78 | Cole Ingram | $30,899 | 2026-11-02 | 169 ÷ 224 = 75.4% | 101 → 101 → 106 | Low — utilization is 75.4% and active users rose 5 ÷ 101 = 5.0%. | | C-0FC4DBB8 | Elena Sinclair | $94,732 | 2026-11-05 | 356 ÷ 464 = 76.7% | 189 → 191 → 193 | Low — utilization is 76.7% and active users rose 4 ÷ 189 = 2.1%. | | C-0D5BBE3A | Dana Mercer | $39,740 | 2026-11-09 | 85 ÷ 102 = 83.3% | 88 → 90 → 91 | Low — utilization is 83.3% and active users rose 3 ÷ 88 = 3.4%. | | C-0FB9D5AF | Cole Ingram | $63,158 | 2026-11-13 | 144 ÷ 199 = 72.4% | 173 → 173 → 176 | Low — utilization is 72.4% and active users rose 3 ÷ 173 = 1.7%. | | C-0B344485 | Elena Sinclair | $64,384 | 2026-11-16 | 224 ÷ 287 = 78.0% | 238 → 240 → 244 | Low — utilization is 78.0% and active users rose 6 ÷ 238 = 2.5%. | | C-0CB2C1B4 | Dana Mercer | $40,628 | 2026-11-20 | 386 ÷ 473 = 81.6% | 47 → 48 → 49 | Low — utilization is 81.6% and active users rose 2 ÷ 47 = 4.3%. | | C-22170CA1 | Cole Ingram | $45,646 | 2026-11-24 | 251 ÷ 294 = 85.4% | 143 → 148 → 146 | Low — utilization is 85.4% and active users rose 3 ÷ 143 = 2.1%. | Date disagreements (ChurnZero → Chargebee; Chargebee used in each case because the contract is multi-year): - C-0B7D2C30: 2026-09-10 → 2026-09-15; outside the 90-day window. - C-0BCDB8C2: 2027-09-18 → 2026-09-18; outside the 90-day window. - C-0D2AB865: 2026-09-10 → 2026-09-22; outside the 90-day window. - C-0BBE3E60: 2027-09-26 → 2026-09-26; included. - C-0F5D2323: 2026-09-10 → 2026-09-29; included. Total ARR renewing: $890,365 across the 17 in-window accounts (sum of the 17 ARR rows above). ARR at risk, defined here as High plus Moderate: ($30,993 + $90,647 + $79,419) + ($21,770 + $48,815 + $46,230) = $201,059 + $116,815 = $317,874.
ARR affected is exposure, not confirmed revenue loss. Each account’s ARR is counted once per theme. Shares use all 80 tickets as the denominator; themes are ranked by ARR exposure. | Theme | Tickets / share | Distinct accounts | ARR affected (arithmetic) | Example ticket IDs | Recommendation | |---|---:|---:|---:|---|---| | HRIS new-hire provisioning failures — broad pattern | 12 / 80 = 15.0% | 3 | $36,000 + $30,000 + $48,000 = **$114,000** | IC-460059, IC-460062 | Investigate skipped new hires and provisioning logs across the three accounts. | | Redemption and gift-card failures — broad pattern | 18 / 80 = 22.5% | 7 | $8,900 + $9,600 + $10,700 + $8,700 + $9,600 + $11,000 + $10,300 = **$68,800** | IC-460025, IC-460024 | Trace checkout failures, missing delivery, and cases where points were deducted. | | Invoice seat-count and renewal-price errors — **single-account concentration** | 16 / 80 = 20.0% | 1: C-0E9C27D1 | **$52,000** | IC-460069, IC-460078 | Reconcile C-0E9C27D1’s seat count and renewal tier against its invoices; do not treat repeat tickets as a cross-account pattern. | | Recognition points not posting — broad pattern | 20 / 80 = 25.0% | 9 | $4,500 + $2,700 + $3,500 + $3,400 + $4,500 + $4,200 + $2,900 + $2,500 + $2,900 = **$31,100** | IC-460001, IC-460004 | Audit delivered recognitions against point postings and balances. | | Slack recognition sync and command failures — broad pattern | 14 / 80 = 17.5% | 4 | $4,400 + $5,400 + $3,900 + $5,200 = **$18,900** | IC-460041, IC-460051 | Test sync, re-authentication, toggle persistence, and slash commands across affected accounts. |
For prospect C-82AF3719 (Technology, Mid-Market, employee_recognition, NA-West), three case-study customers tie on exact field matches: 1. C-64171065 — 3/4: Technology industry, Mid-Market size band, employee_recognition use case. Region differs (NA-East). 2. C-11C31562 — 3/4: Mid-Market size band, employee_recognition use case, NA-West region. Industry differs (Manufacturing). 3. C-A13C193D — 3/4: Technology industry, Mid-Market size band, NA-West region. Use case differs (retention). Arithmetic: each matches 3 of the 4 requested fields. This order favors a matching use case over a matching region when scores tie; no field weights were provided. Source: customers.csv and prospect.csv.
Trailing six months: March–August 2026. SQM and SQO counts use the provided first-touch contact rows; pipeline is the sum of their `pipeline_amount` values. | Paid channel | Spend | SQMs | SQOs | Cost/SQM | Cost/SQO | SQM→SQO | Pipeline | Pipeline/$ | |---|---:|---:|---:|---:|---:|---:|---:|---:| | paid_search | $36,000 | 40 | 18 | $900 | $2,000 | 45.0% | $720,000 | $20.00 | | linkedin_ads | $24,000 | 25 | 8 | $960 | $3,000 | 32.0% | $96,000 | $4.00 | | paid_social | $18,000 | 0 | 0 | undefined | undefined | undefined | $0 | undefined* | | webinars | $9,000 | 12 | 5 | $750 | $1,800 | 41.7% | $60,000 | $6.67 | | Total | $87,000 | 77 | 31 | $1,129.87 | $2,806.45 | 40.3% | $876,000 | $10.07 | Arithmetic: spend = six monthly entries per paid channel; cost/SQM = spend ÷ SQMs; cost/SQO = spend ÷ SQOs; SQM→SQO = SQOs ÷ SQMs; pipeline/$ = pipeline ÷ spend. For example, paid_search: $6,000 × 6 = $36,000; $36,000 ÷ 40 = $900; $36,000 ÷ 18 = $2,000; 18 ÷ 40 = 45.0%; 18 × $40,000 = $720,000; $720,000 ÷ $36,000 = $20.00. Total: $87,000 ÷ 77 = $1,129.87; $87,000 ÷ 31 = $2,806.45; 31 ÷ 77 = 40.3%; $876,000 ÷ $87,000 = $10.07. | Organic channel | Volume (SQMs) | SQOs | SQO rate | Pipeline | |---|---:|---:|---:|---:| | organic_search | 30 | 10 | 10 ÷ 30 = 33.3% | 10 × $9,000 = $90,000 | | referral | 15 | 6 | 6 ÷ 15 = 40.0% | 6 × $8,000 = $48,000 | | Total | 45 | 16 | 16 ÷ 45 = 35.6% | $138,000 | Date flags: CT-000044 (`linkedin_ads`) has SQO 2026-07-18 before SQM 2026-07-23; CT-000041 (`linkedin_ads`) has SQO 2026-06-09 before SQM 2026-06-14. Both are included in the table as supplied; excluding them would change `linkedin_ads` to 6 SQOs, $72,000 pipeline, and 6 ÷ 25 = 24.0% conversion. Recommendation: Pause or sharply reduce `paid_social` pending an attribution check, then test a limited reallocation toward `paid_search` rather than committing the full $18,000 elsewhere. Confidence is moderate in the case for reviewing `paid_social` (0 SQMs on $18,000 spend), but low in the precise destination or expected return: `paid_search` has only 18 SQOs, `webinars` 5, and the two inverted `linkedin_ads` dates need correction before comparing channels definitively. *For `paid_social`, pipeline/$ is shown as undefined rather than a performance multiple because spend produced zero recorded SQMs.
# Rivally battlecard **One-line positioning:** Rivally is a points-based recognition platform with an engaging feed; its EU offering includes multi-language support and generally available EU data residency. Mid-market as its primary segment is unverified. [S02, S12, S15] **Pricing:** Recognition Starter lists at **$7/user/month, annual billing required** on Rivally’s pricing page dated 2026-08-12. This supersedes the **$5/user/month** page dated 2026-04-01 and conflicts with a **$6.50/user/month** annual quote reported for a 500-seat prospect on 2026-06-02; the latter is a deal-specific quote, not list pricing. A prospect reported a $7 list quote with a 15% discount for a three-year term on 2026-08-14. [S17, S08, S13, S18] **Where they win:** Reviewers praise the recognition feed, quick setup, working Slack integration, multi-language support for distributed EU teams, and support response time. EU data residency became generally available on 2026-07-01. These are reported strengths, not verified reasons for any recorded loss. [S02, S04, S12, S22, S15] **Where we win:** An 800-seat prospect picked Bonusly over Rivally citing analytics depth. Reviews also describe Rivally’s reporting as basic, its EMEA rewards catalog as thinner than its US catalog, and enterprise administration as limited by missing SCIM provisioning and bulk recognition editing. No broader Bonusly feature comparison is established by the supplied data. [S25, S07, S14, S10, S24] **Objections and responses:** - “Rivally has Slack integration.” **Acknowledge it**; a reviewer said it worked out of the box. Do not repeat the old card’s “lacks Slack integration” claim. [S04] - “Rivally is cheaper.” **Compare the current $7/user/month annual list price and the actual quoted term**, not the superseded $5 price; a prospect reported a three-year discount. [S17, S08, S18] - “We need EU coverage.” **Acknowledge** generally available EU data residency and praised multi-language support; ask the buyer to assess its EMEA rewards catalog against their needs. [S15, S12, S14] - “We need enterprise controls and reporting.” **Test SCIM, bulk editing, and analytics requirements**: reviewers report gaps in the first two, and one prospect selected Bonusly citing analytics depth. [S10, S24, S25] **Recent changes:** Rivally Pulse launched as a survey add-on on 2026-03-05 and exited beta on 2026-09-01; it is priced separately, not bundled. Rivally hired an EMEA leader on 2026-05-09, opened a Dublin office and made EU data residency generally available on 2026-07-01, raised Recognition Starter list pricing by 2026-08-12, and put Microsoft Teams app v2 in public preview on 2026-08-20. [S06, S23, S11, S15, S08, S17, S19] **Old-card claims not carried forward:** “Acquired by WorkHuman in 2025” is **unverified** by the supplied snippets. “Points-based recognition for mid-market” is supported only as to points-based recognition; the primary-segment claim remains **unverified**. “Lacks a Slack integration” is contradicted by the reviewer account. [S02, S04] **Our 12-month win/loss record (2025-09 through 2026-08):** 13 wins + 7 losses = 20 recorded Rivally deals; win rate = 13 ÷ 20 × 100 = **65%**. The deal file supplies outcomes, not reasons for those outcomes. 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.
Rates below use summed events ÷ summed sends across all three steps; “weakest” means lowest step reply rate. | Sequence | Sent | Open rate | Reply rate | Meeting rate | Weakest step | |---|---:|---:|---:|---:|---| | New Logo Nurture | 500+458+428=1,386 | 490/1,386=35.35% | 90/1,386=6.49% | 27/1,386=1.95% | 3: 18/428=4.21% reply | | Expansion Nurture | 300+300+275=875 | 565/875=64.57% reported; unreliable | 59/875=6.74% | 12/875=1.37% | 3: 12/275=4.36% reply | | Cold Outbound - HR Leaders | 600+595+590=1,785 | 545/1,785=30.53% | 8/1,785=0.45% | 0/1,785=0% | 3: 1/590=0.17% reply | | Cold Outbound - People Ops | 400+386+377=1,163 | 340/1,163=29.23% | 29/1,163=2.49% | 6/1,163=0.52% | 3: 6/377=1.59% reply | Tracking error: Expansion Nurture step 2 records 340 opens against 300 sends (340/300=113.33%). Its aggregate open rate should not be used until that count is corrected. Audience overlap: 21 contact keys appear in both Cold Outbound - HR Leaders and Cold Outbound - People Ops; 2 appear in both New Logo Nurture and Expansion Nurture. These are overlapping assignments, not evidence that both sequences sent to each contact. Under 2% reply: Cold Outbound - HR Leaders is weak at every step (5/600=0.83%, 2/595=0.34%, 1/590=0.17%); opens are not turning into replies or meetings. Cold Outbound - People Ops falls below 2% only at step 3 (6/377=1.59%). The files do not show whether targeting, copy, or timing caused either failure. One change each: revise New Logo Nurture step 3’s ask; correct Expansion Nurture step 2 open tracking; test a more specific first-step ask for Cold Outbound - HR Leaders; revise Cold Outbound - People Ops step 3’s ask. Fix the Expansion tracking error first for measurement integrity; prioritize Cold Outbound - HR Leaders first for performance.
Q3-2026 QTD (66 of 92 days elapsed; linear pace = 66 ÷ 92 = 71.7% of quarter). Delta is actual minus target. | Metric | QTD actual | Target | Delta | Pace | |---|---:|---:|---:|---| | SQMs | 230 | 300 | 230 − 300 = −70 | Ahead: 230 vs 300 × 66/92 = 215.2 | | SQOs | 84 | 120 | 84 − 120 = −36 | Behind: 84 vs 120 × 66/92 = 86.1 | | DS2s | 40 | 75 | 40 − 75 = −35 | Behind: 40 vs 75 × 66/92 = 53.8 | | Closed-lost MIA rate | 5 ÷ 25 = 20% | ≤10% | +10 percentage points | Behind: rate exceeds the ceiling; linear pacing does not apply | | Same-quarter closes | 10 | 20 | 10 − 20 = −10 | Behind: 10 vs 20 × 66/92 = 14.3 | | Active pipeline coverage against target | $3,000,000 ÷ $4,000,000 = 75% | 100% ($4,000,000) | −25 percentage points (−$1,000,000) | Ahead of a *linear* benchmark: $3,000,000 vs $4,000,000 × 66/92 = $2,869,565; still below the full target | What moved this week cannot be determined: only one QTD snapshot was provided, with no prior-week values.
Treat Q3’s $115,976.75 weighted forecast as unvalidated: $44,729 COMMIT + 35% × $203,565 BEST_CASE ($71,247.75); PIPELINE contributes $0. Only 54 of 86 deals have in-quarter close dates; 32 totaling $227,575 fall after September 30, including COMMIT Deal-D348E1 ($13,770). All 7 in-quarter COMMIT deals lack a documented why-buy, so do not treat the $44,729 committed amount as buyer-validated.
Subject: Following up on the demo Hi, I’m following up on the August 5 recap of our July 28 demo and the pricing for 150 seats. Your People team had a strong reaction to automated milestone awards and the points catalog. Would you let me know if you’d like to discuss the pricing further? Best, Alex
Marketing: We brought in 46 SQMs against a target of 52, a gap of 6 (52 − 46). Webinars delivered 18 of the 46 SQMs. Paid search cost per SQM held at $150. Sales: We converted 14 SQOs, set 9 DS2 meetings, and created $310,000 in new pipeline. The same-quarter close count was 3. CS: We saved 2 renewals this week. Team NPS moved to 61, and 3 red-flag accounts remain open heading into next week. The prior NPS score was not provided, so the size of the change is unknown. PLG: We added 412 signups, with activation at 31%. Separately, 38 companies reached the aha moment of 10 recognition gives. The extract does not establish whether those companies came from this week’s signups.
Partner digest | 2026-08-24 to 2026-09-04 Partner-sourced pipeline: 2 + 1 + 2 = 5 deals; $275,000 + $140,000 + $135,000 = $550,000. - Apex Rewards Co — 2 DS1 sourced deals: Deal-DDAAF2 ($180,000) + Deal-2CF33E ($95,000) = $275,000. Co-webinar locked for 09-15. - HRCloud Partners — 1 sourced deal: Deal-F1CDA5 ($140,000). Security review closed; opportunity moved to DS2. - CultureBridge — 2 early-stage sourced deals: Deal-096E1D ($60,000) + Deal-067213 ($75,000) = $135,000. Lunch-and-learn produced both. - WorkWell Group — 0 sourced deals. Q4 joint-playbook restart discussed; planning call booked for 09-09. - Recogniq — Quiet; no activity or sourced deals provided. - KudosWave — Quiet; no activity or sourced deals provided. - PeopleFirst Advisors — Quiet; no activity or sourced deals provided. - TotalPerk — Quiet; no activity or sourced deals provided.
Q1. Yes. Customer data is encrypted at rest using AES-256. [P1] Q2. Yes. Data in transit is encrypted using TLS 1.2 or higher. [P1] Q3. Yes. Bonusly maintains a SOC 2 Type II report, renewed annually. Prospects can obtain it under NDA. [P2] Q4. Customer data is retained for 90 days after the contract ends, 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 retained for 35 days. [P6] Q8. Unanswerable from these excerpts; they do not state whether Bonusly holds ISO 27001 certification. An ISO 27001 certificate or certification record would answer this. [P1–P8] Q9. Unanswerable from these excerpts; they do not state a contractual uptime percentage. The applicable service-level agreement would answer this. [P1–P8] Q10. Unanswerable from these excerpts; they do not state whether Bonusly will sign a HIPAA Business Associate Agreement. An approved BAA policy or agreement template would answer this. [P1–P8]
Reconciliation is limited to the 14 manifest rows and 14 skill files supplied. A target absent from this set cannot be confirmed nonexistent outside it. | Severity | Action | Finding and proposal | |---|---|---| | CRITICAL | MERGE | `comms-drafter` and `email-drafter` both claim “write me an email,” “draft a follow-up,” and “what should I say,” including sales and CS emails. Make `comms-drafter` the broad entry point and retain `email-drafter` only for its distinct email-signature workflow, with non-overlapping triggers. | | WARNING | UPDATE_BODY | `deal-strategy-coach` → `email-drafter` → `deal-strategy-coach` is a conditional handoff loop: the coach invokes the drafter for manager emails, while the drafter points strategic requests back to the coach. Make the return handoff conditional on a *new* strategy request, not the draft already being handled. | | WARNING | REVIEW | Targets referenced but absent from both the supplied files and manifest include `bonusly-brand`, `prospect-research-multithreading`, and `signalforge-reports`; `analysis-validator` also delegates to eight `bonusly-*-questions` specialists not listed here. Verify those dependencies in the full registry before labeling any globally dangling; add their rows/files or remove invalid handoffs. | | WARNING | MERGE | `weekly-pipeline-report` (“pipeline update,” “pipeline report,” “what does pipeline look like”) overlaps `pipeline-intelligence-report` (“pipeline update,” “pipeline report,” “what’s the pipeline look like”). Retain both only with an explicit routing boundary: weekly funnel/booking metrics versus full deal-by-deal scoring. `sales-forecast` also overlaps the latter on “pipeline forecast” and forecast context; reserve current-quarter revenue outlooks for `sales-forecast`. | | CRITICAL | UPDATE_BODY | Transcript schema conflicts: `closed-lost-analysis` selects `t.SNIPPET`; `stale-pipeline-report` says `GONG_TRANSCRIPTS_AGG` has only `CONVERSATION_KEY` and `TRANSCRIPT`, consistent with `analysis-validator`’s approved transcript source. Retain the `TRANSCRIPT` specification; correct the closed-lost query. | | WARNING | UPDATE_BODY | `analysis-validator` identifies itself as v3.6 but its validation-trail template says v3.2. Retain v3.6, the stated current version in the supplied file, and align the template. | | WARNING | UPDATE_BODY | Hardcoded destination IDs appear in `deal-strategy-coach` (AE Excellence Playbook page `2257879045`), `partner-digest` (folder `2286616609` and reference-page IDs), `sales-forecast` (parent page `2232582148`), and `signalforge-feedback` (feedback page `2295136266`). Resolve destinations from maintained configuration or lookup rather than embedding them in workflow bodies. | | WARNING | UPDATE_BODY | Hardcoded dates and time-bound assumptions include `model-selection`’s `last_checked: 2026-05-19`, `weekly-pipeline-report`’s fixed Q2 2026 business-day window, `sales-forecast`’s “Open Q2 Deals” and “Q2 Narrative,” and dated examples/expected ranges in `analysis-validator`, `closed-lost-analysis`, and `partner-digest`. Make operational windows dynamic; keep historical dates clearly labeled as examples or changelog entries. | | WARNING | UPDATE_BODY | Hardcoded people/rosters include `pipeline-intelligence-report`’s AE owner list, `analysis-validator`’s GTM roster, `weekly-pipeline-report`’s Ben Lavin ownership, `partner-digest`’s Amani Phipps ownership and named contacts, and example companies/people in `closed-lost-analysis` and `signalforge-claim-compressor`. Resolve current personnel at run time; label historical examples as non-operational. | | INFO | REVIEW | Description-length check: **0 over limit**. Arithmetic: 14 listed lengths checked; 0 are greater than 1,024 (maximum listed: 1,006). No trimming proposed. | | INFO | REVIEW | Manifest drift: **0 files without rows; 0 rows without files**. Arithmetic: 14 supplied file names − 14 matching manifest names = 0 in either direction. No manifest change proposed. |
1. [M01] Bryce Harmon acknowledged the PagerDuty alert for reward-worker queue depth > 10k and took IC. Verification: the thread records his acknowledgment; no independent verification is documented. Rollback: not documented — needs confirmation. 2. [M02] Farid Osman ran `bundle exec rake sidekiq:queue_depth`. Verification: it returned 48,213 pending reward jobs; he stated normal is under 500. 3. [M03] Farid Osman inspected the dead set and reported 112 jobs, all `Redis::TimeoutError` from around 13:58. Exact inspection command and independent verification: not documented — needs confirmation. 4. [M04] Farid Osman paused enqueue with `bin/rails runner 'FeatureFlag.disable(:auto_recognition_enqueue)'`. Verification of the flag state: not documented — needs confirmation. Rollback: `bin/rails runner 'FeatureFlag.enable(:auto_recognition_enqueue)'`. 5. [M05] Elena Sinclair cleared the dead set in the console. Exact command, verification, and rollback: not documented — each needs confirmation. This thread does not establish a repeatable clearing procedure. 6. [M06] Bryce Harmon scaled workers from 3 to 6 with `kubectl scale deployment/reward-worker --replicas=6`. Direct verification of replica count: not documented — needs confirmation. Rollback: `kubectl scale deployment/reward-worker --replicas=3`. 7. [M07] Farid Osman reported queue depth at 9,400 and falling ~1,200/min. Measurement command: not documented — needs confirmation. 8. [M08] Cole Ingram ran `bundle exec rake sidekiq:queue_depth` and reported that it returned 0. He also reported the Datadog error rate back to baseline. 9. [M09] Bryce Harmon re-enabled enqueue with `bin/rails runner 'FeatureFlag.enable(:auto_recognition_enqueue)'`. Verification: 40 new jobs processed cleanly in the next 3 minutes. Rollback for this step: not documented — needs confirmation. 10. [M10] Bryce Harmon scaled workers back down with `kubectl scale deployment/reward-worker --replicas=3`. Verification: he reported the queue stable at 0 and the incident resolved; direct replica-count verification is not documented — needs confirmation. Rollback for this step: not documented — needs confirmation.
The first logged error is at 2026-09-03 14:01:12 UTC: `reward-service` reports `Redis::TimeoutError` connecting to `redis-primary:6379` after 5 seconds (`datadog_logs.csv`). The cascade, in logged order: `reward-service` exhausts retries for `RewardGiveJob` (14:01:20–14:01:40) → `sidekiq` reports `RewardGiveJob` failures and retries (from 14:01:40) → the `reward` queue exceeds 10,000 (14:02:30) → `api-gateway` times out calling `reward-service` and returns 502s (from 14:03:05) → `web-app` reports failed Give form submissions from those 502s (from 14:03:30). `sidekiq_jobs.csv` also lists `RecognitionDigestJob` Redis timeouts: 12 `RewardGiveJob` + 4 `RecognitionDigestJob` = 16 listed failed jobs. `reward-service` logs Redis connection restoration at 14:22:10; `sidekiq` logs queue depth below 500 at 14:24:45. Datadog query to confirm the first error, scoped to that minute: `service:reward-service "Redis::TimeoutError" "redis-primary:6379"` Time range: 2026-09-03 14:01:00–14:02:00 UTC. The logs do not show why Redis timed out, whether the timeout began before this slice, how many users were affected, or whether every failed job ultimately succeeded.
The export names no individual companies, so only segments or targeting rules can be reported. An “off” flag may have configured targets, but the export does not show it enabled for them. | Flag | State | What the code excerpt controls | Targeting rule; company count | |---|---|---|---| | `recognition_streaks_v2` | On | Records a give in `StreakTracker`. | `segment:beta_companies`; 42 | | `points_budget_guardrails` | On | Enforces the giver’s points budget. | `all_companies`; 220 | | `slack_dm_nudges` | On | Allows the job to send a Slack DM nudge. | `segment:region_na`; 87 | | `redeem_flow_redesign` | Off | Renders `RedeemV2Component` when enabled; otherwise `RedeemV1Component`. | `targeted_list`; 12 configured targets | | `analytics_dashboard_v3` | On | Uses `AnalyticsV3` for the dashboard. | `segment:tier_three`; 65 | | `ms_teams_app_v2` | Off | Installs `TeamsAppV2` when enabled. | `targeted_list`; 9 configured targets | | `legacy_give_modal` | Off | No reference in the supplied code excerpt; behavior unknown. | `segment:legacy_plan`; 14 configured targets | | `survey_boosters_q3` | On | No reference in the supplied code excerpt; behavior unknown. | `segment:legacy_plan`; 7 | | `paused_offboard_cleanup` | Off | No reference in the supplied code excerpt; behavior unknown. | No targeting rule; 0 targets | Count check: on-flag counts sum to 42 + 220 + 87 + 65 + 7 = 421; off-flag configured-target counts sum to 12 + 9 + 14 + 0 = 35. These are sums across flags, not distinct-company totals; overlap is unknown. Sources: `flags_export.csv` and `flag_code.md` as provided.
NDA-1 — GREEN (standard approval): Mutual confidentiality, standard carve-outs, and Delaware law; §3 includes information that “is independently developed” and “must be disclosed by law or court order.” NDA-2 — YELLOW (counsel review): §4 adds an employment restriction: “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.” NDA-3 — RED (full legal review): §2 bars the Recipient from “engag[ing] in or provid[ing] services to any business that competes with Discloser’s business”; §3 selects “the laws of the Republic of Ireland” and exclusive jurisdiction there; §4 states “No confidentiality carve-outs are stated in this Agreement,” alongside the one-way, five-year term in §1.