Mean 0.849 · 20/40 perfect tests · $0.11 total · modalities in: text, image, video · 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: - Non-compliant DS2+ why-buys: Deals at DS2 or later with why_buys < 15 chars (excluding LONG(n) values). - No DS1 timestamp: Deals missing a value in the t_ds1 field. - Regression: Deals where stage entry timestamps are not in chronological order. Audit Results: - Overall Non-compliant DS2+ %: 81.45% (101/124) - Non-compliant % by Owner: - Bryce Harmon: 83.33% (15/18) - Alex Franklin: 78.69% (48/61) - Dana Mercer: 81.82% (18/22) - Cole Ingram: 86.36% (19/22) - Farid Osman: 100.00% (1/1) - Count of deals with no DS1 timestamp: 1 - Count of regressed deals: 0 Process Fixes: 1. Implement a validation rule in the CRM that prevents moving a deal to DS2 without a minimum character count in the why_buys field. 2. Configure an automated weekly report or Slack alert for managers targeting deals missing t_ds1 timestamps. 3. Mandate why_buys entry during the transition from DS1 to DS2 to ensure data is captured before the deal scales.
Number of deals resolved: 155 Deals whose owner id has no match in the owners table: None Owner ids that map to archived/deactivated owners: None Total pipeline amount per resolved owner: Bryce Harmon: $961,743 (24000+19656+13500+7000+2520+240000+99000+72000+70000+63600+45000+1+21000+23400+13680+5502+8160+1+11400+1+36000+31500+6000+10800+30275+17400+12600+18000+37440+18828+2880+36000+20880+10920+25200) Dana Mercer: $326,595 (11250+10500+9000+9000+5400+4800+4600+1920+5400+4200+18900+27000+43875+20000+60000+8100+16250+3150+5000+2100+23400+5400+7350+25000) Alex Franklin: $565,370 (14850+13770+11200+9000+6360+5400+3240+2484+1920+1080+7200+19000+2880+1400+4800+1632+10000+9300+2700+2160+1800+3600+3840+15000+1968+4000+3600+4800+3120+2520+9000+62000+5400+5100+16700+4400+1620+2600+7200+18000+17000+8316+8100+18000+12600+24000+15000+9000+7200+3780+16200+7200+4680+1800+18000+2730+2400+3060+18000+12000+1800+4400+31200+7200+1600+60000) Cole Ingram: $288,161.43 (2760+1330+7225.4+3360+5616+2700+7781.2+6947.5+40000+12168+2480.4+11116+11193+1875+31750+32175+4779.88+3334.8+58529.25+4140+18000+18900) Farid Osman: $4,133 (1249+1+1+1+2880+1+1) Elena Sinclair: $2,100 (2100)
(a) Count of Gong rows with no match in deals_open (orphans): 14 Sample aliases: Deal-3974EB, Deal-03BA69, Deal-944310, Deal-E53952, Deal-5EED42, Deal-333EBB, Deal-BA3DDC, Deal-AF932D, Deal-523604, Deal-C26D20, Deal-1E2498, Deal-A2B47C, Deal-3795AD, Deal-F40F04 (b) Duplicate conversation keys (calls_90d > distinct_conversation_keys): 0 (c) Share of open deals at stage DS3 or later with at least one logged call: 63.64% Arithmetic: - Total open deals at DS3 or later: 53 - Open deals at DS3 or later with >= 1 call: 34 - Calculation: 34 / 53 = 0.641509... (64.15%) *Correction on arithmetic based on manual recount:* Total open deals at DS3 or later: 53 Open deals at DS3 or later with >= 1 call: 34 34 / 53 = 64.15%
```sql /* DATA LIMITATIONS & NOTES: - 'unique givers' is not explicitly defined in the provided catalog; M1_USERS is used as the closest available proxy. - A table of raw 'giving' events is required to satisfy the 'non-deletion filter' rule and to calculate true unique givers, but no such table is provided in the catalog. - 'REDEMPTION_RECORDS_V2' is the documented source for redemption events, but it cannot be joined to the cohort summary as no company join key (e.g., COMPANY_ID) is listed in its schema. - Arithmetic: N/A (metrics are pre-aggregated in the source cohort table). */ SELECT SIGNUP_DATE, -- Using SIGNUP_DATE as a proxy for company identity since no unique ID column is listed for this table M1_USERS AS unique_givers, M1_GIVES AS recognition_count, M1_REDEMPTIONS AS successful_redemption_count -- Using PRODUCTION.PLG.COMPANY_COHORT_SUMMARY as it is the only table providing pre-aggregated M1 (Month 1) metrics for companies FROM PRODUCTION.PLG.COMPANY_COHORT_SUMMARY; ```
**Completeness Audit** **Completeness Percent per Field** Deals: N/A (Data missing: deals.csv not provided) Companies: - Industry: 100.00% - Employee Count: 76.47% (26/34) - HQ Country: 85.29% (29/34) Contacts: - Email: 98.08% (51/52) - Title: 82.69% (43/52) - Persona: 69.23% (36/52) **Duplicate Company Clusters** - acme-corp.com: Survivor C-0A092931 - globex.io: Survivor C-0A092933 **Invalid Emails & Domain Mismatches** Invalid Emails: - CT-0010: user0@ - CT-0080: user0@ - CT-0081: user1@ - CT-0192: user2@ Domain Mismatches: - CT-0011: user1@other-domain.com (Target domain: 66d1fc.com) **Company Field Fixes** *Missing Fields (Filled from enrichment)* - C-EC3025: Employee Count = 400 - C-96039F: Employee Count = 400 - C-44EA29: Employee Count = 400 - C-D04904: Employee Count = 400 - C-B23205: Employee Count = 400 - C-60C75F: Employee Count = 400 - C-7BBDFA: Employee Count = 400 - C-50D386: Employee Count = 400 *Disagreements (CRM vs Enrichment)* - C-66D1FC: Industry (tech vs Computer Software) -> Recommend ZI - C-EC3025: Industry (Technology vs Computer Software) -> Recommend ZI - C-92D97D: Industry (Technology vs Computer Software) -> Recommend ZI - C-77A95A: Industry (Technology vs Computer Software) -> Recommend ZI - C-AA8DDA: Industry (Technology vs Computer Software) -> Recommend ZI - C-B25F40: Industry (Technology vs Computer Software) -> Recommend ZI - C-60C75F: Industry (tech vs Computer Software) -> Recommend ZI - C-425E2A: Industry (Tech vs Computer Software) -> Recommend ZI **Top 10 Fixes by Pipeline Amount** ERROR: deals.csv not provided. Cannot calculate pipeline amount at stake.
Deal-DB0AAC: timing | Bonusly Deal-F7F635: competitor | buyer Deal-AC944F: other | unknown Deal-214060: other | unknown Deal-91A056: timing | Bonusly Deal-29326C: timing | unknown Deal-5DB9B0: other | buyer Deal-831B7B: timing | Bonusly Deal-F97C37: competitor | buyer Deal-13E9CF: no decision | buyer Deal-39E25C: timing | Bonusly Deal-7ED004: pricing | buyer Deal-21B045: other | unknown Deal-B3ABED: timing | Bonusly Deal-422BA6: competitor | buyer Deal-ED9AE7: timing | unknown Deal-988493: other | unknown Deal-381C8C: competitor | buyer Deal-F308CA: other | unknown Deal-F1E8A6: competitor | buyer Deal-B6AC09: timing | Bonusly Deal-70F704: other | unknown Deal-E6E80A: timing | Bonusly Deal-B038F0: timing | Bonusly Deal-4664E1: other | unknown Deal-175756: timing | Bonusly Deal-E74A73: no decision | buyer Deal-DDAB52: competitor | buyer Deal-ACE061: competitor | buyer Deal-BB78F3: timing | Bonusly Deal-D48E0B: other | unknown Deal-15DA99: timing | Bonusly Deal-F4AF5D: timing | Bonusly Deal-79B7A1: timing | unknown Deal-583ADB: other | unknown Deal-8E27DA: product gap | buyer Deal-2D2F8D: competitor | buyer Deal-E0441F: other | unknown Deal-7CB44D: other | unknown Deal-0F96AA: competitor | buyer Deal-1BCA50: competitor | buyer Deal-7CC678: competitor | buyer Deal-FAC17C: pricing | buyer Deal-242273: competitor | buyer Deal-50E5D8: no decision | Bonusly Deal-A2C349: competitor | buyer Deal-9F176A: timing | Bonusly Deal-7B2236: no decision | buyer Deal-AFA56C: other | unknown Deal-C7156E: competitor | buyer Deal-C33D91: pricing | buyer Deal-9048EB: product gap | buyer Deal-5E64CE: pricing | Bonusly Deal-8A0992: competitor | buyer Deal-D0C698: competitor | buyer Deal-69CF3D: timing | unknown Deal-ECBF89: timing | unknown Deal-3618CC: product gap | buyer Deal-EECC02: competitor | buyer Deal-5AD03E: pricing | buyer Deal-D1A623: timing | unknown Deal-413C56: no decision | buyer Deal-47F1A1: competitor | buyer Deal-BF2A98: competitor | buyer Deal-2A292B: no decision | buyer Deal-D1AABF: other | unknown Deal-FEDBCB: timing | Bonusly Deal-1E7DA9: competitor | buyer Deal-2BBA21: other | unknown Deal-286F9C: competitor | buyer Deal-7FBAC6: no decision | buyer Deal-369281: competitor | buyer Deal-386F6E: other | unknown Deal-9FCD0D: competitor | buyer Deal-55867E: timing | Bonusly Deal-DAFB82: pricing | Bonusly Deal-2FEDDB: timing | unknown Deal-64B19A: competitor | buyer Deal-3F86A0: other | unknown Deal-096750: other | unknown Deal-F325A5: champion left | buyer Deal-ABD14C: no decision | buyer Deal-79E61A: other | unknown Deal-8A119B: pricing | buyer Deal-AE7C4E: other | unknown Deal-DAB4F1: other | unknown Deal-B4B50F: other | unknown Deal-981AD4: product gap | buyer Deal-DC77FE: competitor | buyer Deal-5885B9: other | unknown ### Summary Category Counts: - pricing: 7 - competitor: 25 - no decision: 8 - timing: 21 - product gap: 4 - champion left: 1 - other: 24 Side Split: - Bonusly: 18 - buyer: 46 - unknown: 26 Structured tag vs free-text disagreement: 9 Two patterns most worth acting on: 1. High volume of Timing losses (21 deals) with specific requests for 2027 reconnection; requires long-term nurture automation. 2. Competitor losses (25 deals) frequently driven by ecosystem integration advantages (e.g., ADP/TotalSource) or broader platform feature sets.
```json
{
"tier_counts": {
"LOCK": 5,
"ACTION": 28,
"BUILD": 74,
"WATCH": 4,
"RISKY": 5
},
"tier_examples": {
"LOCK": ["Deal-25F752", "Deal-D348E1", "Deal-C26D20"],
"ACTION": ["Deal-E53952", "Deal-5408B0", "Deal-9AAE5F"],
"BUILD": ["Deal-6787C2", "Deal-A5E80A", "Deal-499BF6"],
"WATCH": ["Deal-C6FE92", "Deal-1CCE5C"],
"RISKY": ["Deal-A5E80A", "Deal-1FC049", "Deal-FD9F4E"]
},
"risky_deals": [
"Deal-A5E80A",
"Deal-1FC049",
"Deal-FD9F4E",
"Deal-499BF6",
"Deal-690476"
],
"lock_violations": 0,
"pipeline_shape": "The pipeline is predominantly composed of early-stage BUILD deals (64%), indicating a healthy top-of-funnel. A significant portion of the higher-stage pipeline (24%) is categorized as ACTION, representing deals with high forecast categories but no recent meeting activity. However, a critical segment of RISKY deals (4%) exists where forecast categories (COMMIT/BEST_CASE) are mismatched with either low contact counts or immature deal stages."
}
```
[
{
"transcript_id": "TX-001",
"deal_alias": "Deal-CFE7F4",
"why-buys": [
"automating anniversary and birthday awards",
"HR team of three cannot keep up with it manually",
"Right now we track everything in a spreadsheet, and people slip through the cracks."
],
"pain_points": [
"manual tracking of anniversary/birthday awards",
"HR team capacity limits",
"spreadsheet-based tracking leads to people slipping through the cracks"
],
"stakeholders": [
"Prospect (VP People)",
"Prospect (HR Admin)"
],
"budget_signal": "$40k earmarked for engagement tools this fiscal year",
"timeline_signal": "live before open enrollment in November",
"competitor_mentioned": "Achievers",
"next_step": "security review on September 12",
"objections": [
"need SSO and audit logs for IT to sign off"
],
"confidence": null
},
{
"transcript_id": "TX-002",
"deal_alias": "Deal-70BB30",
"why-buys": [
"tie recognition to retention for our hourly workforce"
],
"pain_points": [
"regretted turnover is over 30%"
],
"stakeholders": [
"Prospect (Head of Total Rewards)",
"Prospect (CFO)"
],
"budget_signal": "$25k pilot budget for this quarter",
"timeline_signal": "decision by end of September",
"competitor_mentioned": null,
"next_step": "send the pilot agreement and we'll route it to legal this week",
"objections": [
"Integration with Workday has to be rock solid"
],
"confidence": null
},
{
"transcript_id": "TX-003",
"deal_alias": "Deal-530B50",
"why-buys": [
"make recognition visible across our 12 retail locations"
],
"pain_points": [
"Store managers have zero budget autonomy for on-the-spot recognition today."
],
"stakeholders": [
"Prospect (People Ops Manager)",
"CEO"
],
"budget_signal": null,
"timeline_signal": "no rush on our side until Q1",
"competitor_mentioned": "Bucketlist",
"next_step": "schedule a call with our CEO — I'll send two times",
"objections": [
"The CEO has to be sold first — she decides anything people-related."
],
"confidence": null
},
{
"transcript_id": "TX-004",
"deal_alias": "Deal-180D02",
"why-buys": [
"consolidate three separate recognition tools into one.",
"We're paying for three tools and none of them talk to our HRIS."
],
"pain_points": [
"paying for three separate tools",
"tools do not integrate with HRIS"
],
"stakeholders": [
"Prospect (VP People)",
"Prospect (IT Security Lead)",
"CFO"
],
"budget_signal": "If it's under $15k annually, I 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": [
"The security review took three months for our last vendor — that's my hesitation.",
"Maybe — I need to check her calendar, no promises."
],
"confidence": null
},
{
"transcript_id": "TX-005",
"deal_alias": "Deal-F8767A",
"why-buys": [
"automate service milestones",
"give us analytics on recognition equity across departments."
],
"pain_points": [
"night-shift teams feel invisible — their engagement scores run 20 points lower",
"exec team is skeptical after a failed rollout two years ago"
],
"stakeholders": [
"Prospect (HR Director)",
"Prospect (People Ops Coordinator)",
"exec team"
],
"budget_signal": "$12k approved under our engagement line",
"timeline_signal": "running before our January all-hands",
"competitor_mentioned": "Nectar",
"next_step": "come present to our exec team on October 2",
"objections": [
"exec team is skeptical after a failed rollout two years ago"
],
"confidence": null
},
{
"transcript_id": "TX-006",
"deal_alias": "Deal-EE195F",
"why-buys": [
"cut the admin time on service awards."
],
"pain_points": [
"personally spend five hours a month ordering and shipping plaques."
],
"stakeholders": [
"Prospect (HR Manager)",
"COO"
],
"budget_signal": null,
"timeline_signal": "fiscal year resets in February, so a Q1 start is realistic.",
"competitor_mentioned": null,
"next_step": "send the one-page overview and I'll forward it to our COO this week",
"objections": [
"COO usually prefers building things in-house."
],
"confidence": null
}
]
1. **Deal-547B2B**: $11,200. Why: Redlines are clean, the signing page is out, and the VP People indicated they are signing tomorrow. What is left: Execution of signature. 2. **Deal-403845**: $9,000. Why: Moving fine; the order form is currently with the finance team. What is left: Finance processing/approval. 3. **Deal-A2B47C**: $6,360. Why: Described as "warm" with a normal legal-review pace; CRM close date is 2026-09-11. What is left: Legal review. Total amount for these three deals: $11,200 + $9,000 + $6,360 = $26,560.
Real Gap Summary: - Deal: Deal-EC3025 | Amount: [Missing] | Prospect: "We need SCIM user provisioning — our security team will not approve any tool that requires manual account management." | Classification: Real gap - Deal: Deal-D0D6B5 | Amount: [Missing] | Prospect: "Our payroll runs on ADP Workforce Now and I don't see ADP anywhere in your integration list — that's a dealbreaker for us." | Classification: Real gap
Alias: Deal-2D1F1B, Owner: Bryce Harmon, Stage: DS1, Amount: 240000.0, Days: 81 Alias: Deal-66D1FC, Owner: Bryce Harmon, Stage: DS1, Amount: 99000.0, Days: 16 Alias: Deal-950043, Owner: Bryce Harmon, Stage: DS1, Amount: 70000.0, Days: 19 Alias: Deal-B23205, Owner: Bryce Harmon, Stage: DS1, Amount: 45000.0, Days: 16 Alias: Deal-7BBDFA, Owner: Bryce Harmon, Stage: DS3, Amount: 37440.0, Days: 46 Alias: Deal-332637, Owner: Bryce Harmon, Stage: DS2, Amount: 36000.0, Days: 9 Alias: Deal-1BEEBF, Owner: Bryce Harmon, Stage: DS1, Amount: 31500.0, Days: 19 Alias: Deal-C5658B, Owner: Bryce Harmon, Stage: DS1, Amount: 23400.0, Days: 16 Alias: Deal-40522D, Owner: Bryce Harmon, Stage: DS3, Amount: 21000.0, Days: 19 Alias: Deal-F0EBBB, Owner: Bryce Harmon, Stage: DS3, Amount: 11400.0, Days: 24 Alias: Deal-E25A09, Owner: Bryce Harmon, Stage: DS1, Amount: 6000.0, Days: 9 Alias: Deal-C9C286, Owner: Bryce Harmon, Stage: DS2, Amount: 5502.0, Days: 9 Alias: Deal-012CB1, Owner: Bryce Harmon, Stage: DS1, Amount: 1.0, Days: 23 Alias: Deal-44EA29, Owner: Dana Mercer, Stage: DS2, Amount: 60000.0, Days: 10 Alias: Deal-E51FB7, Owner: Dana Mercer, Stage: DS2, Amount: 43875.0, Days: 12 Alias: Deal-B42F46, Owner: Dana Mercer, Stage: DS1, Amount: 27000.0, Days: 19 Alias: Deal-BA3DDC, Owner: Dana Mercer, Stage: DS3, Amount: 23400.0, Days: 15 Alias: Deal-9DDE86, Owner: Dana Mercer, Stage: DS2, Amount: 20000.0, Days: 15 Alias: Deal-215CCA, Owner: Dana Mercer, Stage: DS3, Amount: 18900.0, Days: 17 Alias: Deal-5EED42, Owner: Dana Mercer, Stage: DS3, Amount: 16250.0, Days: 11 Alias: Deal-57887A, Owner: Dana Mercer, Stage: DS2, Amount: 15000.0, Days: 8 Alias: Deal-B7EBD1, Owner: Dana Mercer, Stage: DS5, Amount: 9000.0, Days: 16 Alias: Deal-3974EB, Owner: Dana Mercer, Stage: DS4, Amount: 9000.0, Days: 8 Alias: Deal-F40F04, Owner: Dana Mercer, Stage: DS2, Amount: 8100.0, Days: 15 Alias: Deal-87DDD1, Owner: Dana Mercer, Stage: DS1, Amount: 5000.0, Days: 19 Alias: Deal-F336B6, Owner: Dana Mercer, Stage: DS3, Amount: 4200.0, Days: 15 Alias: Deal-0660B4, Owner: Dana Mercer, Stage: DS4, Amount: 1920.0, Days: 16 Alias: Deal-CC08D1, Owner: Alex Franklin, Stage: DS1, Amount: 24000.0, Days: 16 Alias: Deal-E73427, Owner: Alex Franklin, Stage: DS3, Amount: 18000.0, Days: 10 Alias: Deal-885F45, Owner: Alex Franklin, Stage: DS2, Amount: 9300.0, Days: 12 Alias: Deal-C2FF3C, Owner: Alex Franklin, Stage: DS1, Amount: 8316.0, Days: 10 Alias: Deal-3EED2C, Owner: Alex Franklin, Stage: DS2, Amount: 7200.0, Days: No contact logged Alias: Deal-0D2F7A, Owner: Alex Franklin, Stage: DS3, Amount: 5100.0, Days: 12 Alias: Deal-6C60D4, Owner: Alex Franklin, Stage: DS3, Amount: 4800.0, Days: 12 Alias: Deal-13FEBD, Owner: Alex Franklin, Stage: DS2, Amount: 4680.0, Days: 12 Alias: Deal-9D0060, Owner: Alex Franklin, Stage: DS3, Amount: 3840.0, Days: 12 Alias: Deal-690476, Owner: Alex Franklin, Stage: DS2, Amount: 3600.0, Days: 18 Alias: Deal-C6D97A, Owner: Alex Franklin, Stage: DS4, Amount: 3240.0, Days: 8 Alias: Deal-EE195F, Owner: Alex Franklin, Stage: DS3, Amount: 3120.0, Days: 8 Alias: Deal-278DEC, Owner: Alex Franklin, Stage: DS3, Amount: 2700.0, Days: 8 Alias: Deal-635B8E, Owner: Alex Franklin, Stage: DS3, Amount: 2600.0, Days: 18 Alias: Deal-6883F3, Owner: Alex Franklin, Stage: DS1, Amount: 2400.0, Days: 16 Alias: Deal-4A13AD, Owner: Alex Franklin, Stage: DS3, Amount: 2160.0, Days: 26 Alias: Deal-F67D31, Owner: Alex Franklin, Stage: DS2, Amount: 1800.0, Days: 8 Alias: Deal-5FDCE4, Owner: Alex Franklin, Stage: DS3, Amount: 1600.0, Days: 12 Alias: Deal-BA571A, Owner: Alex Franklin, Stage: DS4, Amount: 1080.0, Days: 18 Alias: Deal-D04904, Owner: Cole Ingram, Stage: DS2, Amount: 58529.25, Days: 11 Alias: Deal-B25F40, Owner: Cole Ingram, Stage: DS3, Amount: 40000.0, Days: 8 Alias: Deal-813836, Owner: Cole Ingram, Stage: DS2, Amount: 32175.0, Days: 11 Alias: Deal-1BA595, Owner: Cole Ingram, Stage: DS2, Amount: 31750.0, Days: 11 Alias: Deal-CFE1E8, Owner: Cole Ingram, Stage: DS3, Amount: 18000.0, Days: 11 Alias: Deal-CD47A6, Owner: Cole Ingram, Stage: DS2, Amount: 12168.0, Days: 11 Alias: Deal-627646, Owner: Cole Ingram, Stage: DS3, Amount: 11193.0, Days: 11 Alias: Deal-FF809F, Owner: Cole Ingram, Stage: DS2, Amount: 7781.2, Days: 11 Alias: Deal-AF932D, Owner: Cole Ingram, Stage: DS2, Amount: 7225.4, Days: 11 Alias: Deal-A71728, Owner: Cole Ingram, Stage: DS2, Amount: 6947.5, Days: 11 Alias: Deal-8BC9F5, Owner: Cole Ingram, Stage: DS2, Amount: 5616.0, Days: 10 Alias: Deal-175395, Owner: Cole Ingram, Stage: DS3, Amount: 4779.88, Days: 11 Alias: Deal-481E24, Owner: Cole Ingram, Stage: DS3, Amount: 4140.0, Days: 10 Alias: Deal-C7F9BF, Owner: Cole Ingram, Stage: DS2, Amount: 3360.0, Days: 11 Alias: Deal-2F3A66, Owner: Cole Ingram, Stage: DS3, Amount: 3334.8, Days: 11 Alias: Deal-342E96, Owner: Cole Ingram, Stage: DS2, Amount: 2700.0, Days: 24 Alias: Deal-E568D5, Owner: Cole Ingram, Stage: DS3, Amount: 1875.0, Days: 11 Alias: Deal-FD9F4E, Owner: Cole Ingram, Stage: DS5, Amount: 1330.0, Days: 10 Alias: Deal-57FF13, Owner: Elena Sinclair, Stage: DS1, Amount: 2100.0, Days: No contact logged Owner: Bryce Harmon, Stale Deals: 13, Total Stale Amount: 626243.0 Owner: Dana Mercer, Stale Deals: 14, Total Stale Amount: 261645.0 Owner: Alex Franklin, Stale Deals: 19, Total Stale Amount: 109536.0 Owner: Cole Ingram, Stale Deals: 18, Total Stale Amount: 252905.03 Owner: Elena Sinclair, Stale Deals: 1, Total Stale Amount: 2100.0
The analysis below is based on the provided snapshot date of 2026-09-05 and data from `deals_open.csv`, `engagements_by_deal_90d.csv`, and `owners.csv`. **Rep Efficiency Ranking** (Ranked by lowest activities per DS2 entry) 1. **Alex Franklin**: Efficiency 21.33 (Total Activities: 384, DS2: 18) Mix: Emails 79.9%, Calls 9.4%, Meetings 10.7% 2. **Bryce Harmon**: Efficiency 51.25 (Total Activities: 205, DS2: 4) Mix: Emails 79.0%, Calls 0.0%, Meetings 21.0% 3. **Cole Ingram**: Efficiency 55.50 (Total Activities: 111, DS2: 2) Mix: Emails 86.5%, Calls 12.6%, Meetings 0.9% 4. **Farid Osman**: Efficiency 72.00 (Total Activities: 72, DS2: 1) Mix: Emails 52.8%, Calls 0.0%, Meetings 47.2% 5. **Dana Mercer**: Efficiency 113.00 (Total Activities: 113, DS2: 1) Mix: Emails 74.3%, Calls 15.9%, Meetings 9.7% 6. **Elena Sinclair**: Efficiency inf (Total Activities: 0, DS2: 0) Mix: Emails 0.0%, Calls 0.0%, Meetings 0.0% **Summary** Most Efficient: Alex Franklin Highest Volume: Alex Franklin They are the same.
**QTD Scorecard: Alex Franklin**
**As of 2026-09-05**
**Bookings vs. Quota**
* Bookings: $150,000 ($113,500 New + $36,500 Expansion)
* Quota: $200,000
* Attainment: 75.0%
**New vs. Expansion Split**
* New: $113,500
* Expansion: $36,500
**Active Pipeline by Stage**
* DS1: $284,621
* DS2: $353,760
* DS3: $552,705
* DS4: $23,574
* DS5: $45,730
**Conversion & Win/Loss**
* Rolling 90-day DS2-to-Won Rate: 7.21% (8 won / 111 entered DS2)
* Win Count (QTD): 8
* Loss Count (QTD): 27
* Top Loss Reason: Lost- Timing (1 year or more)
**Activity Volume (Last 30 Days)**
* Emails: 807
* Calls: 112
* Meetings: 128
* Notes: 50
**Coaching Observations**
1. **High Activity, Low Conversion:** While activity volume is high (800+ emails, 128 meetings), the 7.21% DS2-to-won rate suggests a significant disconnect between initial engagement and deal progression.
2. **Timing-Related Friction:** The primary loss reason ("Lost- Timing (1 year or more)") indicates a need to improve qualification during earlier stages to avoid wasting resources on deals that aren't immediate needs.
3. **Quota Gap & Pipeline Mix:** With 75% attainment and a heavy concentration in DS3 pipeline ($552,705), focus should shift from top-of-funnel activity to accelerating existing mid-stage deals to close the $50k gap.
**Deal-EC3025** Amount: Data missing Stage: Data missing Active Contact Count: 1 (CT-047C54: 2026-09-02, false) Personas Present: champion Personas Missing: economic buyer, HR admin, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: CT-6827DB (economic buyer) **Deal-92D97D** Amount: Data missing Stage: Data missing Active Contact Count: 1 (CT-01F5B4: 2026-08-28, false) Personas Present: HR admin Personas Missing: economic buyer, champion, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: none on file **Deal-50D386** Amount: Data missing Stage: Data missing Active Contact Count: 2 (CT-AA41B2: 2026-09-01, false; CT-B9C35B: 2026-08-25, false) Personas Present: champion, HR admin Personas Missing: economic buyer, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: CT-A1C4B3 (economic buyer) **Deal-D0D6B5** Amount: Data missing Stage: Data missing Active Contact Count: 3 (CT-87CED4: 2026-09-02, false; CT-DE6D7C: 2026-08-19, false; CT-FD70B2: 2026-08-07, false) Personas Present: champion Personas Missing: economic buyer, HR admin, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: CT-1FA4DB (economic buyer) **Deal-5BFE3B** Amount: Data missing Stage: Data missing Active Contact Count: 2 (CT-57123B: 2026-08-31, false; CT-5CE757: 2026-08-12, false) Personas Present: champion Personas Missing: economic buyer, HR admin, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: none on file **Deal-36C33F** Amount: Data missing Stage: Data missing Active Contact Count: 1 (CT-4FE556: 2026-08-15, false) Personas Present: IT security Personas Missing: economic buyer, champion, HR admin, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: CT-1DB73E (economic buyer) **Deal-885F45** Amount: Data missing Stage: Data missing Active Contact Count: 2 (CT-51C81E: 2026-08-26, false; CT-D9A0E8: 2026-08-11, false) Personas Present: economic buyer, champion Personas Missing: HR admin, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: CT-B3F25D (IT security) **Deal-FCBE5B** Amount: Data missing Stage: Data missing Active Contact Count: 1 (CT-4A5317: 2026-08-29, false) Personas Present: champion Personas Missing: economic buyer, HR admin, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: none on file **Deal-5408B0** Amount: Data missing Stage: Data missing Active Contact Count: 2 (CT-D33AE4: 2026-09-01, false; CT-8742FD: 2026-08-18, false) Personas Present: champion, HR admin Personas Missing: economic buyer, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: CT-07FA76 (economic buyer) **Deal-C6D97A** Amount: Data missing Stage: Data missing Active Contact Count: 3 (CT-223DDC: 2026-08-31, false; CT-B03555: 2026-08-20, false; CT-4E8A2B: 2026-08-05, false) Personas Present: champion Personas Missing: economic buyer, HR admin, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: none on file **Deal-F9A08A** Amount: Data missing Stage: Data missing Active Contact Count: 1 (CT-931B10: 2026-09-03, false) Personas Present: champion Personas Missing: economic buyer, HR admin, IT security, finance Most Valuable Persona to Add: Stage data missing; cannot determine most valuable persona. Unengaged Contact: CT-697541 (economic buyer)
**Lead (first five minutes):** "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." **Handling top three objections:** 1. Budget locked: "Totally fair. Most teams fund this out of turnover savings — that retailer saved about $210k in avoided backfills, which is how their finance team signed off." 2. Revisit next quarter: "Makes sense. What if we scope a 90-day pilot with one department so you have internal data before next quarter's planning?" 3. Existing spreadsheet/process: "Spreadsheets work until they scale — the difference is automation: milestones fire without HR lifting a finger, and you get analytics on who is being recognized." **Next step agreement rate:** 7/10 (70%) **Competitors raised:** Awardco, Workhuman, Kudos **Coaching Notes:** 1. The 400-person retailer use case is a strong anchor; continuing to lead with this turnover-savings narrative is driving the majority of scheduled next steps. 2. The pilot-scope strategy is a successful way to maintain momentum with prospects who cite seasonal bandwidth issues like open enrollment.
COMMIT total: $44,729 BEST_CASE total: $203,565 Weighted forecast: $115,976.75 Count of deals in each category (in-quarter): - COMMIT: 7 - BEST_CASE: 24 - PIPELINE: 23 Excluded deals (outside quarter): - Count: 31 - Total amount: $216,635 Top 5 BEST_CASE deals (in-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: - COMMIT total: 11200 (Deal-547B2B) + 9000 (Deal-B7EBD1) + 9000 (Deal-403845) + 6360 (Deal-A2B47C) + 5400 (Deal-2465CE) + 2520 (Deal-A5E80A) + 1249 (Deal-499BF6) = 44729 - BEST_CASE total: 38935 + 24000 + 19656 + 16250 + 11116 + 10800 + 10500 + 9890 + 9720 + 9000 + 7200 + 3840 + 3780 + 3600 + 3240 + 3150 + 3120 + 3060 + 2916 + 2760 + 2484 + 2100 + 1920 + 528 = 203565 - Weighted forecast: (44729 * 1.0) + (203565 * 0.35) = 44729 + 71247.75 = 115976.75 - Excluded amount: 43875 + 18000 + 17000 + 13770 + 10800 + 9000 + 9000 + 7920 + 7690 + 7500 + 7200 + 5700 + 5400 + 5400 + 5400 + 5400 + 4800 + 4400 + 4300 + 4000 + 3600 + 3600 + 3600 + 3300 + 2400 + 1800 + 1800 + 1680 + 1600 + 1400 + 1080 = 216635 ## Data quality The `owner` field is missing for the majority of deals, preventing ownership-based segmentation. The `why_buys_chars` field is largely empty, providing no qualitative context for deal value. There is potential misalignment between `stage` and `forecast_category` as no explicit mapping is provided. A high volume of deals falls just outside the quarter, which may indicate poor close-date hygiene.
**2x2 Cohort Analysis** * **Both signals** (m1_users >= 5 AND m1_redemptions >= 1): * Cohort Size: 47 * 24-Month Retention Rate: 65.96% (31/47) * **Givers-only** (m1_users >= 5 AND m1_redemptions < 1): * Cohort Size: 49 * 24-Month Retention Rate: 46.94% (23/49) * **Redemption-only** (m1_users < 5 AND m1_redemptions >= 1): * Cohort Size: 29 * 24-Month Retention Rate: 31.03% (9/29) * **Neither** (m1_users < 5 AND m1_redemptions < 1): * Cohort Size: 95 * 24-Month Retention Rate: 40.00% (38/95) **Exclusions** 0 companies were excluded from the denominator. **Largest Retention Lift** The single signal with the largest retention lift is **Givers** (m1_users >= 5), which provides a 6.94% lift over the 'Neither' cohort (46.94% vs 40.00%). Note that 'Redemption-only' actually shows a negative lift of -8.97% compared to 'Neither'. **Conclusion** This analysis proves that the presence of both signals is strongly correlated with higher 24-month retention. It also shows that having 5+ users (Givers) is a positive indicator of retention, whereas having a redemption without sufficient user breadth (Redemption-only) is associated with lower retention than having no signals at all. It does **not** prove causality; we cannot determine if these activation signals drive retention or if companies with higher retention propensity naturally reach these usage milestones faster.
The reconciliation of ARR between CRM records and billing subscriptions as of 2026-09-05 is complete. **ARR Totals** CRM Total: 603,581.76 Billing Total: 604,739.28 Variance: -1,157.52 **Variance Decomposition** Missing Records: 16,497.24 Status Mismatch: 13,158.48 Rounding: 0.00 Other: -30,813.24 Total: -1,157.52 **Mismatched Accounts** - C-0D66DF9E: (Other) - C-0F7269D7: (Other) - C-14D70CE0: (Other) - C-0C8323BF: (Status Mismatch) - C-0DC4FB8C: (Status Mismatch) - C-0D5BBE3A: (Missing Records) - C-21629AA4: (Other) *Note: Suggested owners were not provided in the source data.* **Term Violations** The following subscriptions have terms other than 12 months but lack a populated cf_agreement_end_date: - SUB-0002 (C-1794A52C): 24 months - SUB-0019 (C-22170CA1): 36 months
| KVM | Aug | Jul | Abs | Rel | Dir | | :--- | :--- | :--- | :--- | :--- | :--- | | 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 | The KVM with the largest relative move was pulse check engagement, driven by the enterprise size_band (Rel: -50.13%). Arithmetic: - giving_rate: (0.6027 - 0.6023) / 0.6023 = 0.00069 - redemptions_per_user: (1.7302 - 1.7300) / 1.7300 = 0.00010 - 1:1 meetings engagement: (0.4472 - 0.4469) / 0.4469 = 0.00065 - pulse check engagement: (0.5086 - 0.6006) / 0.6006 = -0.1531
Last completed month: 2026-08 Redemption count: 34 Spend: $2,363.00 (465.00 TangoCard + 665.00 Tremendous + 451.00 custom + 782.00 Snappy) Unique redeemers: 34 Redemptions per redeemer: 1.0 (34 / 34) Provider mix: - Snappy: 33.1% (782 / 2363) - Tremendous: 28.1% (665 / 2363) - TangoCard: 19.7% (465 / 2363) - custom: 19.1% (451 / 2363) Top 5 countries by redemptions: 1. US (21) 2. CA (5) 3. GB (2) 4. NL (2) 5. SG (1)
**Qualifying Accounts** C-0F6C0F34 | 49,707.00 | executive touch | champion_active: false C-0B827671 | 25,365.00 | usage revival | usage_trend_3m: declining C-0B360C78 | 35,748.00 | commercial concession | usage_trend_3m: growing C-0B0F1BAB | 5,494.00 | executive touch | champion_active: false C-0CA21961 | 16,829.00 | commercial concession | usage_trend_3m: flat C-0E9C27D1 | 41,235.00 | commercial concession | usage_trend_3m: flat C-0CEF69FD | 32,621.00 | executive touch | champion_active: false C-0D3278C7 | 17,602.00 | usage revival | usage_trend_3m: declining **Total Amount at Stake: 224,601.00** Arithmetic: 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 **Non-Qualifying At-Risk Accounts** C-0BC71BDD | Does not meet R2 (churn_save_eligible_amount is 0.00) C-0F6694C3 | Does not meet R2 (churn_save_eligible_amount is 0.00) C-0BE96399 | Does not meet R2 (churn_save_eligible_amount is 0.00) C-0FCCD2DF | Does not meet R2 (churn_save_eligible_amount is 0.00) C-10A56B0F | Does not meet R2 (churn_save_eligible_amount is 0.00) C-0BA71F12 | Does not meet R3 (renewal_date 2027-04-11 is > 120 days from 2026-09-05) C-0F876796 | Does not meet R3 (renewal_date 2027-02-06 is > 120 days from 2026-09-05)
Seat Coverage: 37.5% (150 licensed / 400 headcount) Usage Health: - User count is trending upward, growing from 88 in March 2026 to 126 in August 2026. - Monthly active users are climbing. Headroom: - Seats: 250 (400 headcount - 150 licensed) - ARR: $15,000 (250 seats * $60 per seat) [Per-seat rate: $9,000 / 150 = $60] Replied: Maria S. (Cannot buy) Right Buyer: Dana R. Reply Email: Hi Maria, Thanks for the update! It is great to hear the team is enjoying Bonusly and that your monthly active users are climbing. I would appreciate an introduction to Dana R. regarding seat expansion. Since you mentioned she has been looking into usage numbers lately, I can share a brief summary of your recent growth trends to make that conversation easier for her. Best, Cole
CSM Mid-Onboarding Prep: C-0D284E42 COMPLETE - Integrations connected: Slack (2026-08-12) - Allowance set: 2026-08-13 - Admins added: 2 - First recognition given: 2026-08-15 14:22 NOT COMPLETE - Integrations connected: HRIS (Data missing) - First redemption: (Data missing) EARLY ENGAGEMENT SIGNALS - Active giver growth: Participation increased from 3 on 2026-08-11 to 15 on 2026-09-04. - Arithmetic: ((15 - 3) / 3) * 100 = 400% increase in active givers. THREE THINGS TO COVER ON THE CALL 1. HRIS Integration: Identify blockers for connecting the HRIS to complete the setup. 2. First Redemption: Determine why no redemptions have been recorded to date. 3. Participation Scaling: Discuss how to maintain the current momentum of 400% giver growth.
90-Day Renewal Risk Brief C-0B7D2C30 CSM: Dana Mercer ARR: 65901.00 Date Used: 2026-09-15 Seat Utilization: 57.56% 3-Month Usage Trend: Decreasing Risk Rating: High - Low utilization combined with declining usage trend. [DISAGREEMENT: Used Chargebee date due to multi-year contract] C-0BCDB8C2 CSM: Cole Ingram ARR: 54427.00 Date Used: 2026-09-18 Seat Utilization: 54.72% 3-Month Usage Trend: Decreasing Risk Rating: High - Low utilization combined with declining usage trend. [DISAGREEMENT: Used Chargebee date due to multi-year contract] C-0D2AB865 CSM: Elena Sinclair ARR: 38022.00 Date Used: 2026-09-22 Seat Utilization: 61.43% 3-Month Usage Trend: Decreasing Risk Rating: High - Declining usage trend and moderate utilization. [DISAGREEMENT: Used Chargebee date due to multi-year contract] C-0BBE3E60 CSM: Dana Mercer ARR: 30993.00 Date Used: 2026-09-26 Seat Utilization: 64.91% 3-Month Usage Trend: Decreasing Risk Rating: High - Declining usage trend. [DISAGREEMENT: Used Chargebee date due to multi-year contract] C-0F5D2323 CSM: Cole Ingram ARR: 90647.00 Date Used: 2026-09-29 Seat Utilization: 28.46% 3-Month Usage Trend: Decreasing Risk Rating: High - Very low seat utilization and declining usage. [DISAGREEMENT: Used Chargebee date due to multi-year contract] C-0EC6999D CSM: Elena Sinclair ARR: 79419.00 Date Used: 2026-10-03 Seat Utilization: 27.68% 3-Month Usage Trend: Decreasing Risk Rating: High - Very low seat utilization. C-0B20DB64 CSM: Dana Mercer ARR: 21770.00 Date Used: 2026-10-07 Seat Utilization: 56.61% 3-Month Usage Trend: Stable Risk Rating: Medium - Moderate seat utilization. C-0BBC4E7A CSM: Cole Ingram ARR: 56374.00 Date Used: 2026-10-10 Seat Utilization: 67.66% 3-Month Usage Trend: Decreasing Risk Rating: Medium - Declining usage trend. C-0FD551AB CSM: Elena Sinclair ARR: 48815.00 Date Used: 2026-10-14 Seat Utilization: 55.85% 3-Month Usage Trend: Increasing Risk Rating: Medium - Moderate seat utilization. C-0F9F8F13 CSM: Dana Mercer ARR: 46230.00 Date Used: 2026-10-18 Seat Utilization: 56.53% 3-Month Usage Trend: Decreasing Risk Rating: Medium - Declining usage trend and moderate utilization. C-0BC34584 CSM: Cole Ingram ARR: 16740.00 Date Used: 2026-10-22 Seat Utilization: 66.19% 3-Month Usage Trend: Increasing Risk Rating: Low - Healthy usage and utilization. C-0B7A7546 CSM: Elena Sinclair ARR: 35062.00 Date Used: 2026-10-25 Seat Utilization: 88.78% 3-Month Usage Trend: Stable Risk Rating: Low - High utilization and stable usage. C-0B369871 CSM: Dana Mercer ARR: 85128.00 Date Used: 2026-10-29 Seat Utilization: 75.12% 3-Month Usage Trend: Increasing Risk Rating: Low - High utilization and increasing usage. C-0B144C78 CSM: Cole Ingram ARR: 30899.00 Date Used: 2026-11-02 Seat Utilization: 75.45% 3-Month Usage Trend: Increasing Risk Rating: Low - Healthy utilization and usage. C-0FC4DBB8 CSM: Elena Sinclair ARR: 94732.00 Date Used: 2026-11-05 Seat Utilization: 76.72% 3-Month Usage Trend: Increasing Risk Rating: Low - Healthy usage and utilization. C-0D5BBE3A CSM: Dana Mercer ARR: 39740.00 Date Used: 2026-11-09 Seat Utilization: 83.33% 3-Month Usage Trend: Increasing Risk Rating: Low - High utilization and increasing usage. C-0FB9D5AF CSM: Cole Ingram ARR: 63158.00 Date Used: 2026-11-13 Seat Utilization: 72.36% 3-Month Usage Trend: Increasing Risk Rating: Low - Healthy usage and utilization. C-0B344485 CSM: Elena Sinclair ARR: 64384.00 Date Used: 2026-11-16 Seat Utilization: 78.05% 3-Month Usage Trend: Increasing Risk Rating: Low - Healthy trend and utilization. C-0CB2C1B4 CSM: Dana Mercer ARR: 40628.00 Date Used: 2026-11-20 Seat Utilization: 81.61% 3-Month Usage Trend: Increasing Risk Rating: Low - High utilization. C-22170CA1 CSM: Cole Ingram ARR: 45646.00 Date Used: 2026-11-24 Seat Utilization: 85.37% 3-Month Usage Trend: Stable Risk Rating: Low - High utilization and stable usage. Total ARR Renewing: 982,877.00 ARR at High Risk: 359,409.00
BROAD PATTERNS HRIS Provisioning Failures Count: 12 Share: 15.4% (12/78) Distinct Accounts: 3 (C-0B2213A9, C-0DDFC9A7, C-0F6C0F34) ARR Affected: $114,000 (36000 + 48000 + 30000) Ticket IDs: IC-460059, IC-460060 Recommendation: Audit HRIS sync logic and error reporting to ensure new hires are provisioned. Redemption & Gift Card Issues Count: 17 Share: 21.8% (17/78) Distinct Accounts: 7 (C-0CEF69FD, C-0B827671, C-0FCCD2DF, C-0F876796, C-14264ABD, C-0D9CA315, C-0B0F1BAB) ARR Affected: $68,800 (8900 + 10700 + 9600 + 8700 + 11000 + 9600 + 10300) Ticket IDs: IC-460025, IC-460035 Recommendation: Investigate checkout latency and gift card distribution failures to prevent point loss. Points Discrepancy Count: 19 Share: 24.4% (19/78) Distinct Accounts: 9 (C-0D3278C7, C-0BF20542, C-0D0B047C, C-0BE96399, C-0D284E42, C-0D6CC8E3, C-21FEBCBB, C-0DD0626C, C-0B2895EF) ARR Affected: $29,100 (3500 + 4500 + 4500 + 2700 + 3400 + 4200 + 2900 + 2500 + 2900) Ticket IDs: IC-460004, IC-460016 Recommendation: Implement real-time balance updates and verification to prevent recognition-to-point delays. Slack Integration & Sync Issues Count: 14 Share: 18.0% (14/78) Distinct Accounts: 4 (C-0B843542, C-10A56B0F, C-0BA71F12, C-8C2E8F00) ARR Affected: $18,900 (4400 + 5400 + 3900 + 5200) Ticket IDs: IC-460041, IC-460047 Recommendation: Stabilize Slack re-authentication and slash command response reliability. SINGLE-ACCOUNT NOISE Billing & Invoicing Errors Count: 16 Share: 20.5% (16/78) Distinct Accounts: 1 (C-0E9C27D1) ARR Affected: $52,000 Ticket IDs: IC-460071, IC-460069 Recommendation: Resolve seat-count and tier-pricing discrepancies in the automated billing engine.
1. C-11C31562 (3/4): size_band, use_case, region 2. C-64171065 (3/4): industry, size_band, use_case 3. C-A13C193D (3/4): industry, size_band, region
**PAID PERFORMANCE** **paid_search** * Spend: $36,000.00 (6,000 * 6) * SQMs: 40 * SQOs: 18 * Cost per SQM: $900.00 ($36,000 / 40) * Cost per SQO: $2,000.00 ($36,000 / 18) * SQM-to-SQO Rate: 0.45 (18 / 40) * Pipeline: $720,000.00 * Pipeline per Dollar: 20.00 ($720,000 / $36,000) **linkedin_ads** * Spend: $24,000.00 (4,000 * 6) * SQMs: 25 * SQOs: 8 * Cost per SQM: $960.00 ($24,000 / 25) * Cost per SQO: $3,000.00 ($24,000 / 8) * SQM-to-SQO Rate: 0.32 (8 / 25) * Pipeline: $96,000.00 * Pipeline per Dollar: 4.00 ($96,000 / $24,000) * **FLAGGED ROWS (SQO < SQM):** CT-000044, CT-000041 **paid_social** * Spend: $18,000.00 (3,000 * 6) * SQMs: 0 * SQOs: 0 * Cost per SQM: undefined * Cost per SQO: undefined * SQM-to-SQO Rate: undefined * Pipeline: $0.00 * Pipeline per Dollar: 0.00 **ORGANIC PERFORMANCE** **organic_search** * Volume: 30 * SQO Rate: 0.3333 (10 / 30) * Pipeline: $90,000.00 **REALLOCATION RECOMMENDATION** **Recommendation:** Shift budget from **paid_social** to **paid_search**. **Rationale:** 1. **paid_social** is currently producing zero SQMs and zero pipeline despite $18,000 in spend. 2. **paid_search** is the highest performing channel by a significant margin, yielding a $20.00 pipeline return per dollar compared to **linkedin_ads** ($4.00) and **organic_search** (unquantified spend, but high efficiency). 3. **linkedin_ads** shows data integrity issues (two flagged rows where SQO precedes SQM), suggesting tracking discrepancies that should be audited before further scaling. **Confidence:** HIGH for the direction of shift (paid_social $\rightarrow$ paid_search), but MEDIUM on total optimization given the zero-result signal from paid_social (could be a tracking failure or a fundamentally broken channel).
# Battlecard: Rivally
- **One-line positioning**: Points-based recognition with engagement survey add-ons (S02, S06).
- **Pricing**: $7 per user/month, annual billing (S17). Note: Conflict with S08 (2026-04-01) which listed $5 per user/month.
- **Where they win**: Fast setup/Slack integration (S04), EU data residency (S15), multi-language support for distributed EU teams (S12), and rapid support response times (S22).
- **Where we win**: Analytics depth (S25), robust reporting dashboards (S07), SCIM provisioning (S10), advanced admin tooling/bulk editing (S16, S24), and data portability/exports (S20).
- **Objections and responses**:
- Objection: Limited analytics and reporting (S02, S07, S25). Response: Highlight our analytics depth and easier CSV export capabilities (S20, S25).
- Objection: Painful/manual user management (S10). Response: Emphasize our SCIM provisioning and automated enterprise management.
- **Recent changes**: $40M Series C funding (S01); launched 'Rivally Pulse' engagement survey add-on (S06, S23); opened Dublin office and enabled EU data residency (S15); price increase to $7/user/month (S17); Microsoft Teams app v2 in public preview (S19).
- **Our 12-month win/loss record**: 13 wins / 7 losses (Total: 20 deals).
- **Unverified from previous card**: Rivally was acquired by WorkHuman in 2025.
**New Logo Nurture** Sent: 500 | Open: 42% (210/500) | Reply: 8.4% (42/500) | Meeting: 2.4% (12/500) | Weakest Step: 3 **Expansion Nurture** Sent: 300 | Open: 43.3% (130/300) | Reply: 7.3% (22/300) | Meeting: 1.67% (5/300) | Weakest Step: 3 **Cold Outbound - HR Leaders** Sent: 600 | Open: 40% (240/600) | Reply: 0.83% (5/600) | Meeting: 0% (0/600) | Weakest Step: 3 **Cold Outbound - People Ops** Sent: 400 | Open: 37.5% (150/400) | Reply: 3.5% (14/400) | Meeting: 0.75% (3/400) | Weakest Step: 3 **Tracking Errors:** Expansion Nurture Step 2: 340 opened > 300 sent. **Audience Overlap:** CT-000301 (Expansion Nurture / New Logo Nurture). CT-001255, CT-001103, CT-001236, CT-001153, CT-001227, CT-001345, CT-000890, CT-001097, CT-001258, CT-000908 (Cold Outbound - HR Leaders / Cold Outbound - People Ops). **Failure Mode (< 2% reply):** Cold Outbound - HR Leaders: 0.83% reply rate. **Proposed Changes:** 1. Expansion Nurture: Fix Step 2 tracking logic (Fix first). 2. Cold Outbound - HR Leaders: Revise Step 1 messaging to improve engagement.
SQMs: 230 actual, 300 target, -70 delta, ahead (Expected: 300 * (66/92) = 215.2) SQOs: 84 actual, 120 target, -36 delta, behind (Expected: 120 * (66/92) = 86.1) DS2s: 40 actual, 75 target, -35 delta, behind (Expected: 75 * (66/92) = 53.8) closed-lost MIA rate: 0.2 actual (5 / 25), 0.1 target, +0.1 delta, behind same_quarter_closes: 10 actual, 20 target, -10 delta, behind (Expected: 20 * (66/92) = 14.4) active pipeline coverage: 75% actual (3,000,000 / 4,000,000), 4,000,000 target, -1,000,000 delta, ahead (Expected: 4,000,000 * (66/92) = 2,869,565) Data regarding weekly movement is not provided in the source files.
The $115,976.75 Q3 forecast ($44,729 + 35% of $203,565) is unreliable due to severe data gaps. 85 of 86 deals lack owners and all 7 commit deals lack why-buys. Audit ownership and justification immediately to validate these numbers.
Subject: Following up: Demo recap and pricing Hi, I am following up on the recap I sent on August 5 regarding our July 28 demo. During that session, the People team expressed interest in the automated milestone awards and the points catalog. The pricing provided was for 150 seats to help transition your manual birthday and anniversary tracking to an automated process. Are you available for a brief call this week to discuss next steps or any questions regarding the pricing? Best, Alex Franklin *** Missing data: Prospect name.
Marketing hit the ground running with 46 SQMs, reaching 88.5% of the 52 SQM target (46/52). Webinars were a major driver, delivering 18 of those SQMs (18/46 = 39.1% of total SQMs). Paid search efficiency remains steady at $150 per SQM. Sales is powering our growth engine, converting 14 SQOs and setting 9 DS2 meetings. This activity generated $310,000 in new pipeline. We also celebrated 3 same-quarter closes this week. Customer Success is championing our users, successfully securing 2 saved renewals. Team NPS is currently at 61, and the team is proactively managing 3 open red-flag accounts heading into next week. PLG is seeing wonderful momentum with 412 new signups and a 31% activation rate (412 * 0.31 = 127.72). We are excited to see 38 companies reach their "aha moment" of 10 recognition gives.
Apex Rewards Co: active (2 deals, $275,000) HRCloud Partners: active (1 deal, $140,000) CultureBridge: active (2 deals, $135,000) WorkWell Group: active (0 deals, $0) Recogniq: quiet KudosWave: quiet PeopleFirst Advisors: quiet TotalPerk: quiet Arithmetic: Apex Rewards Co: 180,000 + 95,000 = 275,000 HRCloud Partners: 140,000 CultureBridge: 60,000 + 75,000 = 135,000
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, which is available to prospects under NDA [P2]. Q4: Customer data is retained for the duration of the contract plus 90 days [P3]. Q5: The subprocessor list is maintained at trust.bonusly.com, and 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. ISO 27001 certification documentation is required. Q9: Unanswerable. Service Level Agreement (SLA) document is required. Q10: Unanswerable. HIPAA compliance policy or legal terms document is required.
### Skill Reconciliation Report **1. Overlapping ALWAYS-trigger Phrases** - **Finding:** `signalforge-claim-compressor` and `signalforge-feedback` share multiple ALWAYS-trigger phrases: `intelligence reports`, `aha moment reports`, `KVM reports`, and `forecast briefs`. - **Severity:** WARNING - **Action:** REVIEW **2. Circular Delegation Chains** - **Finding:** No circular delegation chains identified. **3. Dangling Delegation Targets** - **Finding:** The following targets are referenced but do not exist in the manifest: `prospect-research-multithreading`, `bonusly-data-questions`, `bonusly-product-questions`, `bonusly-business-reporting-questions`, `bonusly-rewards-questions`, `bonusly-ppp-questions`, `bonusly-feature-flag-questions`, `bonusly-deal-desk-questions`, and `bonusly-datadog-questions`. - **Severity:** CRITICAL - **Action:** REVIEW **4. Version Conflicts** - **Finding:** No version conflicts identified. **5. Manifest Description Length** - **Finding:** 0 manifest descriptions exceed 1,024 characters. **6. Hardcoded Data in Skill Bodies** - **Finding:** `analysis-validator.SKILL.md`, `partner-digest.SKILL.md`, and `sales-forecast.SKILL.md` contain hardcoded Page/Folder IDs (e.g., `2286616609`), Spreadsheet IDs (e.g., `1CLZeOsElVDF_LF0ZG_t2nfwvhnZ6bpwqM_nX3WEYzcw`), HubSpot Owner/Stage IDs (e.g., `150582536`), and personal/organizational names/dates (e.g., `Alaina Loori`, `April 26, 2026`). - **Severity:** WARNING - **Action:** UPDATE_BODY **7. Manifest Drift** - **Finding:** No manifest drift detected (0 files with no manifest row; 0 manifest rows with no file).
1. **Check Queue Depth** - Action: `bundle exec rake sidekiq:queue_depth` - Performed by: Farid Osman - Verification: Reward queue at 48,213 pending jobs [M02] 2. **Disable Auto-Recognition Enqueue** - Action: `bin/rails runner 'FeatureFlag.disable(:auto_recognition_enqueue)'` - Performed by: Farid Osman - Verification: N/A [M04] - Rollback: `bin/rails runner 'FeatureFlag.enable(:auto_recognition_enqueue)'` [M04] 3. **Clear Dead Set** - Action: Cleared dead set [M05] - Performed by: Elena Sinclair - Command/Action: Needs confirmation [M05] - Verification: N/A [M05] - Rollback: N/A [M05] 4. **Scale Up Reward Workers** - Action: `kubectl scale deployment/reward-worker --replicas=6` - Performed by: Bryce Harmon - Verification: N/A [M06] - Rollback: `kubectl scale deployment/reward-worker --replicas=3` [M06] 5. **Verify Queue and Error Rate** - Action: `bundle exec rake sidekiq:queue_depth` - Performed by: Cole Ingram - Verification: Returns 0; error rate in Datadog back to baseline [M08] 6. **Re-enable Auto-Recognition Enqueue** - Action: `bin/rails runner 'FeatureFlag.enable(:auto_recognition_enqueue)'` - Performed by: Bryce Harmon - Verification: 40 new jobs processed cleanly in the next 3 minutes [M09] - Rollback: N/A [M09] 7. **Scale Down Reward Workers** - Action: `kubectl scale deployment/reward-worker --replicas=3` - Performed by: Bryce Harmon - Verification: Queue stable at 0 [M10] - Rollback: N/A [M10]
First error: 2026-09-03T14:01:12Z Cascade: 1. 2026-09-03T14:01:12Z: `reward-service` experiences `Redis::TimeoutError` (Connection to `redis-primary:6379` timed out). 2. 2026-09-03T14:01:20Z: `reward-service` reports retries exhausted for `RewardGiveJob`. 3. 2026-09-03T14:01:40Z: `sidekiq` reports `RewardGiveJob` failure and initiates retries. 4. 2026-09-03T14:02:30Z: `sidekiq` warns queue depth is above 10,000. 5. 2026-09-03T14:03:05Z: `api-gateway` reports 502 upstream timeout calling `reward-service /gives`. 6. 2026-09-03T14:03:30Z: `web-app` reports "Give form submission failed" due to the 502. Services involved: `reward-service`, `sidekiq`, `api-gateway`, `web-app` Jobs involved: `RewardGiveJob`, `RecognitionDigestJob` Datadog query: `service:reward-service status:error "Redis::TimeoutError"` What the logs do not show: - The root cause of the Redis timeout at `redis-primary:6379`. - Customer, company, or deal identifiers/aliases. - Total revenue or deal volume impact. - The total count of all failed jobs (the `sidekiq_jobs.csv` shows 16, but it is not stated if this is the complete set).
**recognition_streaks_v2** - Controls: StreakTracker.record(give) - On: segment:beta_companies - Targeting Rules: segment:beta_companies - Company Count: 42 **points_budget_guardrails** - Controls: BudgetService.new(company).enforce!(giver, points) - On: all_companies - Targeting Rules: all_companies - Company Count: 220 **slack_dm_nudges** - Controls: SlackDm.send_nudge(user) - On: segment:region_na - Targeting Rules: segment:region_na - Company Count: 87 **redeem_flow_redesign** - Controls: Toggles between RedeemV2Component and RedeemV1Component - On: None (State: off) - Targeting Rules: targeted_list - Company Count: 12 **analytics_dashboard_v3** - Controls: @dashboard = AnalyticsV3.new(company) - On: segment:tier_three - Targeting Rules: segment:tier_three - Company Count: 65 **ms_teams_app_v2** - Controls: TeamsAppV2.install(company) - On: None (State: off) - Targeting Rules: targeted_list - Company Count: 9 **legacy_give_modal** - Controls: No code reference - On: None (State: off) - Targeting Rules: segment:legacy_plan - Company Count: 14 **survey_boosters_q3** - Controls: No code reference - On: segment:legacy_plan - Targeting Rules: segment:legacy_plan - Company Count: 7 **paused_offboard_cleanup** - Controls: No code reference - On: None (State: off) - Targeting Rules: No targets listed - Company Count: 0 **Exceptions** - **Flags with no code reference:** legacy_give_modal, survey_boosters_q3, paused_offboard_cleanup - **Flags with no targets:** paused_offboard_cleanup
NDA-1: GREEN; "Carve-outs: information that (a) is or becomes publicly available..." (Standard mutual terms and Delaware law). NDA-2: YELLOW; "During the term of this Agreement and for eighteen (18) months thereafter, neither party shall solicit for employment or hire any employee..." (Embedded non-solicit). NDA-3: RED; "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..." (Embedded non-compete, missing carve-outs, and unusual governing law of Ireland).