Mean 0.923 · 28/40 perfect tests · $0.44 total · each card: the question → the correct answer (gold) → this model's actual answer
## Stage Hygiene Audit **Definitions:** - *DS2+* = deals in stage DS2, DS3, DS4, or DS5 - *Substantive why_buys* = 15+ characters of real text, OR LONG(n) marker indicating truncated substantive text - *DS1 timestamp* = a non-empty t_ds1 field - *Regressed* = a deal where an earlier-stage timestamp is later than a later-stage timestamp (t_dsN > t_ds(N+1) for any N) --- **Why-Buys Compliance (DS2+ Deals):** | Owner | DS2+ Deals | Compliant | Non-Compliant | Non-Compliant % | |-------|------------|-----------|---------------|-----------------| | Bryce Harmon (119337721) | 36 | 3 | 33 | 91.7% | | Alex Franklin (84342457) | 39 | 8 | 31 | 79.5% | | Dana Mercer (83155923) | 13 | 2 | 11 | 84.6% | | Cole Ingram (83155924) | 12 | 5 | 7 | 58.3% | | **Overall** | **100** | **18** | **82** | **82.0%** | *Note: owner 716654662 (Farid Osman) has 0 DS2+ deals.* --- **Other Hygiene Metrics:** - **Deals with no DS1 timestamp:** 0 - **Deals that regressed:** 0 --- **Three Process Fixes:** 1. **Mandatory why_buys entry at DS2 transition** — block stage advancement unless why_buys field contains 15+ characters or is flagged LONG; auto-notify rep on empty submission. 2. **Weekly why_buys audit report** — automate a dashboard highlighting DS2+ deals with missing/placeholder why_buys, bucketed by owner, to surface hygiene gaps before deals stall. 3. **Stage-timestamp validation rule** — enforce at-time-of-transition that t_ds(N+1) ≥ t_dsN; reject saves that create regressions and require correction before proceeding.
⚠ Stream stalled mid tool-call (execute_code); the action was not executed. Ask me to retry if you want to continue.**RESULTS** **Number of deals resolved:** 156 **Deals whose owner_id has no match in the owners table:** NONE — all 156 owner_ids matched to a row in the owners table. **Owner_ids that map to archived/deactivated owners:** NONE — all resolved owners (119337721, 83155923, 84342457, 83155924, 716654662, 701163055) have `archived=false` in the owners table. The two archived owners (Gavin Porter ID 1520255671, Hugo Lindqvist ID 77260721) have no deals in this extract. **Total pipeline amount per resolved owner:** | Owner | Owner ID | Total Pipeline | # Deals | |-------|----------|----------------|---------| | Bryce Harmon | 119337721 | $1,054,144.00 | 35 | | Alex Franklin | 84342457 | $624,310.00 | 67 | | Dana Mercer | 83155923 | $341,195.00 | 24 | | Cole Ingram | 83155924 | $288,161.43 | 22 | | Farid Osman | 716654662 | $4,134.00 | 7 | | Elena Sinclair | 701163055 | $2,100.00 | 1 | **Combined pipeline total:** $2,314,044.43
## Call-to-Deal Mapping Integrity Report ### (a) Orphan Gong Rows **Count: 30** (gong rows whose deal ID has NO match in deals_open) Sample aliases: - Deal-B038F0 - Deal-9A43B4 - Deal-D84A2D - Deal-51EA1A - Deal-36EA09 - Deal-76821A - Deal-344163 - Deal-3B6668 - Deal-5592CC - Deal-8FA85D *These are deals that exist in Gong (have recorded calls in last 90 days) but are NOT in the current open default-pipeline. Likely closed-won, closed-lost, or moved to another pipeline.* --- ### (b) Duplicate Conversation Keys **Count: 0** No rows have `calls_90d > distinct_conversation_keys`. The data is consistent — every call maps to a unique conversation key. --- ### (c) DS3+ Open Deals with Logged Calls - **Total DS3+ deals (DS3, DS4, DS5):** 85 - **With at least one logged call:** 25 - **Share:** **29.4%** *Among deals advanced to stage DS3 or later in the current open pipeline, fewer than a third have any Gong-recorded calls in the past 90 days.*
Looking at the catalog, I can identify: 1. **Customer companies**: From `OBJECTS_DEALS` (HubSpot deals → companies via associations) 2. **First calendar month as a customer**: From `PROPERTY_CLOSEDATE` on deals 3. **Recognition count**: Requires a recognitions/giving table — **not present in this catalog** 4. **Successful redemption count**: From `PRODUCTION.DEPRECATED_RECOGNITION.REDEMPTION_RECORDS_V2` with `STATE = 'succeeded'` The catalog references "deleted givers" but provides **no recognitions or givers table** in this excerpt. I cannot compute "unique givers" or "recognition count" without that data source. **The catalog is insufficient** for the requested query. I need one of: - A recognitions/giving events table (the "deleted givers" filter implies one exists) - Or clarification on which table provides giver/recognition data Would you like me to: 1. **Query using only available tables** (deals → redemption records, producing company-level redemption metrics per first month, but skipping givers/recognition)? 2. **Check for other tables** in the warehouse that might contain recognitions data?
⚠ Stream stalled mid tool-call (execute_code); the action was not executed. Ask me to retry if you want to continue.============================================================
CRM EXTRACT AUDIT REPORT
============================================================
### COMPLETENESS PERCENTAGE
**COMPANIES (34 records):**
- industry: 34/34 = 100.0%
- employee_count: 25/34 = 73.5%
- hq_country: 28/34 = 82.4%
**CONTACTS (52 records):**
- email: 52/52 = 100.0%
- title: 40/52 = 76.9%
- persona: 37/52 = 71.2%
**DEALS (156 records):**
- owner_id: 156/156 = 100.0%
- stage: 156/156 = 100.0%
- amount: 156/156 = 100.0%
- close_date: 156/156 = 100.0%
- why_buys: 23/156 = 14.7%
---
### DUPLICATE COMPANY CLUSTERS
**Cluster 1: acme-corp.com**
- C-0A092931: industry='Technology', employees='500', country='US'
- C-0A092932: industry='tech', employees='510', country='USA'
- **SURVIVOR: C-0A092931** (most complete)
**Cluster 2: globex.io**
- C-0A092933: industry='SaaS', employees='200', country='US'
- C-0A092934: industry='Technology', employees='200', country='US'
- **SURVIVOR: C-0A092933** (first entry)
---
### INVALID EMAILS
| Contact Key | Email | Company |
|-------------|-------|---------|
| CT-0010 | user0@ (incomplete) | C-66D1FC |
| CT-0080 | user0@ (incomplete) | C-92D97D |
| CT-0081 | user1@ (incomplete) | C-92D97D |
| CT-0192 | user2@ (incomplete) | C-425E2A |
---
### DOMAIN MISMATCHES
| Contact Key | Email | Listed Domain | Issue |
|-------------|-------|---------------|-------|
| CT-0011 | user1@other-domain.com | 66d1fc.com | **MISMATCH** - email domain does not match company domain |
---
### CRM vs ENRICHMENT DISCREPANCIES (21 total)
| Company | Field | CRM Value | Enrichment Value | Recommendation |
|---------|-------|-----------|------------------|----------------|
| C-66D1FC | industry | tech | Computer Software | Use enrichment |
| C-66D1FC | hq_country | US | United States | Use enrichment |
| C-B25F40 | employee_count | 50 | 120 | Use enrichment (conflicts) |
| C-B25F40 | industry | Tech | Computer Software | Use enrichment |
| C-425E2A | industry | Tech | Computer Software | Use enrichment |
**General recommendation:**
- Fill blank employee_count/hq_country from enrichment where available
- Standardize hq_country to full names ("United States" not "US"/"USA")
- Use enrichment "Computer Software" over vague "Technology"/"Tech"
---
### TOP 10 FIXES BY PIPELINE AT STAKE
| # | Object | Field | Identifier | Pipeline |
|---|--------|-------|------------|----------|
| 1 | COMPANY | hq_country | C-2D1F1B | $240,000 |
| 2 | CONTACT | title | CT-0000 at C-2D1F1B | $240,000 |
| 3 | CONTACT | persona | CT-0000 at C-2D1F1B | $240,000 |
| 4 | DEAL | why_buys | Deal-2D1F1B | $240,000 |
| 5 | DEAL | why_buys | Deal-66D1FC | $99,000 |
| 6 | CONTACT | title | CT-0022 at C-C6FE92 | $72,000 |
| 7 | CONTACT | persona | CT-0022 at C-C6FE92 | $72,000 |
| 8 | DEAL | why_buys | Deal-C6FE92 | $72,000 |
| 9 | DEAL | why_buys | Deal-950043 | $70,000 |
| 10 | COMPANY | hq_country | C-D73B89 | $63,600 |
**Total pipeline at stake in top 10 fixes: $1,168,600**
## Lost Deal Classification Summary (90 deals, Aug-Jul 2026) ### Category Counts | Category | Count | % of Total | |----------|-------|-------------| | no decision | 29 | 32% | | competitor | 23 | 26% | | timing | 19 | 21% | | product gap | 8 | 9% | | champion left | 6 | 7% | | pricing | 4 | 4% | | other | 1 | 1% | **Arithmetic:** - 29 + 23 + 19 + 8 + 6 + 4 + 1 = **90 deals** ### Side Split | Side | Count | % of Total | |------|-------|-------------| | buyer | 46 | 51% | | unknown | 44 | 49% | **Arithmetic:** - 46 + 44 = **90 deals** - 46/90 = 51.1% ### Tag vs Free-Text Disagreements: 10 These are deals where the `closed_lost_tag` clearly disagrees with the structured `closed_lost_reason_text`: | Deal Alias | Issue | |------------|-------| | Deal-DB0AAC | Tag "Timing" but text = "putting this on pause" = no specific timeline | | Deal-831B7B | Tag "Timing" but text = "circle back then" = vague | | Deal-DDAB52 | Tag "Competitor" but text = "offers a lot more at same cost" = pricing argument | | Deal-BB78F3 | Tag "Timing" but text mentions specific survey action items | | Deal-1BCA50 | Tag "Competitor" but text = "mostly about budget" = pricing | | Deal-9F176A | Tag "Timing" but text = "pause" = no timeline given | | Deal-69CF3D | Tag "Timing" but text = "On Hold" = no timeline | | Deal-ECBF89 | Tag "Timing" but text = "On Hold for now" = no timeline | | Deal-5AD03E | Tag "Competitor" but text = "Wanted more defined budget access" = budget | | Deal-55867E | Tag "Timing" but text = "not be moving forward" = no decision | ### Two Patterns Most Worth Acting On **1. MIA/Unresponsive Deals (22 of 90 = 24%)** - These are classified as "no decision" where prospect went dark - Revenue at risk: ~$395K - **Action:** Implement earlier intervention protocols, automated multi-touch sequences, and SDR handoff before deals go cold **2. Competitor Losses with Specific Vendors (23 deals)** - Specific competitors named: ADP (PEO partnership), Awardco, HeyTaco, HiThrive, Kudos, Motivosity, Rippl, WorkTango, Paylocity - Revenue at risk: ~$406K - **Action:** Build competitive battle cards addressing: - ADP TotalSource partnershipdifferentiation - Budget-friendly pricing vs Rippl's "same cost but no exchange rate hassle" - Points currency digitization (multiple deals cited this)
{
"tier_counts": {
"LOCK": 2,
"ACTION": 7,
"BUILD": 11,
"REVIVE": 1,
"WATCH": 129,
"RISKY": 6
},
"tier_examples": {
"LOCK": ["Deal-C26D20", "Deal-403845"],
"ACTION": ["Deal-25F752", "Deal-D348E1", "Deal-944310"],
"BUILD": ["Deal-E53952", "Deal-5408B0", "Deal-9AAE5F"],
"REVIVE": ["Deal-2D1F1B"],
"WATCH": ["Deal-66D1FC", "Deal-C6FE92", "Deal-950043"],
"RISKY": ["Deal-547B2B", "Deal-B7EBD1", "Deal-A2B47C"]
},
"risky_deals": ["Deal-547B2B", "Deal-B7EBD1", "Deal-A2B47C", "Deal-2465CE", "Deal-584EE5", "Deal-FD9F4E"],
"lock_violations": 0,
"pipeline_shape": "156 deals total: 24 late-stage (DS4/DS5) vs 132 early-stage; forecast split: 11 COMMIT, 40 BEST_CASE, 105 PIPELINE. Top-tier LOCK/ACTION accounts for $85,459, with 6 RISKY deals flagged where COMMIT forecast lacks meeting evidence."
}
```json
[
{
"transcript_id": "TX-001",
"deal_alias": "Deal-CFE7F4",
"why_buys": [
"automating anniversary and birthday awards — our HR team of three cannot keep up with it manually"
],
"pain_points": [
"track everything in a spreadsheet, and people slip through the cracks",
"HR team cannot keep up manually with awards"
],
"stakeholders": ["VP People", "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": "high"
},
{
"transcript_id": "TX-002",
"deal_alias": "Deal-70BB30",
"why_buys": [
"tie recognition to retention for our hourly workforce"
],
"pain_points": [
"regretted turnover over 30%"
],
"stakeholders": ["Head of Total Rewards", "CFO"],
"budget_signal": "$25k pilot budget for this quarter",
"timeline_signal": "decision by end of September",
"competitor_mentioned": null,
"next_step": "pilot agreement to be routed to legal this week",
"objections": [
"Integration with Workday has to be rock solid — that's my one condition"
],
"confidence": "high"
},
{
"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": ["People Ops Manager"],
"budget_signal": null,
"timeline_signal": "no rush until Q1",
"competitor_mentioned": "Bucketlist",
"next_step": "schedule a call with CEO",
"objections": [],
"confidence": "medium"
},
{
"transcript_id": "TX-004",
"deal_alias": "Deal-180D02",
"why_buys": [
"consolidate three separate recognition tools into one",
"paying for three tools and none of them talk to our HRIS"
],
"pain_points": [
"paying for three tools that don't integrate with HRIS"
],
"stakeholders": ["VP People", "IT Security Lead"],
"budget_signal": "under $15k annually",
"timeline_signal": "procurement cycle runs six to eight weeks minimum",
"competitor_mentioned": null,
"next_step": null,
"objections": [
"security review took three months for last vendor"
],
"confidence": "medium"
},
{
"transcript_id": "TX-005",
"deal_alias": "Deal-F8767A",
"why_buys": [
"automate service milestones",
"give us analytics on recognition equity across departments",
"Our night-shift teams feel invisible — their engagement scores run 20 points lower"
],
"pain_points": [
"night-shift teams feel invisible",
"engagement scores run 20 points lower for night-shift"
],
"stakeholders": ["HR Director", "People Ops Coordinator"],
"budget_signal": "$12k approved under our engagement line",
"timeline_signal": "running before January all-hands",
"competitor_mentioned": "Nectar",
"next_step": "present to exec team on October 2",
"objections": [
"exec team is skeptical after a failed rollout two years ago"
],
"confidence": "high"
},
{
"transcript_id": "TX-006",
"deal_alias": "Deal-EE195F",
"why_buys": [
"cut the admin time on service awards",
"I personally spend five hours a month ordering and shipping plaques"
],
"pain_points": [
"five hours a month ordering and shipping plaques manually"
],
"stakeholders": ["HR Manager"],
"budget_signal": null,
"timeline_signal": "Q1 start (fiscal year resets in February)",
"competitor_mentioned": "internal build",
"next_step": "send one-page overview to forward to COO this week",
"objections": [
"COO usually prefers building things in-house"
],
"confidence": "medium"
}
]
```
## 3 Deals Closest to Signature ### 1. Deal-547B2B — $11,200 **Why close:** Slack says "signing page is out, VP People confirmed signing tomorrow" (Alex Franklin, 9/4). Redlines clean, ready to execute. **What left:** Signature only. Could close as early as 9/7. ### 2. Deal-403845 — $9,000 **Why close:** CRM shows DS5/COMMIT, close date 9/11. Slack confirms "order form is with their finance team" (Dana Mercer, 9/4). **What left:** Finance approval, then signature. ### 3. Deal-A2B47C — $6,360 **Why close:** DS5/COMMIT with close date 9/11. Slack notes "normal legal-review pace" but still warm. **What left:** Legal sign-off, then signature. **Note:** Deal-2465CE ($5,400) shows DS5/COMMIT in CRM but Slack says blocked — champion left, procurement froze. Not actually close despite CRM status.
## Product Gap Analysis | Deal | Prospect Quote | Classification | Amount | |------|----------------|-----------------|--------| | **TG-001 — Deal-EC3025** | "We need SCIM user provisioning — our security team will not approve any tool that requires manual account management." | **REAL GAP** — Product docs confirm: "SCIM user provisioning ... are NOT currently listed as supported capabilities." | — | | **TG-002 — 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** — Product docs confirm: "ADP Workforce Now integrations are NOT currently listed as supported capabilities." | — | | **TG-003 — 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** — Custom report builder exists but is Enterprise tier only. Not a product gap. | — | | **TG-004 — 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 supported on all plans. Gap is training, not product. | — | | **TG-005 — Deal-36C33F** | Rep: "we don't have a native mobile app for hourly workers yet, though it's on the roadmap." | **REAL GAP** — No mobile app in capabilities table. Rep admitted gap. | — | --- ### Summary: Real Product Gaps **1. Deal-EC3025** (amount unknown) - **Gap:** No SCIM user provisioning - **Prospect voice:** "We need SCIM user provisioning — our security team will not approve any tool that requires manual account management." **2. Deal-D0D6B5** (amount unknown) - **Gap:** No ADP Workforce Now integration - **Prospect voice:** "Our payroll runs on ADP Workforce Now and I don't see ADP anywhere in your integration list — that's a dealbreaker for us." **3. Deal-36C33F** (amount unknown) - **Gap:** No native mobile app - **Prospect voice:** (Rep self-identified: "we don't have a native mobile app for hourly workers yet, though it's on the roadmap.") --- *Note: Deal amounts were not provided in the transcript data.*
Here are the stale deals with no logged email, call, or meeting in the last 7 days (since 2026-08-29), computed from the engagements table's last_email/last_call/last_meeting fields. **Arithmetic verification examples:** - Deal-2D1F1B: max(last_email=2026-06-11, last_meeting=2026-06-16) = 2026-06-16 → 81 days since last contact - Deal-66D1FC: last_email=2026-08-20 → 16 days since last contact - Deal-44EA29: last_email=2026-08-26 → 10 days since last contact --- ### Bryce Harmon (13 stale deals, $626,243.00) | Deal Alias | Stage | Amount | Days Since Last Contact | |------------|-------|--------|--------------------------| | Deal-2D1F1B | DS1 | $240,000.00 | 81 | | Deal-66D1FC | DS1 | $99,000.00 | 16 | | Deal-950043 | DS1 | $70,000.00 | 19 | | Deal-B23205 | DS1 | $45,000.00 | 16 | | Deal-7BBDFA | DS3 | $37,440.00 | 46 | | Deal-332637 | DS2 | $36,000.00 | 9 | | Deal-1BEEBF | DS1 | $31,500.00 | 19 | | Deal-C5658B | DS1 | $23,400.00 | 16 | | Deal-40522D | DS3 | $21,000.00 | 19 | | Deal-F0EBBB | DS3 | $11,400.00 | 24 | | Deal-E25A09 | DS1 | $6,000.00 | 9 | | Deal-C9C286 | DS2 | $5,502.00 | 9 | | Deal-012CB1 | DS1 | $1.00 | 23 | ### Dana Mercer (14 stale deals, $261,645.00) | Deal Alias | Stage | Amount | Days Since Last Contact | |------------|-------|--------|--------------------------| | Deal-44EA29 | DS2 | $60,000.00 | 10 | | Deal-E51FB7 | DS2 | $43,875.00 | 12 | | Deal-B42F46 | DS1 | $27,000.00 | 19 | | Deal-BA3DDC | DS3 | $23,400.00 | 15 | | Deal-9DDE86 | DS2 | $20,000.00 | 15 | | Deal-215CCA | DS3 | $18,900.00 | 17 | | Deal-5EED42 | DS3 | $16,250.00 | 11 | | Deal-57887A | DS2 | $15,000.00 | 8 | | Deal-B7EBD1 | DS5 | $9,000.00 | 16 | | Deal-3974EB | DS4 | $9,000.00 | 8 | | Deal-F40F04 | DS2 | $8,100.00 | 15 | | Deal-87DDD1 | DS1 | $5,000.00 | 19 | | Deal-F336B6 | DS3 | $4,200.00 | 15 | | Deal-0660B4 | DS4 | $1,920.00 | 16 | ### Alex Franklin (19 stale deals, $109,536.00) | Deal Alias | Stage | Amount | Days Since Last Contact | |------------|-------|--------|--------------------------| | Deal-CC08D1 | DS1 | $24,000.00 | 16 | | Deal-E73427 | DS3 | $18,000.00 | 10 | | Deal-885F45 | DS2 | $9,300.00 | 12 | | Deal-C2FF3C | DS1 | $8,316.00 | 10 | | Deal-3EED2C | DS2 | $7,200.00 | N/A (no engagement) | | Deal-0D2F7A | DS3 | $5,100.00 | 12 | | Deal-6C60D4 | DS3 | $4,800.00 | 12 | | Deal-13FEBD | DS2 | $4,680.00 | 12 | | Deal-9D0060 | DS3 | $3,840.00 | 12 | | Deal-690476 | DS2 | $3,600.00 | 18 | | Deal-C6D97A | DS4 | $3,240.00 | 8 | | Deal-EE195F | DS3 | $3,120.00 | 8 | | Deal-278DEC | DS3 | $2,700.00 | 8 | | Deal-635B8E | DS3 | $2,600.00 | 18 | | Deal-6883F3 | DS1 | $2,400.00 | 16 | | Deal-4A13AD | DS3 | $2,160.00 | 26 | | Deal-F67D31 | DS2 | $1,800.00 | 8 | | Deal-5FDCE4 | DS3 | $1,600.00 | 12 | | Deal-BA571A | DS4 | $1,080.00 | 18 | ### Cole Ingram (18 stale deals, $252,905.03) | Deal Alias | Stage | Amount | Days Since Last Contact | |------------|-------|--------|--------------------------| | Deal-D04904 | DS2 | $58,529.25 | 11 | | Deal-B25F40 | DS3 | $40,000.00 | 8 | | Deal-813836 | DS2 | $32,175.00 | 11 | | Deal-1BA595 | DS2 | $31,750.00 | 11 | | Deal-CFE1E8 | DS3 | $18,000.00 | 11 | | Deal-CD47A6 | DS2 | $12,168.00 | 11 | | Deal-627646 | DS3 | $11,193.00 | 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 | $5,616.00 | 10 | | Deal-175395 | DS3 | $4,779.88 | 11 | | Deal-481E24 | DS3 | $4,140.00 | 10 | | Deal-C7F9BF | DS2 | $3,360.00 | 11 | | Deal-2F3A66 | DS3 | $3,334.80 | 11 | | Deal-342E96 | DS2 | $2,700.00 | 24 | | Deal-E568D5 | DS3 | $1,875.00 | 11 | | Deal-FD9F4E | DS5 | $1,330.00 | 10 | ### Elena Sinclair (1 stale deal, $2,100.00) | Deal Alias | Stage | Amount | Days Since Last Contact | |------------|-------|--------|--------------------------| | Deal-57FF13 | DS1 | $2,100.00 | N/A (no engagement) | --- **Summary per owner:** | Owner | Stale Deals | Total Stale Amount | |-------|-------------|-------------------| | Bryce Harmon | 13 | $626,243.00 | | Dana Mercer | 14 | $261,645.00 | | Alex Franklin | 19 | $109,536.00 | | Cole Ingram | 18 | $252,905.03 | | Elena Sinclair | 1 | $2,100.00 | | **GRAND TOTAL** | **65** | **$1,252,429.03** |
## Report: Activity Mix and Efficiency by Sales Rep **Snapshot Date:** 2026-09-05 **Window:** 2026-08-06 to 2026-09-05 (last 30 days) --- ### Per-Rep Activity Totals (Last 30 Days) | Rep | Emails | Calls | Meetings | **Total** | Email % | Call % | Meeting % | |-----|--------|-------|----------|-----------|---------|--------|-----------| | **Alex Franklin** | 307 | 36 | 41 | **384** | 79.9% | 9.4% | 10.7% | | **Bryce Harmon** | 162 | 0 | 43 | **205** | 79.0% | 0.0% | 21.0% | | **Dana Mercer** | 84 | 18 | 11 | **113** | 74.3% | 15.9% | 9.7% | | **Cole Ingram** | 96 | 14 | 1 | **111** | 86.5% | 12.6% | 0.9% | | **Farid Osman** | 38 | 0 | 34 | **72** | 52.8% | 0.0% | 47.2% | *Note: Elena Sinclair excluded (only 1 deal, still in DS1 with no DS2 entry in window).* --- ### DS2 Entries (Last 30 Days) and Efficiency | Rep | DS2 Entries | Total Activities | Activities per DS2 Entry | |-----|-------------|------------------|-------------------------| | **Alex Franklin** | 18 | 384 | **21.3** | | **Bryce Harmon** | 4 | 205 | 51.2 | | **Cole Ingram** | 2 | 111 | 55.5 | | **Farid Osman** | 1 | 72 | 72.0 | | **Dana Mercer** | 1 | 113 | 113.0 | **Ranked by efficiency (lowest = most efficient):** 1. Alex Franklin — 21.3 activities/DS2 2. Bryce Harmon — 51.2 activities/DS2 3. Cole Ingram — 55.5 activities/DS2 4. Farid Osman — 72.0 activities/DS2 5. Dana Mercer — 113.0 activities/DS2 --- ### Summary - **Most Efficient Rep:** Alex Franklin (21.3 activities per DS2 entry) - **Highest-Volume Rep:** Alex Franklin (384 total activities) - **Same Person:** Yes — Alex Franklin is both the most efficient and highest-volume rep. *Do not attribute cause. This data shows correlation, not causation.*
**QTD SCORECARD - Alex Franklin (As of 2026-09-05)** --- **1. BOOKINGS VS QUOTA** - QTD Bookings: $150,000 - Quota: $200,000 - Attainment: 75.0% **2. NEW VS EXPANSION SPLIT** - New: $113,500 (5 deals) - Expansion: $36,500 (3 deals) - New %: 75.7% **3. ACTIVE PIPELINE BY STAGE** | Stage | Deals | Amount | |-------|-------|--------| | DS1 | 20 | $284,621 | | DS2 | 28 | $353,760 | | DS3 | 67 | $552,705 | | DS4 | 5 | $23,574 | | DS5 | 5 | $45,730 | | **TOTAL** | **125** | **$1,260,390** | **4. ROLLING 90-DAY DS2-TO-WON RATE** - DS2 entries (last 90 days): 111 deals - DS2-to-won: 8 deals - Conversion rate: 7.2% **5. WINS AND LOSSES** - Wins: 8 - Losses: 27 - Win/Loss ratio: 0.30 - Top loss reason: "Lost- Timing (1 year or more)" — 13 deals (48% of all losses) **6. ACTIVITY VOLUME (LAST 30 DAYS)** - Emails: 807 - Calls: 112 - Meetings: 128 - Notes: 50 - **Total: 1,097 activities** --- ## THREE COACHING OBSERVATIONS **1. Timing losses are killing your quarter.** 13 of 27 losses (48%) cite "Timing (1 year or more)" as the reason. This signals weak ICP fit at the top of funnel or deals being pursued without confirming buyer intent timeline. Coach: Implement a "3-month commit" check at discovery — don't advance deals where the buyer can't confirm a close within the quarter. **2. DS2 conversion is severely underperforming.** At 7.2%, you're converting roughly 1-in-14 deals that reach DS2. Given $1.26M in pipeline, even a modest improvement to 12% would yield ~$90K additional bookings. Coach: The 111 DS2 entries in 90 days is strong volume, but quality is lacking. Review DS2 qualification criteria with the AE. **3. You have a pipeline coverage problem, not an activity problem.** $1.26M pipeline against $200K quota (6.3x coverage) yet only 75% attainment. Activity is high (1,097 touches), but the weighted forecast is missing. Coach: Focus on advancing DS3→DS4 deals where the commit is real, not adding more DS1 volume. Your DS4+DS5 pipeline is only $69K — that's <1 month of quota.
The files provided (deal_contacts.csv and unengaged_contacts.csv) do not contain deal **amount** or **stage** data. I can only analyze threading based on the contact data provided. --- ## Flagged Deals: Single-Threaded or Under-Threaded | Deal Alias | Company | Active Contacts | Personas Present | Personas Missing | Flag | Unengaged on File | |------------|---------|-----------------|-------------------|-------------------|------|-------------------| | Deal-EC3025 | C-FDD0C7 | 1 | champion | HR admin, IT security, economic buyer, finance | **SINGLE-THREADED** | CT-6827DB: Chief People Officer (economic buyer) | | Deal-92D97D | C-E23238 | 1 | HR admin | IT security, champion, economic buyer, finance | **SINGLE-THREADED** | none on file | | Deal-36C33F | C-077A0E | 1 | IT security | HR admin, champion, economic buyer, finance | **SINGLE-THREADED** | CT-1DB73E: Chief People Officer (economic buyer) | | Deal-FCBE5B | C-737030 | 1 | champion | HR admin, IT security, economic buyer, finance | **SINGLE-THREADED** | none on file | | Deal-F9A08A | C-0D15DF | 1 | champion | HR admin, IT security, economic buyer, finance | **SINGLE-THREADED** | CT-697541: Chief People Officer (economic buyer) | | Deal-50D386 | C-EB10E4 | 2 | champion, HR admin | IT security, economic buyer, finance | **UNDER-THREADED** | CT-A1C4B3: Chief People Officer (economic buyer) | | Deal-5BFE3B | C-535D36 | 2 | champion | HR admin, IT security, economic buyer, finance | **UNDER-THREADED** | none on file | | Deal-885F45 | C-5E8EFB | 2 | champion, economic buyer | HR admin, IT security, finance | **UNDER-THREADED** | CT-B3F25D: IT Security Lead (IT security) | | Deal-5408B0 | C-2AE3AA | 2 | champion, HR admin | IT security, economic buyer, finance | **UNDER-THREADED** | CT-07FA76: Chief People Officer (economic buyer) | | Deal-D0D6B5 | C-32918E | 3 | champion | HR admin, IT security, economic buyer, finance | **UNDER-THREADED** | CT-1FA4DB: Chief People Officer (economic buyer) | | Deal-C6D97A | C-5A8FC2 | 3 | champion | HR admin, IT security, economic buyer, finance | **UNDER-THREADED** | none on file | --- ### Data Missing The following were requested but not present in the provided files: - **Deal amount** — not in deal_contacts.csv or unengaged_contacts.csv - **Deal stage** — not in deal_contacts.csv or unengaged_contacts.csv - **Most valuable persona to add given the stage** — cannot determine without stage data To complete the analysis with amount, stage, and stage-based persona recommendations, please provide a file containing deal amounts and stages.
## Analysis: Alex Franklin — Last 10 Calls
### Lead (first 5 minutes)
- **8 of 10 calls**: "Quick one to kick off: a 400-person retailer we work with cut regretted turnover 18% in two quarters after automating milestone awards..."
- **1 call**: "I put together a short agenda — security review first, then pricing." (TT-004)
- **1 call**: "You asked for straight pricing last time, so let's start there." (TT-009)
### Three most common objections and responses
**Objection 1 — Budget locked** ("budget is locked until next fiscal year — I can't add a new line item right now")
- Response: "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."
**Objection 2 — Revisit next quarter** ("This is good, but can we revisit it next quarter? Open enrollment starts in October and we're underwater.")
- Response: "Makes sense. What if we scope a 90-day pilot with one department so you have internal data before next quarter's planning?"
**Objection 3 — Spreadsheets work** ("We already do recognition with a spreadsheet and quarterly gift cards — why would we change?")
- Response: "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%** of calls ended with a concrete next step confirmed.
Calls without a locked next step: TT-004, TT-007, TT-010
### Competitors raised by prospects
- **Awardco** — "We're also in late talks with Awardco — their rewards catalog looks bigger than yours."
- **Kudos** — "How are you different from Kudos? Our CEO used them at her last company."
- **Workhuman** — "And unlike Workhuman, our pricing includes the full rewards catalog with no extra margin." (spoken by Alex, not raised by prospect)
### Coaching notes
1. **One call broke pattern** (TT-009) — Alex led with pricing instead of the case study and skipped the budget objection entirely. That call still closed with a next step, suggesting the tailored opener worked. Consider testing the case study vs. direct pricing more deliberately.
2. **Three calls stalled on committee/inaction** — TT-004, TT-007, and TT-010 produced no next step. In each case the rep either accepted "I'll leave it with you" (TT-004) or mirrored the prospect's deferral language. A stronger close such as "What would you need to bring to the committee?" could surface blockers earlier and recover the deal.
## Q3 2026 FORECAST **Quarter:** 2026-07-01 to 2026-09-30 **Weighting:** 100% COMMIT + 35% BEST_CASE. PIPELINE = 0. --- ### Category Totals (Inside Q3 Only) | Category | Count | Total Amount | |----------|-------|--------------| | COMMIT | 7 | $44,729.00 | | BEST_CASE | 24 | $203,565.00 | | PIPELINE | 23 | $201,637.40 (counts as $0) | --- ### Weighted Forecast Calculation ``` COMMIT (100%): $44,729.00 BEST_CASE (35%): $203,565.00 × 0.35 = $71,247.75 ───────────────────────────────────────────────── WEIGHTED FORECAST: $115,976.75 ``` --- ### Excluded Deals (Outside Q3) - **Count:** 32 deals - **Total amount:** $227,575.00 *(These have close dates from 2026-10-01 to 2026-10-15)* --- ### Top 5 BEST_CASE Deals by Amount (Inside Q3) | Rank | Deal Alias | Amount | Close Date | |------|------------|--------|------------| | 1 | Deal-2D7423 | $38,935.00 | 2026-09-30 | | 2 | Deal-25F752 | $24,000.00 | 2026-09-25 | | 3 | Deal-E53952 | $19,656.00 | 2026-09-30 | | 4 | Deal-5EED42 | $16,250.00 | 2026-09-30 | | 5 | Deal-FA32A0 | $11,116.00 | 2026-09-25 | --- ## Data Quality Four data quality problems make this forecast unreliable if run unattended: (1) the `owner` field is empty on most deals, making it impossible to assign credit or identify whose pipeline this is; (2) the `why_buys_chars` field is mostly zero with no buy signal details, so BEST_CASE and COMMIT deals cannot be validated against actual customer intent; (3) one amount contains a decimal (`Deal-42326B` at $2,480.4) while all others are integers, indicating inconsistent data entry; and (4) the extract was pulled on 2026-09-05 but contains deals closing through 2026-10-15, meaning the data was not a point-in-time snapshot but rather includes future-dated pipeline that would shift categories between runs as close dates approach.
⚠ Stream stalled mid tool-call (execute_code); the action was not executed. Ask me to retry if you want to continue.## Activation Hypothesis Test Results ### 2x2 Matrix: Cohort Size & 24-Month Retention Rate | Signal Combination | Cohort Size | Active at 24mo | Retention Rate | |---|---|---|---| | **Both signals** (m1_users >= 5 AND m1_redemptions >= 1) | 47 | 31 | **66.0%** | | **Givers-only** (m1_users >= 5, m1_redemptions = 0) | 49 | 23 | **46.9%** | | **Redemption-only** (m1_users < 5, m1_redemptions >= 1) | 29 | 9 | **31.0%** | | **Neither** (m1_users < 5, m1_redemptions = 0) | 95 | 38 | **40.0%** | ### Exclusions **None.** All 220 companies fit into one of the four categories. ### Single Signal with Largest Retention Lift **GIVERS (m1_users >= 5)** — lift of **+6.9 percentage points** vs the baseline "neither" rate (40.0% → 46.9%). The redemption signal alone shows negative lift (-9.0 pp). ### What This Does and Does Not Prove **DOES PROVE:** - Strong correlation between dual-signal activation and retention: companies with both 5+ unique givers AND 1+ redemptions in month 1 retain at 66.0%, 26 points above the baseline. - The givers signal is the stronger single predictor: 46.9% (givers-only) vs 40.0% (neither) vs 31.0% (redemption-only). - Synergistic effect exists: both (66%) > givers-only (47%), meaning redemption adds value when the company already has givers. **DOES NOT PROVE:** - **Causation.** This is observational. Companies with both signals may have been more likely to succeed regardless of early engagement. - **Redemption alone is not predictive.** Actually shows negative correlation (-9.0 pp vs baseline) — small companies with early redemptions churn more, not less. - **No control for confounders.** Company size, industry, product tier, geography, and sales source are not controlled. - **Small cell sizes.** Redemption-only (n=29) is insufficient for strong inference. - **Cannot prove intervention works.** Driving more givers/redemptions in low-engagement companies may not cause retention improvement.
## ARR Reconciliation Report — 2026-09-05 ### TOTALS | Source | ARR | |--------|-----| | Billing (active MRR × 12) | $604,739.28 | | Company (HubSpot) | $603,581.76 | | **Variance** | **-$1,157.52** | --- ### VARIANCE DECOMPOSITION (sums to -$1,157.52) | Bucket | Amount | Explanation | |--------|--------|-------------| | **Status Mismatch - Missing in Company** | -$28,449.24 | In billing but no CRM record | | **Status Mismatch - Missing in Billing** | +$29,655.72 | In CRM but no active billing | | **Rounding (≤$20 diff)** | +$36.00 | Small numeric differences | | **Other (>$20 diff)** | -$2,400.00 | Same account, large variance | --- ### MISMATCHED ACCOUNTS **Status Mismatch — Missing in Company:** | Company Alias | Billing ARR | Suggested Owner | |--------------|------------|-----------------| | C-21629AA4 | $28,449.24 | CRM data entry error — verify if this ID exists in HubSpot | **Status Mismatch — Missing in Billing (all 3 are cancelled in Chargebee):** | Company Alias | Company ARR | Suggested Owner | |--------------|------------|-----------------| | C-0C8323BF | $4,905.24 | Verify subscription status — this is cancelled in billing | | C-0DC4FB8C | $8,253.24 | Verify subscription status — this is cancelled in billing | | C-0D5BBE3A | $16,497.24 | Verify subscription status — no subscription record | **Other (>$20 variance):** | Company Alias | Billing ARR | Company ARR | Diff | Suggested Owner | |--------------|------------|-------------|------|-----------------| | C-0F7269D7 | $26,796.00 | $24,396.00 | -$2,400.00 | Review contract terms / multi-year discount | --- ### BUSINESS RULE VIOLATIONS Term ≠ 12 months but `cf_agreement_end_date` is NOT populated: | Subscription ID | Company Alias | Term | End Date | |-----------------|---------------|------|----------| | SUB-0002 | C-1794A52C | 24 months | *(MISSING)* | | SUB-0019 | C-22170CA1 | 36 months | *(MISSING)* | --- ### ARITHMETIC VERIFICATION ``` Variance = -$1,157.52 Bucket Sum = +$29,655.72 - $28,449.24 + $36.00 - $2,400.00 = -$1,157.52 ✓ ```
**Four Core KVMs: 2026-08 vs 2026-07** | KVM | Aug | Jul | Abs Change | Rel Change | Dir | |-----|-----|-----|------------|------------|-----| | Giving Rate | 0.6027 | 0.6023 | +0.0004 | +0.07% | ↑ | | Redemptions per User | 1.7302 | 1.7300 | +0.0002 | +0.01% | ↑ | | 1:1 Engagement | 0.4472 | 0.4469 | +0.0003 | +0.06% | ↑ | | Pulse Engagement | 0.5086 | 0.6006 | -0.0920 | **-15.31%** | ↓ | **Largest relative move:** Pulse Engagement at **-15.31%** (downward). The segment driving this is **enterprise** — pulse engagement dropped from 0.5500 in July to 0.2743 in August, a -50.13% decline for enterprise accounts. SMB and mid-market showed minimal movement (-0.22% and +0.21%, respectively). The data shows all companies in the enterprise segment experienced this drop, suggesting a structural shift specific to enterprise users rather than a company-specific anomaly.
**Last completed month: 2026-08 (August 2026)** --- **Redemption Count:** 48 **Spend:** $3,536.00 **Unique Redeemers:** 46 **Redemptions per Redeemer:** 1.04 --- **Provider Mix (% of spend):** | Provider | Spend | % of Total | |----------|-------|------------| | Tremendous | $1,145.00 | 32.4% | | custom | $1,057.00 | 29.9% | | Snappy | $834.00 | 23.6% | | TangoCard | $500.00 | 14.1% | | **Total** | **$3,536.00** | **100.0%** | --- **Top 5 Countries by Redemptions:** 1. US: 31 2. CA: 7 3. GB: 2 4. SG: 2 5. AU: 2
## Churn-Save Eligibility Analysis **Snapshot date:** 2026-09-05 **120-day cutoff:** 2027-01-03 (2026-09-05 + 120 days) --- ### ELIGIBLE ACCOUNTS (All 3 rules met: R1 + R2 + R3) | Account | Health Score | Eligible Amount | Renewal Date | At Stake | Play | Signal | |---------|-------------|-----------------|--------------|----------|------|--------| | C-0F6C0F34 | 51 | $49,707 | 2026-10-03 | $49,707 | Executive Touch | champion_active = false | | C-0B827671 | 56 | $25,365 | 2026-11-14 | $25,365 | Usage Revival | usage_trend_3m = declining | | C-0B360C78 | 57 | $35,748 | 2026-10-28 | $35,748 | Commercial Concession | champion_active = true, usage_trend_3m = growing (no urgent signal) | | C-0B0F1BAB | 38 | $5,494 | 2026-09-23 | $5,494 | Executive Touch | champion_active = false | | C-0CA21961 | 58 | $16,829 | 2026-12-28 | $16,829 | Commercial Concession | usage_trend_3m = flat, champion_active = true | | C-0E9C27D1 | 39 | $41,235 | 2026-09-24 | $41,235 | Commercial Concession | usage_trend_3m = flat, champion_active = true | | C-0D3278C7 | 54 | $17,602 | 2026-11-12 | $17,602 | Usage Revival | usage_trend_3m = declining | | C-0F876796 | 47 | $19,958 | 2027-02-06 | $19,958 | Executive Touch | champion_active = false | **Total at stake: $211,938** --- ### AT-RISK ACCOUNTS THAT DO NOT QUALIFY | Account | Health Score | Eligible Amount | Renewal Date | Why Disqualified | |---------|-------------|-----------------|--------------|------------------| | C-0BC71BDD | 55 | **$0.00** | 2026-10-27 | R2 fails: churn_save_eligible_amount = 0 | | C-0F6694C3 | 43 | **$0.00** | 2027-03-21 | R2 fails: churn_save_eligible_amount = 0 | | C-0BE96399 | 54 | **$0.00** | 2026-10-29 | R2 fails: churn_save_eligible_amount = 0 | | C-0FCCD2DF | 43 | **$0.00** | 2027-04-23 | R2 fails: churn_save_eligible_amount = 0 | | C-10A56B0F | 54 | **$0.00** | 2026-12-12 | R2 fails: churn_save_eligible_amount = 0 | | C-0BA71F12 | 52 | $6,824 | **2027-04-11** | R3 fails: renewal is 248 days after snapshot (beyond 120-day window) | | C-0B843542 | 63 | $0.00 | 2027-02-01 | R1 fails: health_score = 63 (≥60); R2 fails: amount = 0 | | C-14264ABD | 87 | $0.00 | 2027-05-13 | R1 fails: health_score = 87 (≥60); R2 fails: amount = 0 | | C-0B2895EF | 73 | $0.00 | 2027-05-05 | R1 fails: health_score = 73 (≥60); R2 fails: amount = 0 | | C-0EE1203E | 88 | $0.00 | 2027-04-15 | R1 fails: health_score = 88 (≥60); R2 fails: amount = 0 | | C-0FC7A215 | 62 | $0.00 | 2027-05-28 | R1 fails: health_score = 62 (≥60); R2 fails: amount = 0 | | C-0D035262 | 85 | $0.00 | 2026-10-20 | R1 fails: health_score = 85 (≥60); R2 fails: amount = 0 | | C-0D6CC8E3 | 77 | $0.00 | 2027-04-05 | R1 fails: health_score = 77 (≥60); R2 fails: amount = 0 | | C-0B2213A9 | 69 | $0.00 | 2026-12-03 | R1 fails: health_score = 69 (≥60); R2 fails: amount = 0 | | C-0D0B047C | 70 | $0.00 | 2027-05-08 | R1 fails: health_score = 70 (≥60); R2 fails: amount = 0 | | C-21FEBCBB | 65 | $0.00 | 2027-06-30 | R1 fails: health_score = 65 (≥60); R2 fails: amount = 0 | | C-172EEFBC | 75 | $0.00 | 2026-11-24 | R1 fails: health_score = 75 (≥60); R2 fails: amount = 0 | | C-0C3848D2 | 73 | $0.00 | 2027-03-05 | R1 fails: health_score = 73 (≥60); R2 fails: amount = 0 | | C-0D890324 | 81 | $0.00 | 2027-04-10 | R1 fails: health_score = 81 (≥60); R2 fails: amount = 0 | | C-0AAA9434 | 75 | $0.00 | 2026-10-14 | R1 fails: health_score = 75 (≥60); R2 fails: amount = 0 | | C-8C2E8F00 | 73 | $0.00 | 2027-05-09 | R1 fails: health_score = 73 (≥60); R2 fails: amount = 0 | --- ### PLAY ASSIGNMENT LOGIC - **Usage Revival**: usage_trend_3m = "declining" → account needs usage recovery to stabilize - **Executive Touch**: champion_active = "false" → account lacks internal sponsor, needs executive engagement - **Commercial Concession**: usage_trend_3m = "flat" or "growing" AND champion_active = "true" → no usage/champion issues, but commercial intervention needed to secure renewal
## Expansion Kit: C-0DDFC9A7 ### Seat Coverage - Licensed seats: **150** - Headcount: **400** - Coverage ratio: **37.5%** (150 ÷ 400) ### Usage Health (Two Lines) 1. **Utilization rate**: 126 users / 150 licensed seats = **84%** of license in use (August 2026) 2. **Growth trend**: Users grew from 88 (March) to 126 (August) — **+43% over 6 months**, averaging ~6-8 new users/month ### Headroom - **Seats**: 150 licensed − 126 active = **24 seats available** - **ARR expansion potential**: $9,000 ÷ 150 seats = **$60/seat/year** → 24 × $60 = **$1,440 ARR** at current rate ### Who Replied & Buying Authority - **Replier**: Maria S., People Operations Coordinator - **Can they buy?**: **No** — explicitly stated "I'm not the right person for purchasing decisions" ### Right Buyer - **Dana R.**, VP People — owns budget and seat expansion decisions; "been asking about our usage numbers lately" (per Maria's reply) --- ### Reply Email (138 words) > Hi Maria, > > Thanks so much for the quick reply — really glad to hear the team is getting value from Bonusly. And no worries at all, I appreciate you clarifying the routing. > > I'd love to connect with Dana. Given that she's been asking about usage numbers, I think there's a strong story to tell: we've grown from 88 monthly users to 126 over the last six months, now at 84% license utilization with room to grow. That kind of organic uptake often makes the case for expansion pretty straightforward. > > If you're able to make an intro, that would be fantastic. Either way, thank you for being such a great champion internally! > > Best, > Cole
## CSM Mid-Onboarding Call Prep: C-0D284E42 ### ✅ What's Complete (Data Confirmed) | Milestone | Data Field | Value | |-----------|------------|-------| | Integration connected (Slack) | `integration_slack` | 2026-08-12 | | Allowance set | `allowance_set` | 2026-08-13 | | Admins added | `admins_added` | 2 | | First recognition given | `first_recognition_at` | 2026-08-15 14:22 | ### ❌ What's NOT Complete (Data Missing) | Milestone | Data Field | Status | |-----------|------------|--------| | Integration HRIS | `integration_hris` | **EMPTY** — not connected | | First redemption | `first_redemption_at` | **EMPTY** — not completed | --- ### Early Engagement Signals From `onboarding_usage.csv`, active givers grew from **3 → 15** over 25 days: ``` Aug 11: 3 → Aug 18: 5 → Aug 25: 9 → Sept 1: 13 Aug 12: 3 → Aug 19: 7 → Aug 26: 11 → Sept 2: 13 Aug 13: 4 → Aug 20: 6 → Aug 27: 10 → Sept 3: 15 Aug 14: 4 → Aug 21: 9 → Aug 28: 10 → Sept 4: 15 Aug 15: 5 → Aug 22: 8 → Aug 29: 11 Aug 16: 4 → Aug 23: 9 → Aug 30: 13 Aug 17: 7 → Aug 24: 9 → Aug 31: 11 ``` - **Trend**: +12 active givers (400% growth) - **Peak**: 15 on Sept 3-4 - **Pattern**: Consistent upward trajectory with minor dips; strong sustained engagement --- ### Three Things to Cover on the Call 1. **HRIS Integration** — Still shows as not connected. Ask: What's blocking? Need help with setup? 2. **First Redemption** — No redemption recorded yet. Ask: Are rewards resonating? Any friction in the redemption flow? 3. **Engagement Celebration + Expansion** — Highlight the 15 active givers. Discuss: What's driving adoption? Any department or use case to double down on?
# 90-Day Renewal Risk Brief ## Date Source Decisions & Disagreements Flagged | Account | CZ Date | CB Date | Disagree? | Decision | Rationale | |---------|---------|---------|-----------|----------|-----------| | C-0B7D2C30 | 2026-09-10 | 2026-09-15 | Yes (5 days) | **CB** | Trust CB; multi-year (36mo) known wrong in CZ | | C-0BCDB8C2 | 2027-09-18 | 2026-09-18 | **YES — 1 year off** | **CB** | CZ shows 2027; CB shows 2026. CZ multi-year bug confirmed. Use CB: 2026-09-18 | | C-0D2AB865 | 2026-09-10 | 2026-09-22 | Yes (12 days) | **CB** | Trust CB; multi-year (24mo) known wrong in CZ | | C-0BBE3E60 | 2027-09-26 | 2026-09-26 | **YES — 1 year off** | **CB** | CZ shows 2027; CB shows 2026. CZ multi-year bug confirmed. Use CB: 2026-09-26 | | C-0F5D2323 | 2026-09-10 | 2026-09-29 | Yes (19 days) | **CB** | Trust CB; multi-year (24mo) known wrong in CZ | | C-0EC6999D | 2026-10-03 | 2026-10-03 | No | **CZ** | Single-year; dates agree | | C-0B20DB64 | 2026-10-07 | 2026-10-07 | No | **CZ** | Single-year; dates agree | | C-0BBC4E7A | 2026-10-10 | 2026-10-10 | No | **CZ** | Single-year; dates agree | | C-0FD551AB | 2026-10-14 | 2026-10-14 | No | **CZ** | Single-year; dates agree | | C-0F9F8F13 | 2026-10-18 | 2026-10-18 | No | **CZ** | Single-year; dates agree | | C-0BC34584 | 2026-10-22 | 2026-10-22 | No | **CZ** | Single-year; dates agree | | C-0B7A7546 | 2026-10-25 | 2026-10-25 | No | **CZ** | Single-year; dates agree | | C-0B369871 | 2026-10-29 | 2026-10-29 | No | **CZ** | Single-year; dates agree | | C-0B144C78 | 2026-11-02 | 2026-11-02 | No | **CZ** | Single-year; dates agree | | C-0FC4DBB8 | 2026-11-05 | 2026-11-05 | No | **CZ** | Single-year; dates agree | | C-0D5BBE3A | 2026-11-09 | 2026-11-09 | No | **CZ** | Single-year; dates agree | | C-0FB9D5AF | 2026-11-13 | 2026-11-13 | No | **CZ** | Single-year; dates agree | | C-0B344485 | 2026-11-16 | 2026-11-16 | No | **CZ** | Single-year; dates agree | | C-0CB2C1B4 | 2026-11-20 | 2026-11-20 | No | **CZ** | Single-year; dates agree | | C-22170CA1 | 2026-11-24 | 2026-11-24 | No | **CZ** | Single-year; dates agree | **Disagreements flagged: 5** — All involve multi-year contracts where CZ erroneously adds 1 year to renewal date. --- ## Renewal Detail by Account (Sorted by Renewal Date) ### September 2026 **C-0B7D2C30** | CSM: Dana Mercer | ARR: $65,901 | Date: **2026-09-15** - Seat Utilization: 274/476 = **57.6%** - 3-Month Usage Trend: May-Jul avg 99.3 → Jun-Aug avg 91.7 (**-7.7%**, declining) - Risk: **MEDIUM** — Seat utilization moderate but usage trending down 8% over 3 months. **C-0BCDB8C2** | CSM: Cole Ingram | ARR: $54,427 | Date: **2026-09-18** - Seat Utilization: 232/424 = **54.7%** - 3-Month Usage Trend: Mar-May avg 146.3 → Jun-Aug avg 118.3 (**-19.1%**, declining sharply) - Risk: **HIGH** — Usage dropped 19% quarter-over-quarter with only moderate seat utilization. **C-0D2AB865** | CSM: Elena Sinclair | ARR: $38,022 | Date: **2026-09-22** - Seat Utilization: 250/407 = **61.4%** - 3-Month Usage Trend: Mar-May avg 144.3 → Jun-Aug avg 126.3 (**-12.5%**, declining) - Risk: **MEDIUM** — Usage down 12.5% QoQ though seat utilization sits just above 60%. **C-0BBE3E60** | CSM: Dana Mercer | ARR: $30,993 | Date: **2026-09-26** - Seat Utilization: 74/114 = **64.9%** - 3-Month Usage Trend: Mar-May avg 44.3 → Jun-Aug avg 38.3 (**-13.5%**, declining) - Risk: **HIGH** — Usage declined 13.5% QoQ despite decent seat utilization. **C-0F5D2323** | CSM: Cole Ingram | ARR: $90,647 | Date: **2026-09-29** - Seat Utilization: 111/390 = **28.5%** - 3-Month Usage Trend: Mar-May avg 19.0 → Jun-Aug avg 19.7 (flat) - Risk: **HIGH** — Critical: only 28.5% seat utilization indicates severe under-adoption. --- ### October 2026 **C-0EC6999D** | CSM: Elena Sinclair | ARR: $79,419 | Date: **2026-10-03** - Seat Utilization: 31/112 = **27.7%** - 3-Month Usage Trend: Mar-May avg 14.7 → Jun-Aug avg 16.0 (up 9%) - Risk: **HIGH** — Only 27.7% seat utilization despite slight usage uptick. **C-0B20DB64** | CSM: Dana Mercer | ARR: $21,770 | Date: **2026-10-07** - Seat Utilization: 214/378 = **56.6%** - 3-Month Usage Trend: Mar-May avg 295.3 → Jun-Aug avg 298.7 (+1.2%, stable) - Risk: **LOW** — Usage stable, seat utilization acceptable. **C-0BBC4E7A** | CSM: Cole Ingram | ARR: $56,374 | Date: **2026-10-10** - Seat Utilization: 228/337 = **67.7%** - 3-Month Usage Trend: Mar-May avg 142.0 → Jun-Aug avg 140.7 (**-0.9%**, flat) - Risk: **LOW** — High seat utilization, usage essentially flat. **C-0FD551AB** | CSM: Elena Sinclair | ARR: $48,815 | Date: **2026-10-14** - Seat Utilization: 210/376 = **55.9%** - 3-Month Usage Trend: Mar-May avg 125.3 → Jun-Aug avg 123.7 (**-1.3%**, flat) - Risk: **LOW** — Stable usage with moderate seat utilization. **C-0F9F8F13** | CSM: Dana Mercer | ARR: $46,230 | Date: **2026-10-18** - Seat Utilization: 199/352 = **56.5%** - 3-Month Usage Trend: Mar-May avg 183.7 → Jun-Aug avg 184.0 (flat) - Risk: **LOW** — Usage flat, seat utilization moderate. **C-0BC34584** | CSM: Cole Ingram | ARR: $16,740 | Date: **2026-10-22** - Seat Utilization: 327/494 = **66.2%** - 3-Month Usage Trend: Mar-May avg 103.7 → Jun-Aug avg 104.3 (+0.6%, stable) - Risk: **LOW** — Good seat utilization, usage stable. **C-0B7A7546** | CSM: Elena Sinclair | ARR: $35,062 | Date: **2026-10-25** - Seat Utilization: 182/205 = **88.8%** - 3-Month Usage Trend: Mar-May avg 61.3 → Jun-Aug avg 64.0 (+4.4%, growing) - Risk: **LOW** — High seat utilization, usage growing. **C-0B369871** | CSM: Dana Mercer | ARR: $85,128 | Date: **2026-10-29** - Seat Utilization: 317/422 = **75.1%** - 3-Month Usage Trend: Mar-May avg 316.0 → Jun-Aug avg 325.0 (+2.8%, growing) - Risk: **LOW** — Strong seat utilization, usage trending up. --- ### November 2026 **C-0B144C78** | CSM: Cole Ingram | ARR: $30,899 | Date: **2026-11-02** - Seat Utilization: 169/224 = **75.4%** - 3-Month Usage Trend: Mar-May avg 99.7 → Jun-Aug avg 102.0 (+2.3%, stable) - Risk: **LOW** — High seat utilization, usage stable. **C-0FC4DBB8** | CSM: Elena Sinclair | ARR: $94,732 | Date: **2026-11-05** - Seat Utilization: 356/464 = **76.7%** - 3-Month Usage Trend: Mar-May avg 183.3 → Jun-Aug avg 188.3 (+2.7%, growing) - Risk: **LOW** — Strong seat utilization, usage growing. **C-0D5BBE3A** | CSM: Dana Mercer | ARR: $39,740 | Date: **2026-11-09** - Seat Utilization: 85/102 = **83.3%** - 3-Month Usage Trend: Mar-May avg 86.3 → Jun-Aug avg 88.3 (+2.3%, growing) - Risk: **LOW** — Very high seat utilization, usage growing. **C-0FB9D5AF** | CSM: Cole Ingram | ARR: $63,158 | Date: **2026-11-13** - Seat Utilization: 144/199 = **72.4%** - 3-Month Usage Trend: Mar-May avg 166.3 → Jun-Aug avg 172.3 (+3.6%, growing) - Risk: **LOW** — Good seat utilization, usage trending up. **C-0B344485** | CSM: Elena Sinclair | ARR: $64,384 | Date: **2026-11-16** - Seat Utilization: 224/287 = **78.0%** - 3-Month Usage Trend: Mar-May avg 234.0 → Jun-Aug avg 240.7 (+2.9%, growing) - Risk: **LOW** — Strong utilization, usage growing. **C-0CB2C1B4** | CSM: Dana Mercer | ARR: $40,628 | Date: **2026-11-20** - Seat Utilization: 386/473 = **81.6%** - 3-Month Usage Trend: Mar-May avg 49.0 → Jun-Aug avg 47.7 (**-2.7%**, slight decline) - Risk: **MEDIUM** — High seat utilization but usage dipped 2.7% QoQ. **C-22170CA1** | CSM: Cole Ingram | ARR: $45,646 | Date: **2026-11-24** - Seat Utilization: 251/294 = **85.4%** - 3-Month Usage Trend: Mar-May avg 142.0 → Jun-Aug avg 145.7 (+2.6%, growing) - Risk: **LOW** — Excellent utilization, usage growing. --- ## Summary | Risk Level | Count | Total ARR | |------------|-------|-----------| | **HIGH** | 4 | $255,486 | | **MEDIUM** | 2 | $104,529 | | **LOW** | 14 | $746,406 | | **TOTAL** | 20 | **$1,106,421** | ### ARR at Risk (HIGH + MEDIUM): **$360,015** at risk (32.5% of total renewing ARR) --- ### CSM Workload in Renewal Window | CSM | Accounts | Total ARR | |-----|----------|-----------| | Dana Mercer | 6 | $245,160 | | Cole Ingram | 7 | $357,932 | | Elena Sinclair | 7 | $503,329 | **Highest-risk accounts by CSM:** - Cole: C-0F5D2323 ($90,647, HIGH), C-0BCDB8C2 ($54,427, HIGH) - Dana: C-0BBE3E60 ($30,993, HIGH), C-0CB2C1B4 ($40,628, MEDIUM) - Elena: C-0EC6999D ($79,419, HIGH)
## Q2 2026 Support Ticket Theme Analysis **80 total tickets | $1,598,900 total ARR affected** --- ### BROAD PATTERNS (ranked by ARR exposure) **1. HRIS Provisioning Failures** - Count: 12 (15%) - ARR: $456,000 - Distinct accounts: 3 - Ticket IDs: IC-460059, IC-460055, IC-460062 - Recommendation: Investigate HRIS sync job for null/empty field handling; add bulk provisioning retry logic **2. Checkout/Redemption Failures** - Count: 18 (22.5%) - ARR: $177,300 - Distinct accounts: 7 - Ticket IDs: IC-460025, IC-460035, IC-460031 - Recommendation: Audit checkout timeout handling and gift card email dispatch for race conditions **3. Points Not Posting** - Count: 20 (25%) - ARR: $70,200 - Distinct accounts: 9 - Ticket IDs: IC-460004, IC-460016, IC-460001 - Recommendation: Add point ledger transaction rollback on recognition delivery failure **4. Slack Integration Failures** - Count: 14 (17.5%) - ARR: $63,400 - Distinct accounts: 4 - Ticket IDs: IC-460041, IC-460047, IC-460045 - Recommendation: Persist Slack OAuth tokens and re-auth state to prevent toggle resets --- ### SINGLE-ACCOUNT NOISE (excluded from ranking) **5. Billing Seat Count Errors** - Count: 16 (20%) - ARR: $832,000 - Distinct accounts: 1 (C-0E9C27D1 only — 16 of 16 tickets) - Ticket IDs: IC-460071, IC-460069, IC-460078 - Recommendation: Escalate to C-0E9C27D1 dedicated support; this is account-specific, not a product-wide issue --- ### Summary | Theme | Count | Share | ARR | Accounts | |-------|-------|-------|-----|----------| | HRIS Provisioning | 12 | 15% | $456,000 | 3 | | Checkout/Redemption | 18 | 22.5% | $177,300 | 7 | | Points Not Posting | 20 | 25% | $70,200 | 9 | | Slack Integration | 14 | 17.5% | $63,400 | 4 | | Billing (C-0E9C27D1 only) | 16 | 20% | $832,000 | 1 |
## Top 3 Similar Customers with Case Studies | Rank | Company | Matching Fields | Non-Matching | |------|---------|-----------------|---------------| | **1** | C-64171065 | **Industry, Size Band, Use Case** | Region (NA-East vs NA-West) | | **2** | C-A13C193D | **Industry, Size Band, Region** | Use Case (retention vs employee_recognition) | | **3** | C-11C31562 | **Size Band, Use Case, Region** | Industry (Manufacturing vs Technology) | ### Reasoning The prospect (C-82AF3719) is **Technology / Mid-Market / employee_recognition / NA-West**. **Scoring methodology**: Each matching field gets 1 point. | Company | Industry | Size Band | Use Case | Region | Total | |---------|----------|-----------|----------|--------|-------| | C-64171065 | ✓ | ✓ | ✓ | ✗ | **3** | | C-A13C193D | ✓ | ✓ | ✗ | ✓ | **3** | | C-11C31562 | ✗ | ✓ | ✓ | ✓ | **3** | | C-9D69D147 | ✗ | ✓ | ✗ | ✓ | 2 | | C-CD4829A7 | ✓ | ✓ | ✗ | ✗ | 2 | The three-way tie at 3 points was broken by weighting the most common/prospective valuable fields: 1. **C-64171065**: Same technology industry + same mid-market segment + same use case — strongest alignment 2. **C-A13C193D**: Same technology industry + same region (critical for NA-West expansion) 3. **C-11C31562**: Same region + same use case + same size band — strongest operational match Eight customers total have case studies; five were evaluated above.
## CHANNEL PERFORMANCE REPORT — TRAILING 6 MONTHS (Mar–Aug 2026) --- ### PAID CHANNELS | Channel | Spend | SQMs | SQOs | Cost/SQM | Cost/SQO | SQM→SQO Rate | Pipeline | Pipeline/$ | |---------|-------|------|------|----------|----------|--------------|----------|------------| | 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** | N/A | $0 | $0.00 | | webinars | $9,000 | 12 | 5 | $750 | $1,800 | 41.7% | $60,000 | $6.67 | ### ORGANIC CHANNELS | Channel | Volume | SQMs | SQOs | SQO Rate | Pipeline | |---------|--------|------|------|----------|----------| | organic_search | 30 | 30 | 10 | 33.3% | $90,000 | | referral | 15 | 15 | 6 | 40.0% | $48,000 | --- ### DATE FLAGS — SQO precedes SQM - **linkedin_ads**: CT-000044 (SQM: 2026-07-23, SQO: 2026-07-18), CT-000041 (SQM: 2026-06-14, SQO: 2026-06-09) These 2 records are data errors — SQO cannot occur before first touch. --- ### REALLOCATION RECOMMENDATION **Efficiency ranking (Pipeline per dollar):** 1. **paid_search**: $20.00/$ 2. **webinars**: $6.67/$ 3. **linkedin_ads**: $4.00/$ 4. **paid_social**: $0.00/$ (undefined — zero SQMs from spend) **Action**: Shift budget away from paid_social ($18,000) toward paid_search and webinars, which show 3x–5x better pipeline efficiency. - paid_search generates **$20 pipeline per dollar** — the clear winner - webinars delivers **$6.67** — solid secondary ROI - linkedin_ads is underperforming at **$4.00** but has higher ASPs ($12K vs $40K); worth testing angle optimization before cutting - paid_social: $18K spent, zero attributed SQMs — **pause immediately** --- ### CONFIDENCE ASSESSMENT | Channel | SQMs | SQOs | Confidence | |---------|------|------|------------| | paid_search | 40 | 18 | HIGH — n > 30 | | linkedin_ads | 25 | 8 | MODERATE — n ≈ 25 | | webinars | 12 | 5 | LOW-MODERATE — n < 15 | | paid_social | 0 | 0 | NONE — no data | | organic_search | 30 | 10 | HIGH | | referral | 15 | 6 | MODERATE | Sample sizes: paid_search and organic_search are statistically meaningful (n≥30). LinkedIn and webinars are suggestive but need more volume. Paid_social has **no attribution data** — cannot evaluate.
# Battlecard: Rivally (Updated September 2026) ## One-Line Positioning Points-based employee recognition platform targeting mid-market and EU enterprise companies, with recent expansion into engagement surveys. (S02, S12, S06) --- ## Pricing **Current Price: $7 per user/month** (annual billing required) | Date | Source | Price | |------|--------|-------| | 2026-01-20 | Pricing page (S03) | $5/user/mo | | 2026-04-01 | Pricing page (S08) | $5/user/mo | | 2026-08-12 | Pricing page (S17) | $7/user/mo | | 2026-08-14 | Call notes (S18) | $7/user/mo list, 15% discount for 3-year | **Conflict noted:** Pricing increased from $5 to $7 between April and August 2026. One deal (S13, June 2026) quoted $6.50/user/mo for a 500-seat prospect—indicating discounting started before the official price change. --- ## Where They Win 1. **EU data residency requirements** — Prospect C mentioned Rivally pitched this capability (S05). Dublin office opened July 2026; EU data residency generally available (S15). 2. **Distributed EU teams** — Multi-language support praised by EU enterprise reviewer (S12). 3. **Fast implementation** — Mid-market reviewer: setup under a week, Slack integration worked out of the box (S04). 4. **Recognition feed engagement** — Reviewers consistently praise the social recognition feed (S02, S16). 5. **Support responsiveness** — G2 review praises sub-4-hour response time (S22). --- ## Where We Win 1. **Analytics depth** — 800-seat prospect chose Bonusly over Rivally citing analytics depth (S25). Rivally reviews cite "basic" and "limited" analytics (S02, S07). 2. **SCIM provisioning** — Enterprise reviewer notes manual user management is painful; lacks SCIM (S10). 3. **Admin tooling** — Reviewer cites admin tooling lags peers; lacks bulk recognition editing (S16, S24). 4. **Migration/offboarding** — Migration off Rivally hard; CSV-only exports (S20). 5. **Rewards catalog (EMEA)** — TrustRadius review: EMEA rewards catalog thinner than US (S14). --- ## Objections and Responses | Objection | Response | |-----------|----------| | "Their analytics is basic" | S02, S07, S25 — Confirm. Our analytics depth won an 800-seat deal. | | "No SCIM provisioning" | S10 — True. Manual user management required; painful at scale. | | "EU data residency needed" | S05, S15 — They offer it now (Dublin office, GA July 2026). Competitive differentiator eroded. | | "Migration was hard" | S20 — True, CSV-only exports. Our export capabilities are superior. | | "Thinner EMEA rewards" | S14 — True. US catalog stronger than EMEA. | --- ## Recent Changes | Date | Change | Source | |------|--------|--------| | 2026-08-12 | Pricing increased to $7/user/mo | S17 | | 2026-08-20 | Microsoft Teams app v2 in public preview | S19 | | 2026-09-01 | Rivally Pulse add-on exits beta, now paid add-on | S23 | | 2026-07-19 | Dublin office opened; EU data residency GA | S15 | | 2026-05-09 | Hired ex-Workday VP EMEA | S11 | | 2026-03-05 | Launched Rivally Pulse (survey add-on) | S06 | --- ## Our 12-Month Win/Loss Record Against Rivally **Period: September 2025 – August 2026** | Month | Wins | Losses | |-------|------|--------| | 2025-09 | 1 | 1 | | 2025-10 | 2 | 0 | | 2025-11 | 1 | 1 | | 2025-12 | 1 | 1 | | 2026-01 | 2 | 0 | | 2026-02 | 2 | 0 | | 2026-03 | 1 | 1 | | 2026-04 | 0 | 2 | | 2026-05 | 0 | 2 | | 2026-06 | 1 | 0 | | 2026-07 | 1 | 0 | | 2026-08 | 1 | 0 | | **TOTAL** | **13** | **7** | **Win Rate: 65%** (13/20 deals) --- ## Items from Old Card — Status | Old Card Claim | Status | |---------------|--------| | Positioning: points-based recognition for mid-market | **VERIFIED** — Consistent across reviews (S02) | | Pricing: starts at $5 per user/month (as of 2026-01) | **VERIFIED BUT STALE** — Now $7 (S17) | | Rivally lacks a Slack integration | **UNVERIFIED** — S04 says Slack integration worked "out of the box" | | Rivally was acquired by WorkHuman in 2025 | **UNVERIFIED** — No source in snippets | | Strong in EU enterprise with multi-language support | **VERIFIED** — S12 confirms |
## Sequence Analysis | Sequence | Step | Sent | Open Rate | Reply Rate | Meeting Rate | Weakest Step | |----------|------|------|-----------|------------|-------------|--------------| | **New Logo Nurture** | 1 | 500 | 42.0% | 8.40% | 2.40% | — | | | 2 | 458 | 34.9% | 6.55% | 1.97% | — | | | 3 | 428 | 28.0% | 4.21% | 1.40% | Step 3 (reply ↓) | | **Expansion Nurture** | 1 | 300 | 43.3% | 7.33% | 1.67% | — | | | 2 | 300 | 113.3%* | 8.33% | 1.33% | Step 2 (tracking error) | | | 3 | 275 | 34.5% | 4.36% | 1.09% | Step 3 (reply ↓) | | **Cold Outbound - HR Leaders** | 1 | 600 | 40.0% | **0.83%** | 0.00% | **Step 1** | | | 2 | 595 | 29.4% | **0.34%** | 0.00% | — | | | 3 | 590 | 22.0% | **0.17%** | 0.00% | — | | **Cold Outbound - People Ops** | 1 | 400 | 37.5% | 3.50% | 0.75% | — | | | 2 | 386 | 28.5% | 2.33% | 0.52% | — | | | 3 | 377 | 21.2% | **1.59%** | 0.27% | **Step 3** | *Tracking error: 340 opened > 300 sent ### Tracking Errors - **Expansion Nurture Step 2**: 340 opened exceeds 300 sent — likely duplicate opens counted or CRM sync error ### Audience Overlap - **Cold Outbound - HR Leaders ∩ Cold Outbound - People Ops**: 21 contacts (e.g., CT-001285, CT-001311, CT-001130) - **New Logo Nurture ∩ Expansion Nurture**: 2 contacts (CT-000301, CT-000624) ### Failure Modes (<2% Reply) - **Cold Outbound - HR Leaders** all 3 steps: 0.83% → 0.34% → 0.17% — message mismatch to HR audience, no personalization - **Cold Outbound - People Ops** Step 3: 1.59% — sequence fatigue, diminishing relevance ### One Change Per Weak Sequence + Priority 1. **Cold Outbound - HR Leaders (PRIORITY 1)**: Revise Step 1 with HR-specific value prop + personalization trigger — current 0.83% reply is catastrophic 2. **Cold Outbound - People Ops**: Add a different hook at Step 3 or shorten to 2 steps — Step 3 under 2% 3. **Expansion Nurture**: Fix tracking before Step 2 (duplicate open issue), then review Step 3 content
## Weekly Marketing Goals Update — Q3-2026 (as of Day 66) | Metric | QTD Actual | Target | Delta | Pace | |---|---|---|---|---| | SQMs | 230 | 300 | -70 | **Ahead** (230 vs 215 expected) | | SQOs | 84 | 120 | -36 | Behind (84 vs 86 expected) | | DS2s | 40 | 75 | -35 | Behind (40 vs 54 expected) | | Closed-Lost MIA Rate | 0.20 (5/25) | 0.10 | +0.10 | Behind (20% vs 10% target) | | Same-Quarter Closes | 10 | 20 | -10 | Behind (10 vs 14 expected) | | Active Pipeline | $3.00M | $4.00M | -$1.00M | **Ahead** ($3.00M vs $2.87M expected) | **What moved this week:** SQMs remain the strongest performer, now exceeding pace by 15 units — likely driven by the trade show leads from early August converting to meetings. DS2s and same-quarter closes are the biggest gaps; the DS2 shortfall (-35) suggests bottleneck in demo-to-close progression. Closed-lost MIA rate ticked up (5 out of 25 closed-lost = 20% vs 10% target), indicating reps are abandoning deals without sufficient discovery. Pipeline coverage is healthy at 75% ($3M/$4M) but needs $1M more to hit target by quarter-end.
Q3 weighted forecast: **$115,977** (7 COMMIT deals at $44,729 + 35% of $203,565 BEST_CASE). Caveat: 85 of 86 deals missing owner, 71 missing why-buy including all COMMIT, and 32 deals closing in October—close dates appear pushed rather than re-qualified. This forecast looks precise but isn't.
Subject: Following up on the pricing we sent Hi Alex, I wanted to check in since we haven't heard back since sending over the pricing for the 150-seat plan back on August 5th. I know things get busy — just wanted to see if you had any questions or if there's anything else I can clarify? Happy to jump on a quick call or answer via email. Let me know how you'd like to proceed. Best, Amani
# Weekly GTM Digest **Marketing** kicked off the week strong with 46 SQMs, coming in at 88.5% against the 52 target. The webinar channel delivered 18 of those—good for 39.1% of total SQMs—showing solid momentum in that channel. Paid search kept acquisition efficient at $150 cost per SQM, holding steady from prior weeks. **Sales** converted 14 SQOs and set 9 DS2 meetings, building pipeline at a steady clip. The team created $310,000 in new pipeline and closed 3 deals in the same quarter this week. **Customer Success** saved 2 renewals and pushed team NPS up to 61, reflecting strong customer relationships. The team is tracking 3 open red-flag accounts heading into next week—close monitoring in progress. **PLG** had a standout week with 412 new signups and 31% activation, showing healthy product traction. Thirty-eight companies hit the aha moment milestone of giving 10 recognitions—proof that users are finding value and spreading the appreciation culture.
# Partner Digest — August 24 to September 04, 2026 **Partner-Sourced Pipeline: 5 deals | $550,000** --- ## Active Partners **Apex Rewards Co** - Status: Active - Sourced Pipeline: 2 deals | $275,000 - Deals: Deal-DDAAF2 ($180,000), Deal-2CF33E ($95,000) - Activity: Co-webinar locked for 09-15; 2 sourced opps in DS1 (confirmed UTM Source = Partner) **HRCloud Partners** - Status: Active - Sourced Pipeline: 1 deal | $140,000 - Deals: Deal-F1CDA5 ($140,000) - Activity: Integration referral advanced to DS2; 1 sourced opp this period **CultureBridge** - Status: Active - Sourced Pipeline: 2 deals | $135,000 - Deals: Deal-096E1D ($60,000), Deal-067213 ($75,000) - Activity: Lunch-and-learn produced 2 sourced opps (early stage) **WorkWell Group** - Status: Active - Sourced Pipeline: 0 deals | $0 - Activity: Planning call booked for 09-09 to restart joint playbook for Q4 --- ## Quiet Partners - **Recogniq** — No activity this period - **KudosWave** — No activity this period - **PeopleFirst Advisors** — No activity this period - **TotalPerk** — No activity this period
# Vendor Response to Security Questionnaire **Q1: Is customer data encrypted at rest? If so, how?** Yes. All customer data is encrypted at rest using AES-256. [P1] **Q2: Is data encrypted in transit?** Yes. Data in transit is encrypted with TLS 1.2 or higher. [P1] **Q3: Do you hold a SOC 2 report, and can we obtain a copy?** Yes. Bonusly maintains a SOC 2 Type II report, renewed annually. The report is available to prospects under NDA. [P2] **Q4: How long is customer data retained after contract termination?** Customer data is retained for the duration of the contract plus 90 days, after which it is deleted from production systems. [P3] **Q5: Where is your subprocessor list published and how are changes notified?** The subprocessor list is maintained at trust.bonusly.com. Customers receive 30 days notice before a new subprocessor is added. [P4] **Q6: Do you support SAML single sign-on?** Yes. SAML 2.0 single sign-on is available on the Enterprise plan (along with SCIM user provisioning). [P5] **Q7: What is your production backup schedule and retention?** Production databases are backed up daily. Backups are encrypted and retained for 35 days. [P6] **Q8: Do you hold an ISO 27001 certification?** Unanswerable from provided excerpts. This information would be in a certification or compliance directory document. **Q9: What is your contractual uptime SLA percentage?** Unanswerable from provided excerpts. This information would be in the master services agreement or SLA terms document. **Q10: Will you sign a HIPAA Business Associate Agreement?** Unanswerable from provided excerpts. This would be addressed in contract terms or a dedicated HIPAA compliance document.
# Skill Set Reconciliation Report ## Finding 1: Duplicate ALWAYS-Trigger Phrases **Severity:** CRITICAL **Action Type:** REVIEW **Issue:** `email-drafter` and `comms-drafter` have identical ALWAYS trigger phrases: - "write me an email" - "draft a follow-up" - "help me reply" - "what should I say" - "bump email" - "contract nudge" Both skills handle email drafting. `comms-drafter` explicitly covers "outbound prospecting, follow-ups, post-demo recaps" — overlap is direct. `email-drafter` is more specific to AEs/SDRs/CSMs, while `comms-drafter` is company-wide. **Proposal:** Designate one as primary. Recommendation: keep `email-drafter` for revenue team emails, expand `comms-drafter` scope to non-email communications (Slack, Intercom) or consolidate under one skill with role-based routing. --- ## Finding 2: No Circular Delegation Chains **Severity:** N/A **Action Type:** N/A No circular chains detected. Delegations flow outward: - `pipeline-intelligence-report` → `closed-lost-analysis` - `deal-strategy-coach` → `prospect-research-multithreading` (external) - `comms-drafter`/`email-drafter` → `deal-strategy-coach` (reference only, not delegation) --- ## Finding 3: No Dangling Delegation Targets **Severity:** INFO **Action Type:** TRIM_DESC No dangling targets. Skills reference external systems (`bonusly-data-questions`, `bonusly-product-questions`, `prospect-research-multithreading`) that exist outside this manifest scope. --- ## Finding 4: Version Conflicts **Severity:** WARNING **Action Type:** UPDATE_BODY | Skill | Manifest Declares | Body States | Conflict | |-------|------------------|-------------|----------| | `analysis-validator` | (none) | Frontmatter: v3.6, Trail: v3.2 | Version in validation trail (line ~918) says "analysis-validator v3.2" but frontmatter and changelog say v3.6 | | `pipeline-intelligence-report` | (none) | Description: "v6 · May 2026" | Version in description but not frontmatter | **Proposal:** The skill body should survive — update manifest to include version field. For `analysis-validator`, change validation trail reference from v3.2 to v3.6 to match current state. --- ## Finding 5: Manifest Descriptions Exceeding 1,024 Characters **Severity:** INFO **Action Type:** TRIM_DESC Count: **0** — None exceed 1,024 characters. | Skill | Characters | |-------|------------| | pipeline-intelligence-report | 1006 | | signalforge-claim-compressor | 1006 | | partner-digest | 1004 | All are below the 1,024 threshold. --- ## Finding 6: Hardcoded Page IDs, Dates, and Person Names **Severity:** CRITICAL **Action Type:** UPDATE_BODY **Hardcoded dates:** - `analysis-validator`: "April 26, 2026" (Created), "May 9, 2026" (Last Updated), "May 4, 2026" (CALL_SPOTLIGHT_BRIEF removal) - `closed-lost-analysis`: "May 2026" (AI field sample), "May 4, 2026" (roster) - `deal-strategy-coach`: "April 2026" (Playbook), "May 4, 2026" (roster) - `model-selection`: "2026-05-19" (last_checked) - `next-to-close`: "May 2026", "May 4, 2026" - `pipeline-intelligence-report`: "May 2026" - `stale-pipeline-report`: "2026-06-10" (v1.0) - `sales-forecast`: "April 27, 2026", "Q2 2026" **Hardcoded person names:** - `analysis-validator`: "Manish", "Amani" (escalation contacts) - `closed-lost-analysis`: Full AE roster with names (Bryce Harmon, Hugo Lindqvist, Dana Mercer, etc.) - `deal-strategy-coach`: Full GTM roster with names - `pipeline-intelligence-report`: Full AE roster with names + "Alaina Loori" **Hardcoded HubSpot IDs:** - Multiple skills embed owner IDs: 83155923 (Dana Mercer), 83155924 (Cole Ingram), 84342457 (Alex Franklin), 1520255671 (Gavin Porter), etc. **Hardcoded page IDs:** - `partner-digest`: Folder ID `2286616609`, Space ID `1958248479` - `pipeline-intelligence-report`: Confluence references with page IDs - `signalforge-feedback`: Page ID `2295136266` **Proposal:** Replace hardcoded dates with dynamic queries or "current quarter" language. Move person rosters to external reference tables. Keep HubSpot IDs only where necessary for join logic, not for display. --- ## Finding 7: Manifest Drift **Severity:** INFO **Action Type:** REVIEW | Direction | Status | |-----------|--------| | Files with no manifest row | **NONE** — all 14 files have corresponding rows | | Manifest rows with no file | **NONE** — all 14 rows have corresponding files | **Drift:** None detected. 14 files ↔ 14 rows — exact match. --- ## Summary Table | Finding | Severity | Count | Action Type | |---------|----------|-------|-------------| | Duplicate trigger phrases | CRITICAL | 1 pair | REVIEW | | Circular delegation | — | 0 | N/A | | Dangling delegation | — | 0 | — | | Version conflicts | WARNING | 2 skills | UPDATE_BODY | | Long descriptions (>1K chars) | INFO | 0 | — | | Hardcoded IDs/dates/names | CRITICAL | 9 skills | UPDATE_BODY | | Manifest drift | INFO | 0 | — |
# Runbook — #incident-2026-08-29-reward-queue ## Step 1: Acknowledge alert and assume incident command - **Who:** Bryce Harmon - **Action:** PagerDuty alert acknowledged, IC taken - **Verification:** Alert acknowledged in PagerDuty - **Rollback:** N/A — administrative action - **Trace:** M01 --- ## Step 2: Check current queue depth - **Who:** Farid Osman - **Action:** `bundle exec rake sidekiq:queue_depth` - **Verification:** Command returns pending job count; reported 48,213 - **Rollback:** N/A — read-only diagnostic - **Trace:** M02 --- ## Step 3: Inspect dead set for failed jobs - **Who:** Farid Osman - **Action:** Examined dead set in Sidekiq - **Verification:** Found 112 jobs, all Redis::TimeoutError timestamped ~13:58 - **Rollback:** N/A — read-only diagnostic - **Trace:** M03 --- ## Step 4: Pause auto-recognition enqueue to stop the bleed - **Who:** Farid Osman - **Action:** `bin/rails runner 'FeatureFlag.disable(:auto_recognition_enqueue)'` - **Verification:** Check that new jobs stop appearing in queue (manual observation) - **Rollback:** `bin/rails runner 'FeatureFlag.enable(:auto_recognition_enqueue)'` - **Trace:** M04 --- ## Step 5: Clear the dead set - **Who:** Elena Sinclair - **Action:** Cleared dead set via Rails console - **Verification:** Dead set confirmed empty - **Rollback:** N/A — jobs already failed; no recovery path in thread - **Trace:** M05 > **Note:** Command used for clearing not specified in thread — needs confirmation --- ## Step 6: Scale up reward-worker deployment - **Who:** Bryce Harmon - **Action:** `kubectl scale deployment/reward-worker --replicas=6` - **Verification:** `kubectl get deployment reward-worker` shows 6 replicas; queue depth decreases - **Rollback:** `kubectl scale deployment/reward-worker --replicas=3` - **Trace:** M06 --- ## Step 7: Verify queue depth declining - **Who:** Farid Osman - **Action:** `bundle exec rake sidekiq:queue_depth` - **Verification:** Reported 9,400 and falling ~1,200/min - **Rollback:** N/A — read-only diagnostic - **Trace:** M07 --- ## Step 8: Confirm queue drained and error rate normalized - **Who:** Cole Ingram - **Action:** `bundle exec rake sidekiq:queue_depth` + check Datadog - **Verification:** Queue at 0; Datadog error rate at baseline - **Rollback:** N/A — read-only diagnostic - **Trace:** M08 --- ## Step 9: Re-enable auto-recognition enqueue - **Who:** Bryce Harmon - **Action:** `bin/rails runner 'FeatureFlag.enable(:auto_recognition_enqueue)'` - **Verification:** Observed 40 new jobs processed cleanly in 3 minutes - **Rollback:** `bin/rails runner 'FeatureFlag.disable(:auto_recognition_enqueue)'` - **Trace:** M09 --- ## Step 10: Scale workers back to normal - **Who:** Bryce Harmon - **Action:** `kubectl scale deployment/reward-worker --replicas=3` - **Verification:** Queue remains at 0; stable - **Rollback:** `kubectl scale deployment/reward-worker --replicas=6` - **Trace:** M10
## Failure Sequence Analysis ### First Error (Root Cause) - **Timestamp:** 2026-09-03T14:01:12Z - **Service:** reward-service - **Message:** `Redis::TimeoutError: Connection to Redis at redis-primary:6379 timed out after 5s` ### Cascade (in order) | Timestamp | Service | Message | |-----------|---------|---------| | 14:01:20Z | reward-service | ERROR retry exhausted for RewardGiveJob | | 14:01:30Z | reward-service | ERROR retry exhausted for RewardGiveJob | | 14:01:40Z | reward-service | ERROR retry exhausted for RewardGiveJob | | 14:01:40Z | sidekiq | ERROR RewardGiveJob failed: Redis::TimeoutError; retrying in 60s | | 14:02:28Z | sidekiq | ERROR RewardGiveJob failed: Redis::TimeoutError; retrying | | 14:02:30Z | sidekiq | WARN Queue reward depth above 10,000 | | 14:03:05Z | api-gateway | ERROR 502 upstream timeout calling reward-service /gives | | 14:03:30Z | web-app | ERROR Give form submission failed: upstream 502 from api-gateway | | 14:03:31Z+ | sidekiq | ERROR RewardGiveJob failed (repeated through 14:06:47Z) | ### Service and Job Involved - **Service:** reward-service (primary), sidekiq (job processor), api-gateway (upstream) - **Job:** RewardGiveJob (class: `RewardGiveJob`) ### Datadog Query to Confirm First Error ``` service:reward-service level:error "Redis::TimeoutError" "redis-primary:6379" ``` Time range: 2026-09-03T14:01:00Z to 2026-09-03T14:01:30Z ### What the Logs Do NOT Show - **Root cause of the Redis timeout** — no preceding Redis logs showing memory pressure, connection exhaustion, or network issues - **Recovery trigger** — no logs explaining how/why Redis connection was restored at 14:22:10Z - **Alert notifications** — no PagerDuty, Slack, or email alerts in the slice - **Peak queue depth** — the WARN at 14:02:30Z says "above 10,000" but doesn't give the exact peak - **Impact scope** — no logs showing how many Give form submissions failed, or customer-facing impact duration - **Resolution actions** — no operator intervention logs, no Redis config changes, no restarts
# Feature Flag Summary ## Flags WITH code references | Flag | State | What it controls | Segment/Targeting | Companies | |------|-------|------------------|-------------------|------------------| | recognition_streaks_v2 | ON | Triggers StreakTracker.record(give) to track recognition streaks | segment:beta_companies | 42 | | points_budget_guardrails | ON | Runs BudgetService.enforce!(giver, points) to enforce point budget limits | all_companies | 220 | | slack_dm_nudges | ON | Sends Slack DM nudges via SlackDm.send_nudge(user) | segment:region_na | 87 | | redeem_flow_redesign | OFF | Renders RedeemV2Component (on) vs RedeemV1Component (off) | targeted_list | 12 | | analytics_dashboard_v3 | ON | Loads AnalyticsV3 dashboard | segment:tier_three | 65 | | ms_teams_app_v2 | OFF | Installs TeamsAppV2 via TeamsAppV2.install(company) | targeted_list | 9 | ## Flags with NO code reference | Flag | State | Segment/Targeting | Companies | Issue | |------|-------|-------------------|-----------|-------| | legacy_give_modal | OFF | segment:legacy_plan | 14 | No code found in flag_code.md | | survey_boosters_q3 | ON | segment:legacy_plan | 7 | No code found in flag_code.md | | paused_offboard_cleanup | OFF | (none) | 0 | No code found in flag_code.md | ## Flags with zero targets - **paused_offboard_cleanup**: company_count = 0. Targeting rules column is empty, meaning no companies are assigned to this flag.
## NDA Triage ### NDA-1 — [PARTY A] / Bonusly **Triage: GREEN** Reasoning: Standard mutual NDA with reasonable terms (2-year term, 3-year survival). Contains all standard carve-outs (publicly available, prior knowledge, third-party receipt, independent development, legal disclosure). Delaware law is favorable. No non-solicits, non-competes, or concerning restrictions. --- ### NDA-2 — [PARTY B] / Bonusly **Triage: YELLOW** Reasoning: Contains a non-solicitation clause restricting hiring of employees "with whom it came into contact under this Agreement" for 18 months post-termination. The clause is somewhat narrow (only applies to employees contacted during the NDA), but introduces a post-term restriction that warrants counsel review. All other terms are standard. *Key clause:* "During the term of this Agreement and for eighteen (18) months thereafter, neither party shall solicit for employment or hire any employee of the other party with whom it came into contact under this Agreement." --- ### NDA-3 — [PARTY C] / Bonusly **Triage: RED** Reasoning: Multiple high-risk issues requiring full legal review: 1. **One-way confidentiality**: Only protects [PARTY C]. Bonusly receives no confidentiality protection — it's purely the disloser. 2. **Non-compete is overly broad**: "Recipient shall not, directly or indirectly, engage in or provide services to any business that competes with Discloser's business" for 3 years — no geographic limitation, no customer/prospect carve-out, no reasonableness test. 3. **No carve-outs stated**: Missing exceptions for publicly available information, prior knowledge, independent development, or legally required disclosure. This creates ambiguous exposure. 4. **Irish jurisdiction**: Foreign governing law adds complexity and potential enforcement challenges. *Key clause:* "For a period of three (3) years following the Effective Date, Recipient shall not, directly or indirectly, engage in or provide services to any business that competes with Discloser's business."