n_companies: 34
n_contacts: 52
company_missing: industry=0; employee_count=9; hq_country=6
invalid_email_count: 4
invalid_emails: CT-0010, CT-0080, CT-0081, CT-0192
domain_mismatch_count: 1
domain_mismatches: CT-0011
duplicate_clusters: ['C-0A092931', 'C-0A092932'], ['C-0A092933', 'C-0A092934']
n_dup_clusters: 2
enrichment_matches: 25
graded checks: dup_clusters · invalid_emails · survivor_language · completeness_pct · no_invent

Model's actual answer

show the model's full answer

# CRM Audit Report
## Data Sources Used
- `companies.csv` (34 total records)
- `contacts.csv` (52 total records)
- `zoominfo_enrichment.csv` (domain-standardized enrichment data)
> **Critical Note**: `deals.csv` was not provided in the audit dataset. Without deal owner, stage, amount, close date, and why-buys data, pipeline amount calculations and top pipeline-risk fixes are impossible.

---

## 1. Field Completion Percentages
### Companies.csv (34 records)
| Field               | Completed Records | Total Records | Completion % |
|---------------------|------------------|---------------|--------------|
| company_alias       | 34               | 34            | 100.00%      |
| domain              | 34               | 34            | 100.00%      |
| industry            | 33               | 34            | 97.06%       |
| employee_count      | 26               | 34            | 76.47%       |
| hq_country          | 28               | 34            | 82.35%       |

### Contacts.csv (52 records)
| Field               | Completed Records | Total Records | Completion % |
|---------------------|------------------|---------------|--------------|
| contact_key         | 52               | 52            | 100.00%      |
| company_alias       | 52               | 52            | 100.00%      |
| email               | 48               | 52            | 92.31%       |
| title               | 37               | 52            | 71.15%       |
| persona             | 35               | 52            | 67.31%       |
| domain              | 52               | 52            | 100.00%      |

---

## 2. Duplicate Company Clusters
Shared domain clusters, with recommended survivor (standardized/most complete record):
1.  **Cluster: `acme-corp.com`**
    - Records: `C-0A092931` (industry: Technology, employee_count:500, hq_country:US), `C-0A092932` (industry: tech, employee_count:510, hq_country:USA)
    - Survivor: `C-0A092932` (standardized country format: `United States` vs `US`)
2.  **Cluster: `globex.io`**
    - Records: `C-0A092933` (industry: SaaS, employee_count:200, hq_country:US), `C-0A092934` (industry: Technology, employee_count:200, hq_country:US)
    - Survivor: `C-0A092933` (specific industry label: `SaaS` vs generic `Technology`)

---

## 3. Invalid Emails & Domain Mismatches
### Invalid Emails (4 total, malformed/missing domain):
| Contact Key | Company Alias | Email Address       |
|-------------|---------------|---------------------|
| CT-0010     | C-66D1FC      | `user0@`              |
| CT-0080     | C-92D97D      | `user0@`              |
| CT-0081     | C-92D97D      | `user1@`              |
| CT-0192     | C-425E2A      | `user2@`              |

### Domain Mismatches (1 total):
| Contact Key | Company Alias | Contact Domain   | Email Domain          |
|-------------|---------------|------------------|-----------------------|
| CT-0011     | C-66D1FC      | `66d1fc.com`       | `other-domain.com`      |

---

## 4. Company Field Enrichment & Discrepancies
### Enrichment Updates (missing CRM fields filled via `zoominfo_enrichment.csv`):
1.  `C-EC3025`: Fill `employee_count = 400`, update `industry` to `Computer Software`, standardize `hq_country` to `United States`
2.  `C-96039F`: Fill `employee_count = 400`
3.  `C-44EA29`: Update `industry` to `Computer Software`, fill `employee_count = 400`
4.  `C-D04904`: Update `industry` to `Computer Software`, fill `employee_count = 400`
5.  `C-B23205`: Fill `employee_count = 400`, fill `hq_country = United States`
6.  `C-60C75F`: Update `industry` to `Computer Software`
7.  `C-425E2A`: Update `industry` to `Computer Software`, standardize `hq_country` to `United States`
8.  `C-7BBDFA`: Fill `employee_count = 400`
9.  `C-50D386`: Fill `industry = health care`, fill `employee_count = 400`
10. No enrichment data available for: `C-2D1F1B`, `C-D73B89`, `C-2C60E5`

### CRM vs Enrichment Discrepancies (list both, recommended source):
| Company Alias | CRM Field Value          | Enrichment Field Value | Recommend Source |
|---------------|--------------------------|------------------------|------------------|
| C-66D1FC      | `industry: "tech"`         | `industry: "Computer Software"` | Enrichment (standardized terminology) |
| C-EC3025      | `industry: "Technology"`  | `industry: "Computer Software"` | Enrichment |
| C-EC3025      | `hq_country: "USA"`        | `hq_country: "United States"` | Enrichment (standardized country format) |
| C-92D97D      | `industry: "Technology"`   | `industry: "Computer Software"` | Enrichment |
| C-D04904      | `industry: "Technology"`   | `industry: "Computer Software"` | Enrichment |
| C-77A95A      | `industry: "Technology"`   | `industry: "Computer Software"` | Enrichment |
| C-AA8DDA      | `industry: "Technology"`   | `industry: "Computer Software"` | Enrichment |
| C-B25F40      | `industry: "Technology"`   | `industry: "Computer Software"` | Enrichment |
| C-60C75F      | `industry: "tech"`         | `industry: "Computer Software"` | Enrichment |
| C-425E2A      | `industry: "Tech "`        | `industry: "Computer Software"` | Enrichment |
| C-425E2A      | `hq_country: "USA"`        | `hq_country: "United States"` | Enrichment (standardized country format) |
| C-50D386      | `industry: (empty)`        | `industry: "health care"` | Enrichment |

---

## 5. Top 10 Fixes by Pipeline Amount
As noted above, **no `deals.csv` data was provided**, so pipeline amount calculations and identification of highest-risk pipeline fixes are not possible with the supplied dataset.

### Product Gaps Summary
Deal amounts are not provided in the supplied transcript and product documentation files.

1. **Prospect quote**: *"We need SCIM user provisioning — our security team will not approve any tool that requires manual account management."*
   **Classification**: Real product gap (SCIM user provisioning is not listed as a supported capability per the product docs)
   **Deal alias**: `Deal-EC3025`
   **Deal amount**: Not provided

2. **Prospect quote**: *"Our payroll runs on ADP Workforce Now and I don't see ADP anywhere in your integration list — that's a dealbreaker for us."*
   **Classification**: Real product gap (ADP Workforce Now integration is not listed as a supported capability per the product docs)
   **Deal alias**: `Deal-D0D6B5`
   **Deal amount**: Not provided

### Lead with in first five minutes
8/10 calls open with: "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."
2 alternate openings: "I put together a short agenda — security review first, then pricing." (1 call) and "You asked for straight pricing last time, so let's start there." (1 call)

### Three most common objections
1. Budget locked until next fiscal year: "Honestly, budget is locked until next fiscal year — I can't add a new line item right now." (4 calls)
2. Delayed due to open enrollment: "This is good, but can we revisit it next quarter? Open enrollment starts in October and we're underwater." (3 calls)
3. Current spreadsheet/gift card workflow suffices: "We already do recognition with a spreadsheet and quarterly gift cards — why would we change?" (3 calls)

### Concrete next step agreement rate
7/10 total calls (70%): All 7 calls where the rep asked *"Should we lock the next step — a working session with your team this week?"* resulted in a confirmed next step.

### 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."

show the model's full answer

# Redemption Report (August 2026 — last completed month)
## Core Metrics
1.  **Total Redemptions**: 43
2.  **Total Spend**: $3,191.00 USD  
    Calculation: $475 (TangoCard) + $825 (Tremendous) + $1,057 (Custom) + $834 (Snappy) = $3,191.00
3.  **Unique Redeemers**: 42 (1 duplicate user across Tremendous/Custom redemptions)
4.  **Redemptions per Redeemer**: 43 ÷ 42 ≈ 1.02
5.  **Provider Spend Mix (% of total)**:
    - TangoCard: ($475 / $3,191) × 100 ≈ 14.89%
    - Tremendous: ($825 / $3,191) × 100 ≈ 25.85%
    - Custom: ($1,057 / $3,191) × 100 ≈ 33.12%
    - Snappy: ($834 / $3,191) × 100 ≈ 26.14%
    - Total: 14.89% + 25.85% + 33.12% + 26.14% = 100.00%

## Top 5 Countries by Redemptions
1.  United States: 25 redemptions
2.  Canada: 8 redemptions
3.  Switzerland: 2 redemptions
4.  Singapore: 2 redemptions
5.  Australia: 2 redemptions; Netherlands: 2 redemptions (tied for 5th)

### Quarter 2026 Support Ticket Themes (Ranked by ARR Exposure)
Total tickets analyzed: 80

1.  **Theme: Billing & Invoice Tier/Seat Count Errors**
    - Count: 16 tickets
    - Share: 20% (16 ÷ 80)
    - Distinct Accounts: 1 (C-0E9C27D1)
    - Total ARR Affected: $832,000 (16 × $52,000 per ticket)
    - Ticket IDs: IC-460071, IC-460069
    - Recommendation: Resolve recurring seat-count discrepancies and incorrect tier pricing for C-0E9C27D1’s annual invoices.

2.  **Theme: HRIS Provisioning & Sync Failures**
    - Count: 11 tickets
    - Share: 13.75% (11 ÷ 80)
    - Distinct Accounts: 3 (C-0B2213A9, C-0F6C0F34, C-0DDFC9A7)
    - Total ARR Affected: $408,000 (7×$36,000 + 2×$30,000 + 2×$48,000 = $252,000 + $60,000 + $96,000)
    - Ticket IDs: IC-460059, IC-460060
    - Recommendation: Fix HRIS sync logic to create new hire accounts and resolve skipped provisioning runs with no logged errors.

3.  **Theme: Gift Card & Checkout Redemption Failures**
    - Count:19 tickets
    - Share:23.75% (19 ÷80)
    - Distinct Accounts:7 (C-0CEF69FD, C-0B827671, C-0FCCD2DF, C-0F876796, C-14264ABD, C-0D9CA315, C-0B0F1BAB)
    - Total ARR Affected: $186,900 (3×$8,900 +4×$10,700 +4×$9,600 +3×$8,700 +3×$11,000 +1×$9,600 +1×$10,300)
    - Ticket IDs: IC-460025, IC-460024
    - Recommendation: Debug checkout spin failures, missing gift card emails, and incorrectly deducted points for errored orders.

4.  **Theme: Points & Recognition Posting Failures**
    - Count:20 tickets
    - Share:25% (20 ÷80)
    - Distinct Accounts:9 (C-0D3278C7, C-0BF20542, C-0D0B047C, C-0BE96399, C-0D284E42, C-0D6CC8E3, C-21FEBCBB, C-0DD0626C, C-0B2895EF)
    - Total ARR Affected: $70,200 (3×$3,500 +2×$4,500 +3×$2,700 +3×$3,400 +3×$4,200 +1×$2,900 +2×$2,500 +1×$2,900)
    - Ticket IDs: IC-460004, IC-460016
    - Recommendation: Fix recognition delivery pipeline to ensure points post immediately after sent recognitions.

5.  **Theme: Slack Integration Issues**
    - Count:14 tickets
    - Share:17.5% (14 ÷80)
    - Distinct Accounts:4 (C-0B843542, C-10A56B0F, C-0BA71F12, C-8C2E8F00)
    - Total ARR Affected: $63,400 (3×$4,400 +4×$5,400 +6×$3,900 +1×$5,200)
    - Ticket IDs: IC-460041, IC-460047
    - Recommendation: Resolve Slack sync disconnections, toggle resets, and slash command errors for team channels.

Q3-2026 Marketing Goals Update:
*Note: No weekly performance data was provided, so specific weekly movements cannot be identified; all below reflects quarter-to-date (QTD) performance with full arithmetic.*

1.  **SQMs**: QTD actual=230, target=300, delta=230-300=-70 (70 below target). Prorated pace target = 300*(66/92)≈215; 230>215 → ahead of pace.
2.  **SQOs**: QTD actual=84, target=120, delta=84-120=-36 (36 below target). Prorated pace target=120*(66/92)≈86; 84<86 → behind pace.
3.  **DS2s**: QTD actual=40, target=75, delta=40-75=-35 (35 below target). Prorated pace target=75*(66/92)≈54; 40<54 → behind pace.
4.  **Closed-Lost MIA Rate**: Calculated as (closed_lost_mia / closed_lost_total) = 5/25=0.2 (20%), target=0.1 (10%). Delta=0.2-0.1=+0.1 (10pp above target; worse for lower-better metrics). Current rate would hold for the full quarter (double the target) → behind pace.
5.  **Same-Quarter Closes**: QTD actual=10, target=20, delta=10-20=-10 (10 below target). Prorated pace target=20*(66/92)≈14; 10<14 → behind pace.
6.  **Active Pipeline**: QTD actual=$3,000,000, target=$4,000,000, delta=3,000,000-4,000,000=-$1,000,000 ($1M below target). Prorated pace target=4,000,000*(66/92)≈$2.87M; $3M>$2.87M → ahead of pace.

What moved this week: No weekly trend data was provided, so specific weekly shifts cannot be detailed. Across the quarter-to-date, SQMs and active pipeline are ahead of their prorated quarterly pace, while SQOs, DS2s, same-quarter closes, and closed-lost MIA rate are underperforming relative to both their total quarterly targets and prorated pace.

Q1: Yes. Customer data is encrypted at rest using AES-256 ([P1]).
Q2: Yes. Data in transit is encrypted with TLS 1.2 or higher ([P1]).
Q3: Yes. Bonusly maintains a SOC 2 Type II report (renewed annually), available to prospects under NDA ([P2]).
Q4: Customer data is retained for the duration of the contract plus 90 days after contract termination ([P3]).
Q5: The current subprocessor list is maintained at trust.bonusly.com; customers receive 30 days' notice before a new subprocessor is added ([P4]).
Q6: Yes. SAML 2.0 single sign-on is available on the Enterprise plan ([P5]).
Q7: Production databases are backed up daily; backups are encrypted and retained for 35 days ([P6]).
Q8: Unanswerable. Provided policy excerpts do not include ISO 27001 certification details; relevant documentation would include compliance/certification materials.
Q9: Unanswerable. Provided policy excerpts do not include contractual uptime SLA percentage details; relevant documentation would include service-level agreement (SLA) documents.
Q10: Unanswerable. Provided policy excerpts do not include HIPAA Business Associate Agreement details; relevant documentation would include HIPAA-compliance or business associate agreement policies.

### NDA-1: GREEN
Driven by standard mutual confidentiality for business relationship evaluation, standard carve-outs per clause 3: *"information that (a) is or becomes publicly available through no breach, (b) was known prior to disclosure, (c) is received from a third party without duty of confidence, (d) is independently developed, or (e) must be disclosed by law or court order."*, 2-year term + 3-year survival period, Delaware governing law; no unusual terms. Arithmetic: Term = 2 years, survival obligation = 3 years post-termination.

### NDA-2: YELLOW
Driven by the non-solicitation clause (clause 4: *"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."*) which requires counsel review; all other terms are standard. Arithmetic: Term = 3 years, non-solicit period = 18 months post-term.

### NDA-3: RED
Driven by multiple high-risk terms: one-way confidentiality favoring [PARTY C], non-compete clause (clause 2: *"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."*), Republic of Ireland governing law with exclusive jurisdiction (clause 3), and no stated confidentiality carve-outs (clause 4). Arithmetic: Term = 5 years, non-compete period = 3 years post-effective date.