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

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CRM Audit Summary

1. Missing Deals Data  
• deals.csv not provided; owner, stage, amount, close date and why-buys completeness cannot be assessed or linked to pipeline amounts.

2. Completeness by Entity and Field  
• Companies (N=34)  
  – industry: 34/34 = 100%  
  – employee_count: 25/34 = 74%  
  – hq_country: 29/34 = 85%  

• Contacts (N=52)  
  – email: 52/52 = 100%  
  – title: 42/52 = 81%  
  – persona: 37/52 = 71%  

3. Duplicate-Domain Company Clusters  
Cluster 1: domain=acme-corp.com  
 • C-0A092931 (Technology, 500, US)  
 • C-0A092932 (tech, 510, USA) ← survivor: C-0A092932 (more recent emp_count)  

Cluster 2: domain=globex.io  
 • C-0A092933 (SaaS, 200, US) ← survivor: C-0A092933 (more specific industry)  
 • C-0A092934 (Technology, 200, US)  

4. Invalid Emails  
• CT-0010: “user0@”  
• CT-0080: “user0@”  
• CT-0081: “user1@”  
• CT-0192: “user2@”  

5. Email ↔ Domain Mismatches  
• CT-0010 (user0@ vs 66d1fc.com)  
• CT-0011 (user1@other-domain.com vs 66d1fc.com)  
• CT-0080 (user0@ vs 92d97d.com)  
• CT-0081 (user1@ vs 92d97d.com)  
• CT-0192 (user2@ vs 425e2a.com)  

6. Auto-Fill Missing Company Fields from ZoomInfo Enrichment  
(employee_count, where CRM blank & enrichment available)  
• C-EC3025 → 400  
• C-96039F → 400  
• C-44EA29 → 400  
• C-D04904 → 400  
• C-B23205 → 400  
• C-60C75F → 400  
• C-7BBDFA → 400  
• C-50D386 → 400  
(93C8BF.com not in enrichment → no fill)

No hq_country blanks could be filled (all enrichment hq_country blank or domain absent).

7. CRM vs Enrichment Disagreements (recommend using enrichment as canonical source)  
• industry  
  – C-66D1FC: CRM=tech vs ZI=Computer Software  
  – C-EC3025: CRM=Technology vs ZI=Computer Software  
  – C-44EA29: CRM=tech vs ZI=Computer Software  
  – C-92D97D: CRM=Technology vs ZI=Computer Software  
  – C-77A95A: CRM=Technology vs ZI=Computer Software  
  – C-AA8DDA: CRM=Technology vs ZI=Computer Software  
  – C-425E2A: CRM=Tech  vs ZI=Computer Software  

• hq_country  
  (US/USA vs United States)  
  – C-66D1FC, C-950043, C-EC3025, C-96039F, C-77A95A, C-B23205, C-E51FB7, C-D0662E, C-425E2A, C-2D7423  

8. Proposed Fixes  
1. Merge duplicate-domain records, retaining survivor IDs above.  
2. Normalize industry names (map “tech”/“Tech ”→“Technology”; “health care”→“Healthcare”).  
3. Normalize hq_country (“US”/“USA” → “United States”).  
4. Fill employee_count for 8 companies per enrichment.  
5. Manually source hq_country for the 5 remaining blanks.  
6. Correct invalid emails (add missing domains).  
7. Update mismatched email domains to match company domain.  
8. Populate missing contact titles (via data source or manual).  
9. Populate missing contact personas (via data source or manual).  
10. Standardize company_alias for merged clusters.  

No pipeline-amount ranking can be produced: deals data is missing.

Summary of real product gaps:

1. Deal-EC3025 (amount not provided)  
   Quote: “We need SCIM user provisioning — our security team will not approve any tool that requires manual account management.”  
   Classification: Real gap

2. Deal-D0D6B5 (amount not provided)  
   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 gap

Lead-in themes (first five minutes)  
• “Quick one to kick off: a 400-person retailer we work with cut regretted turnover 18% in two quarters after automating milestone awards, and I wanted to walk you through exactly how they did it.”  
• “I put together a short agenda — security review first, then pricing.”  
• “You asked for straight pricing last time, so let’s start there.”  

Three most common objections and Alex’s replies  
• Budget locked until next fiscal year (4×):  
  “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.”  
• Revisit next quarter/underwater (3×):  
  “Makes sense. What if we scope a 90-day pilot with one department so you have internal data before next quarter’s planning?”  
• “We already do recognition with a spreadsheet and quarterly gift cards” (3×):  
  “Spreadsheets work until they scale — the difference is automation: milestones fire without HR lifting a finger, and you get analytics on who is being recognized.”  

Concrete next-step agreed rate  
Agreed next step in 7 out of 10 calls → 7/10 = 70%  

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.”  

Coaching notes  
1. Rotate and personalize your opening—tailor the hook to the prospect’s industry or role to avoid sounding scripted.  
2. Pre-frame common objections in your intro and lock in next steps immediately after handling objections to boost your agreement rate.

Last completed month: August 2026

1. Redemption count  
   48  
   (Count of records with redeemed_at in 2026-08)

2. Total spend  
   \$3 536.00  
   (Sum of amount_usd for 2026-08: 3536.0)

3. Unique redeemers  
   46  
   (Distinct user_key values among those 48 records)

4. Redemptions per redeemer  
   48 ÷ 46 = 1.04

5. Provider mix (percent of spend)  
   • TangoCard: \$500 ÷ \$3 536 × 100 = 14.14%  
   • Tremendous: \$1 145 ÷ \$3 536 × 100 = 32.38%  
   • custom: \$1 057 ÷ \$3 536 × 100 = 29.89%  
   • Snappy: \$834 ÷ \$3 536 × 100 = 23.59%  
   (Shares sum to 100%)

6. Top 5 countries by redemption count  
   1. US – 31  
   2. CA – 7  
   3. GB – 2  
   4. SG – 2  
   5. AU – 2

1. HRIS provisioning failures  
   • Count: 12 (18% of tickets)  
   • Distinct accounts: 3 (C-0B2213A9, C-0F6C0F34, C-0DDFC9A7)  
   • ARR exposure: $114,000  
   • Sample tickets: IC-460059, IC-460062  
   • Recommendation: Implement retry logic and enhanced logging/alerts on the HRIS sync endpoint to ensure new-hire accounts are created reliably.

2. Gift-card redemption failures  
   • Count: 17 (25%)  
   • Distinct accounts: 7 (e.g. C-0CEF69FD, C-0B827671, C-14264ABD, …)  
   • ARR exposure: $68,800  
   • Sample tickets: IC-460025, IC-460030  
   • Recommendation: Fix the checkout timeout bug and integrate a reliable email-delivery pipeline so gift-card codes arrive without error.

3. Billing and invoicing errors  
   • Count: 12 (18%)  
   • Distinct accounts: 1 (C-0E9C27D1)  
   • ARR exposure: $52,000  
   • Sample tickets: IC-460071, IC-460069  
   • Recommendation: Correct seat-count and tier-pricing logic in the billing engine and add a pre-send invoice validation step.

4. Missing points posting  
   • Count: 14 (21%)  
   • Distinct accounts: 7 (e.g. C-0D3278C7, C-0BF20542, C-0D6CC8E3, …)  
   • ARR exposure: $25,300  
   • Sample tickets: IC-460004, IC-460016  
   • Recommendation: Audit the recognition-to-points pipeline and add end-to-end monitoring to ensure credit events are queued and processed.

5. Slack integration breakdowns  
   • Count: 12 (18%)  
   • Distinct accounts: 4 (C-0B843542, C-10A56B0F, C-0BA71F12, C-8C2E8F00)  
   • ARR exposure: $18,900  
   • Sample tickets: IC-460041, IC-460047  
   • Recommendation: Resolve token-persistence and slash-command endpoint issues in the Slack app and implement health checks to detect sync outages.

Weekly Marketing Goals Update for Q3-2026 (66/92 days elapsed)

SQMs  
 • QTD actual: 230  
 • Target: 300  
 • Δ: –70  
 • Pace: Ahead (required QTD = 300 × 66/92 = 215.2; 230 > 215.2)  

SQOs  
 • QTD actual: 84  
 • Target: 120  
 • Δ: –36  
 • Pace: Behind (required QTD = 120 × 66/92 = 86.1; 84 < 86.1)  

DS2s  
 • QTD actual: 40  
 • Target: 75  
 • Δ: –35  
 • Pace: Behind (required QTD = 75 × 66/92 = 53.8; 40 < 53.8)  

Closed-lost MIA rate  
 • QTD actual: 5/25 = 20.0%  
 • Target: 10.0%  
 • Δ: +10.0 pp  
 • Pace: Behind (20.0% > 10.0%)  

Same-quarter closes  
 • QTD actual: 10  
 • Target: 20  
 • Δ: –10  
 • Pace: Behind (required QTD = 20 × 66/92 = 14.35; 10 < 14.35)  

Active pipeline  
 • QTD actual: $3,000,000  
 • Target: $4,000,000  
 • Δ: –$1,000,000  
 • Pace: Ahead (required QTD = 4,000,000 × 66/92 = 2,869,565; 3,000,000 > 2,869,565)  

Weekly movement data was not provided, so unable to report what moved this week.

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. We maintain a SOC 2 Type II report, renewed annually, and it 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?
A current list of subprocessors is maintained at trust.bonusly.com. Customers receive 30 days’ notice before any new subprocessor is added. [P4]

Q6. Do you support SAML single sign-on?
Yes. SAML 2.0 single sign-on (and SCIM user provisioning) is available on our Enterprise plan. [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. ISO 27001 certification is not covered in the provided policy excerpts; please refer to our ISO 27001 certification documentation or security compliance report.

Q9. What is your contractual uptime SLA percentage?
Unanswerable. Uptime SLA details are not included in the provided excerpts; please refer to our Service Level Agreement document.

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NDA-1 — GREEN — “Carve-outs: information that (a) is or becomes publicly available through no breach, (b) was known prior to disclosure, (c) is received from a third party without duty of confidence, (d) is independently developed, or (e) must be disclosed by law or court order.”  

NDA-2 — YELLOW — “Non-solicitation: ‘During the term of this Agreement and for eighteen (18) months thereafter, neither party shall solicit for employment or hire any employee of the other party with whom it came into contact under this Agreement.’”  

NDA-3 — RED — “Non-compete: ‘For a period of three (3) years following the Effective Date, Recipient shall not, directly or indirectly, engage in or provide services to any business that competes with Discloser's business.’”