# Deal Split Reconciliation

*/Opportunities/Deal_Split_Reconciliation*

## Opportunity Overview

**Wedge**: Target B2B SaaS companies using paired Account Executive and Sales Engineer teams. This niche experiences the highest volume of disputes because technical evaluations create ambiguous contribution boundaries. Expand from technical overlays into SDR-to-AE handoffs, and finally into external channel partner attribution.
**Timing**: Models now reliably extract attribution and timeline sequences from noisy unstructured text like chat logs and meeting transcripts. This makes automated synthesis of deal participation possible without forcing reps to fill out endless forms.
**Why This I C P**: Mid-market B2B software sales organizations run complex overlay models with sales engineers and account managers but lack the massive custom-built RevOps headcount of Fortune 500s. They have the acute dispute pain alongside modern API-accessible data stacks.
**Size Of Prize**: ~50,000 US mid-market and enterprise sales organizations × ~$30,000 annual RevOps labor spent resolving commission disputes = ~$1.5B total prize.
**Gap Narrative**: RevOps and commission teams manually investigate CRM audit trails and communication threads to determine correct quota retirement for co-sold deals. Current commission software relies on clean CRM inputs, but reps routinely log splits late, incorrectly, or dispute them post-close. This demands a system that reads unstructured proof to validate and correct deal splits before payroll runs.
**Defensibility**: Defensibility builds through workflow lock-in as the system writes verified splits directly into payroll engines like Spiff or CaptivateIQ. Disconnecting the integration breaks the compensation cycle, while the system continuously maps company-specific sales terminology to improve accuracy.
**Why This Thesis**: Service-as-Software matches the shape of the problem because split reconciliation is an internal service provided by RevOps. Delivering a verified split decision directly into the commission system mimics the human workflow without forcing sales teams to adopt new interfaces.

## Opportunity Linked Thesis

**Thesis**: [Software](/Theses/Software)

## Opportunity Linked I C P

**Icp**: [Real Estate Brokerage](/CompanyTypes/Real_Estate_Brokerage)

## Opportunity Market Sizing

_Illustrative — target and order-of-magnitude estimate figures, not an achieved track record (this Thing is concept-stage)._

**S A M**: ~$100M-200M North American mid-market brokerages with multi-tier team structures
**S O M**: ~$5M-15M
**T A M**: ~80k-100k North American real estate brokerages × ~$3k-5k/yr ≈ ~$250M-500M
**Growth Rate**: ~8-12%/yr, driven by the proliferation of complex agent team structures and dynamic commission caps
**Paid Comparable Spend**: ~$15k-30k/yr on dedicated administrative labor, part-time bookkeepers, and legacy back-office software to manually track commission caps

## Opportunity Incumbents

- [Microsoft Excel](/Products/Microsoft_Excel) — Spreadsheet
- [Google Sheets](/Products/Google_Sheets) — Spreadsheet
- [Xactly Incent](/Products/Xactly_Incent) — Tool
- [CaptivateIQ Platform](/Products/CaptivateIQ_Platform) — Tool
- [Salesforce Revenue Cloud](/Products/Salesforce_Revenue_Cloud) — Tool
- [Spiff Compensation](/Products/Spiff_Compensation) — Tool
- [Manual CRM Exports](/Products/Manual_CRM_Exports) — DIY
- [Custom Python Scripts](/Products/Custom_Python_Scripts) — DIY

## Opportunity Win Conditions

**Kill Thresholds**:
- Less than 50 percent of pilot users complete a full payout cycle in 30 days
- Manual override rate remains above 20 percent after the second month
- Average contract value closes under $3,000 per year
- Customer acquisition cost exceeds $2,500
**Leading Metrics**:
- Days from signup to first automated commission run
- Percentage of deals reconciled without manual override
- Number of connected data integrations per brokerage
- Agent dispute ticket volume per payout cycle
**What Proves Right**: Brokerages connect their transaction data sources and run their first full commission cycle without manual spreadsheet adjustments within 14 days of onboarding. Admin teams reduce time spent on end-of-month reconciliation by 80 percent and dispute rates from agents drop near zero. Customers willingly sign $5,000 annual contracts after a single 30-day pilot cycle.
**What Proves Wrong**: The platform requires constant human intervention because edge-case commission rules or bespoke team agreements cannot be mapped into the rules engine. Brokerages abandon pilots mid-cycle because the output differs from their legacy spreadsheets and they lack trust in the automated numbers. The sales cycle stretches past 90 days as brokers demand custom engineering work before committing.

## Opportunity Build Profile

**Hardest Part**: Translating bespoke, free-text deal-split agreements buried in CRM opportunity notes into deterministic, auditable compensation rules that pass finance review.
**Min Viable Scope**: Focus exclusively on internal AE and SDR deal splits originating in Salesforce, exporting a verified flat file for payroll. Deliberately leave out channel partner commissions, multi-currency conversions, and direct write-access integrations with specialized compensation software.
**Cold Start Problem**: The engine requires messy, real-world sales data and historical dispute logs to tune its parsing logic. Solve this by securing one mid-market design partner and running a shadow back-test on their last 12 months of finalized commission payouts.
**Time To First Value**: 1 full commission cycle (typically 30 days) to run parallel to the manual process and prove zero variance.
**Data Moat Available**: false
**Technical Difficulty**: Moderate

## Neighborhood

### Where the gap lives

- [Commission Calculation](/Processes/Commission_Calculation) — latent gap · Processes

### Incumbent in

- [Bespoke Python Scripts](/Products/Bespoke_Python_Scripts) — incumbent in · Products
- [Microsoft Excel](/Software/Microsoft_Excel) — incumbent in · Software
- [Xactly Incent](/Products/Xactly_Incent) — incumbent in · Products
- [Google Sheets](/Software/Google_Sheets) — incumbent in · Software
- [CaptivateIQ Platform](/Products/CaptivateIQ_Platform) — incumbent in · Products
- [Manual CRM Exports](/Products/Manual_CRM_Exports) — incumbent in · Products
- [Salesforce Revenue Cloud](/Products/Salesforce_Revenue_Cloud) — incumbent in · Products
- [Spiff Compensation](/Products/Spiff_Compensation) — incumbent in · Products

### Applies thesis

- [Real Estate Brokerage](/CompanyTypes/Real_Estate_Brokerage) — applies thesis · CompanyTypes

### Embodies

- [Software](/Theses/Software) — embodies · Theses

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