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Seller Approval Workflow
Rules-based marketplace solution that evaluates business credentials, expertise, inventory quality, and background checks to maintain seller standards.
Solution
This automated seller approval system streamlines the onboarding process by evaluating multiple qualification factors before accepting new merchants. It analyzes business credentials by verifying documentation authenticity and assessing company maturity based on years in operation. The expertise validation ensures merchants have adequate knowledge in their primary category, while inventory quality assessment examines product authenticity, compliance with regulations, and image quality standards.
The system incorporates comprehensive background screening including criminal record verification, credit assessment, and identity confirmation. When evaluating applications, each factor receives a weighted score that contributes to the final approval decision. Rejected applications include specific reasoning, allowing potential sellers to address deficiencies. Approved sellers receive immediate confirmation with their qualification score, enabling marketplace operators to maintain consistent quality standards while efficiently processing applications.
How it works
The decision graph processes seller applications through a series of evaluation stages:
- Input Processing: Collects business credentials, category expertise information, inventory quality data, and background check results.
- Business Credential Validation: Assigns scores based on documentation validity and business longevity, categorizing businesses as new, established, or mature.
- Qualification Assessment: Evaluates the combined factors of business status, category expertise rating, inventory quality, and background check results.
- Scoring Algorithm: Calculates a final qualification score by weighing each factor appropriately and applying business rules.
- Approval Decision: Routes applications through approval or rejection paths based on qualification thresholds.
- Result Generation: Creates final response with approval status, qualification score, and timestamp.
Where teams use it
- Online marketplaces and retail platforms
- B2B wholesale supplier networks
- Specialty product marketplaces
- Artisan and handcrafted goods platforms
- Service provider networks
- Digital product marketplaces
Inside the decision model
Seller Approval Workflow ships as a JDM decision graph with 6 nodes, 2 decision tables and 11 rules. Download it, load it into GoRules, and run it as-is on Zen Engine.
Seller Application Request
inputEvery application carries four top-level blocks: businessCredentials, categoryExpertise, inventoryQuality, and backgroundCheck. Fields like businessCredentials.yearsInBusiness, categoryExpertise.rating, and backgroundCheck.passed feed the two scoring tables directly.
Sample requestJSON
{
"businessCredentials": {
"hasValidDocumentation": true,
"yearsInBusiness": 2.5,
"businessName": "TechGadgets LLC",
"businessType": "Limited Liability Company",
"taxId": "12-3456789"
},
"categoryExpertise": {
"primaryCategory": "Electronics",
"yearsOfExperience": 3,
"certifications": [
"Consumer Electronics Specialist"
],
"rating": 4
},
"inventoryQuality": {
"sampleProducts": 15,
"brandAuthenticity": true,
"productCompliance": true,
"productImageQuality": "high",
"rating": 4.2
},
"backgroundCheck": {
"passed": true,
"criminalRecord": false,
"creditScore": 720,
"identityVerified": true
}
}Evaluate Business Credentials
tableDocumentation validity is checked before anything else: with a first hit policy, the row where businessCredentials.hasValidDocumentation is false returns a credentialScore of 0 and a businessStatus of 'invalid'. Valid businesses are then banded by businessCredentials.yearsInBusiness, with under 1 year scoring 15 as 'new', the [1..3) range scoring 25 as 'established', and 3 or more years scoring 35 as 'mature'.
Gating on documentation first mirrors how marketplaces actually onboard merchants, since a missing registration or tax record stops review regardless of other strengths. The one and three year cutoffs are sensible proxies for survival risk, as most small-business failures happen in the first years of trading, so longevity earns a progressively larger share of the credential score.
| Has Valid DocumentationbusinessCredentials.hasValidDocumentation | Years In BusinessbusinessCredentials.yearsInBusiness | Credential Scoreevaluation.credentialScore | Business Statusevaluation.businessStatus | Credential Notesevaluation.credentialNotes |
|---|---|---|---|---|
| false | - | 0 | 'invalid' | 'Business documentation is missing or invalid' |
| true | < 1 | 15 | 'new' | 'New business with limited history' |
| true | [1..3) | 25 | 'established' | 'Established business with moderate history' |
| true | >= 3 | 35 | 'mature' | 'Mature business with solid history' |
Evaluate Seller Qualifications
tableFour signals converge here under a first hit policy: evaluation.businessStatus, categoryExpertise.rating, inventoryQuality.rating, and backgroundCheck.passed. An 'invalid' status short-circuits to a finalScore of 0, a failed background check caps the score at 15 or 30 depending on whether expertise sits below or at least 3, and a passed check with inventoryQuality.rating below 3 still rejects at 40 with 'Low inventory quality score'. Sellers rating at least 3 on both expertise and inventory are approved at 85 as a 'Strong seller profile', and the fallback row approves remaining passed applicants at evaluation.credentialScore + 30 as a 'Standard seller approval'.
Treating the background check as a hard gate is standard marketplace practice, because fraud and counterfeit exposure lands on the platform no matter how skilled the seller is. The inventory quality floor protects the catalog itself, while the additive fallback keeps borderline but clean applicants in play, so rejections come with a specific stated reason rather than a single opaque score.
| Business Statusevaluation.businessStatus | Category ExpertisecategoryExpertise.rating | Inventory QualityinventoryQuality.rating | Background Check PassedbackgroundCheck.passed | Final Scoreevaluation.finalScore | Is Approvedevaluation.isApproved | Evaluation Notesevaluation.notes |
|---|---|---|---|---|---|---|
| == 'invalid' | - | - | - | 0 | false | 'Business credentials are invalid' |
| - | < 3 | - | false | 15 | false | 'Failed background check and low category expertise' |
| - | >= 3 | - | false | 30 | false | 'Failed background check despite good category expertise' |
| - | - | < 3 | true | 40 | false | 'Low inventory quality score' |
| - | >= 3 | >= 3 | true | 85 | true | 'Strong seller profile with good expertise and inventory' |
| - | >= 4 | >= 4 | true | 95 | true | 'Exceptional seller profile with excellent expertise and inventory' |
+1 more row in the downloadable template
Route Application
switchRouting splits on a single boolean: the condition evaluation.isApproved == true sends the application down the approval branch, and the default statement catches everything else as a rejection. Keeping the branch logic out of the scoring tables lets each outcome build its own response payload.
Generate Approval Result Generate Rejection ResultGenerate Approval Result
expressionApproved applications are reduced to a clean response: status is set to 'APPROVED', score carries evaluation.finalScore forward, and approvalDate is stamped with date('now'). With passThrough disabled, intermediate evaluation fields stay out of the payload returned to the onboarding system.
'APPROVED'evaluation.finalScoredate('now')Generate Rejection Result
expressionOn the rejection branch the shape mirrors the approval payload, with status set to 'REJECTED' and a rejectionDate from date('now'). Returning evaluation.finalScore even on rejection lets applicants see how far they fell short of the approval bar before reapplying.
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Make this template
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Load Seller Approval Workflow into GoRules, adjust the rules to your policy, and ship it behind your own API.