Merchant-Level Categorisation

How It Works

• Extraction: Merchant information and transaction details are extracted from the receipt or invoice.
• Analysis: The extracted data is analysed using Taggun Machine Learning algorithms.
• Categorisation: An expense category is assigned to the transaction (from a finite list of categories).
• Confidence Scoring: A confidence level is provided for the assigned category to indicate how close it is to that category.

Set-Up Process

1. Contact Taggun

Reach out to [email protected] to enable this feature for your account.

2. API Endpoints

Available under Verbose Data Extraction API Endpoints

• Upload File (verbose)
• Encoded File (verbose)
• URL (verbose)

3. Make an API call

No changes are required. This feature automatically returns data once activated by Taggun.

Example

Image

Response

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Access Path

Access the category via the path entities.category.data

A snippet from the JSON Payload:

{
  "entities": {
    "category": {
      "data": "food & drink",
      "confidenceLevel": 0.81
    }
  }
}

Standard Categories

Taggun offers the following standard expense categories:

• entertainment
• mail & courier
• taxi
• hotel
• subscriptions & online services
• car toll
• parking
• petrol station
• bus fare & train fare
• stationery & office supplies
• food & drink

Use Cases

• Corporate expense management
• Personal finance tracking
• Market analysis and consumer behaviour insights

Best Practices

• Use the confidence level to determine when manual review might be necessary.
• Combine with Product-Level Categorisation for more detailed insights.

Customisation

The transaction categorisation feature is powerful, but it may need fine-tuning to be truly effective for your unique setup. If the standard categories don't align with your specific requirements, reach out to us at [email protected] to set up custom categories.