Basic TagMatcher Rules

TagMatcher is the app's automatic categorization system. It uses rules you create to automatically assign tags (categories) to transactions based on their description. This saves you hours of manual categorization.

What is TagMatcher?

TagMatcher is a rule engine that:

• Reads transaction descriptions - Looks at merchant names, transaction text
• Matches against rules - Compares description to your rules
• Assigns tags automatically - Categorizes transactions based on matches
• Applies deterministically - Same transaction always gets same tag

Why Use TagMatcher?

Without TagMatcher:
- You manually categorize every transaction
- Takes hours each month
- Easy to make mistakes or be inconsistent
- Tedious and repetitive

With TagMatcher:
- Rules categorize transactions automatically
- Takes minutes to set up rules
- Consistent categorization every time
- You only review exceptions

How TagMatcher Works

TagMatcher uses two types of matching:

1. Contains - Description contains specific text
2. Equals - Description exactly matches text

Rules are evaluated in priority order - first match wins.

Creating Your First Rule

Step 1: Navigate to TagMatcher

1. Go to Settings in main navigation
2. Click "TagMatcher Rules" or navigate to TagMatcher Rules
3. Click "New Rule" button

Try it now: If you have demo data, view TagMatcher rules to see the pre-configured rules, then create your own.

Step 2: Choose Match Type

For your first rule, start with "Contains" - it's the simplest and most flexible.

Step 3: Enter Match Text

Enter the text you want to match. For example:
- "STARBUCKS" - Matches any transaction containing "STARBUCKS"
- "AMAZON" - Matches any transaction containing "AMAZON"
- "WALMART" - Matches any transaction containing "WALMART"

Tip: Use uppercase - transaction descriptions are usually uppercase.

Step 4: Select Tag

Choose the tag (category) to assign when this text is found:
- "Dining Out" for Starbucks
- "Shopping" for Amazon
- "Groceries" for Walmart

Step 5: Set Priority

Priority determines which rule wins if multiple rules match:
- Higher priority (lower number) = checked first
- Lower priority (higher number) = checked later

For now, use priority 1 (highest priority).

Step 6: Save Rule

Click "Save Rule". The rule is now active and will categorize matching transactions.

Example Rules

Here are some common rules to get you started:

Grocery Stores

• Contains: "WALMART" → Tag: "Groceries"
• Contains: "TARGET" → Tag: "Groceries"
• Contains: "KROGER" → Tag: "Groceries"
• Contains: "SAFEWAY" → Tag: "Groceries"

Restaurants

• Contains: "STARBUCKS" → Tag: "Dining Out"
• Contains: "MCDONALDS" → Tag: "Dining Out"
• Contains: "CHIPOTLE" → Tag: "Dining Out"

Utilities

• Contains: "ELECTRIC" → Tag: "Utilities"
• Contains: "GAS COMPANY" → Tag: "Utilities"
• Contains: "WATER DEPT" → Tag: "Utilities"

Subscriptions

• Contains: "NETFLIX" → Tag: "Subscriptions"
• Contains: "SPOTIFY" → Tag: "Subscriptions"
• Contains: "AMAZON PRIME" → Tag: "Subscriptions"

Testing Your Rules

After creating a rule, test it:

1. Go to Transactions list
2. Find a transaction that should match your rule
3. Check if it was automatically tagged
4. If not, review the transaction description and adjust your rule

Tip: Review several transactions to make sure your rule is matching correctly before moving on.

Rule Priority

When multiple rules could match, priority matters:

Example:
- Rule 1 (Priority 1): Contains "AMAZON" → Tag: "Shopping"
- Rule 2 (Priority 2): Contains "AMAZON PRIME" → Tag: "Subscriptions"

Transaction: "AMAZON PRIME MONTHLY"

Result: Rule 1 matches first (contains "AMAZON"), so transaction gets "Shopping" tag, even though Rule 2 is more specific.

Solution: Put more specific rules (like "AMAZON PRIME") at higher priority (lower number) than general rules (like "AMAZON").

Best Practices

1. Start simple - Use "Contains" matching for most rules
2. Be specific - More specific rules = fewer mistakes
3. Test regularly - Check that rules are working as expected
4. Review exceptions - Manually categorize transactions that don't match
5. Adjust as needed - Rules aren't set in stone; refine them over time

Common Mistakes

Mistake: Too General

Bad Rule: Contains "STORE" → Tag: "Shopping"
Problem: Matches "BOOKSTORE", "STORAGE", "STORE CREDIT", etc.

Better: Be more specific - "TARGET", "WALMART", etc.

Mistake: Wrong Priority

Problem: General rule matches before specific rule

Solution: Put specific rules at higher priority (lower number)

Mistake: Case Sensitivity

Problem: Rule uses lowercase but transactions are uppercase

Solution: TagMatcher is usually case-insensitive, but use uppercase to be safe

What's Next?

Once you have basic rules working:
- Module 5 will cover advanced TagMatcher strategies (priority ordering, comprehensive rule sets)
- You'll learn to fine-tune rules for better accuracy
- You'll create rules for all your common merchants

For now, create 5-10 basic rules for your most common transactions. This will handle the majority of your categorization automatically.

Key Takeaway: TagMatcher rules automatically categorize transactions based on description text. Start with simple "Contains" rules for your most common merchants. Test them, adjust priority, and refine over time. Even basic rules save hours of manual work.