Spending Review

Overview

Wilson Tools Used

• spending_summary

  — get total spending grouped by category for any date range

• transaction_search

  — drill into specific categories for transaction-level detail

Workflow

1. Run

   spending_summary

   for the current month to get category-level totals.
2. Run

   spending_summary

   for the previous month to establish a comparison baseline.
3. Calculate the dollar change and percentage change for each category between the two months.
4. Flag any category where spending increased by more than 20% or more than $100.
5. For each flagged category, run

   transaction_search

   with

   category: "<flagged_category>"

   and

   months: 1

   to pull the individual transactions driving the increase.
6. Present results as a summary table with columns: Category, This Month, Last Month, Change ($), Change (%), Trend Arrow.
7. Below the table, list the top 3 categories by absolute spending and the top 3 by percentage increase.
8. Provide a one-paragraph narrative summary describing the overall spending pattern and notable changes.

Without Wilson

1. Export your last two months of transactions as CSV files from your bank (most banks: Account > Statements > Download > CSV format).
2. Open both CSVs in Google Sheets. Combine them into one sheet with a "Month" column added.
3. If your bank doesn't categorize transactions, manually add a "Category" column. Common categories: Groceries, Dining, Transportation, Utilities, Entertainment, Shopping, Health, Subscriptions.
4. Create a pivot table: Rows = Category, Columns = Month, Values = SUM of Amount.
5. Add a calculated column for change:

   =B2-C2

   (this month minus last month).
6. Add a percentage change column:

   =IF(C2<>0, (B2-C2)/ABS(C2)*100, "New")

   .
7. Conditional format the change column: red for increases, green for decreases (since spending is negative, reverse the logic or use absolute values).
8. Sort by absolute change descending to see your biggest movers.
9. For a quick visual, insert a bar chart from the pivot table showing this month vs. last month by category.

Important Notes

• Category accuracy depends on your bank's auto-categorization or Wilson's categorization rules. Run the

  categorize

  tool first if many transactions are uncategorized.
• One-time large purchases (appliances, travel, medical) can skew month-over-month comparisons. Consider whether a spike is a true trend or an outlier.
• For a more meaningful view, compare against a 3-month rolling average rather than just the prior month.