> ## Documentation Index
> Fetch the complete documentation index at: https://help.mytruv.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Spending Trends

> See how your spending changes across days, weeks, months, or years.

The **Spending over time** chart tracks your spending across a configurable time window so you can spot patterns, see if a change in habits is working, or just understand the rhythm of your spending.

## Where to find it

The trend chart is on the Spending page - see [Spending Overview](/spending/spending-overview) for the full layout.

## Picking a time range

The time-range options carry different labels on each platform:

<Note>
  **On the web** - **Days**, **Weeks**, **Months**, **Year**.

  **On iOS** - **30D**, **3M**, **6M**, **1Y**.
</Note>

Each option re-buckets the same underlying spending data at a different granularity - daily bars zoom in on recent days; the longest range smooths out short-term noise so you can see the trend.

## What the chart shows

* **Total spending per bucket** - the height of each bar / point
* **Average per period** - shown alongside the total in the chart header
* **Trend direction** - visually obvious from the slope; the chart also calls out the period total at the top

## What it's good for

* **Spot patterns** - holidays, summer travel, end-of-year shopping all show up clearly over a long enough window
* **Track changes** - did you cut subscriptions a few months ago? The trend should show a step-down in the months after
* **Plan ahead** - your typical monthly average is a starting point for planning future months

## Related

* [Month-to-Date Spending](/spending/month-to-date-spending) for the pace check inside the current month
* [Comparing Spending Across Periods](/spending/comparing-spending-periods) for explicit period-over-period comparisons
* [Spending by Category](/spending/spending-by-category) to break the trend down by where the money goes

<Tip>Look at trends over at least 3 - 6 months. Two months of data is too noisy to draw conclusions; six months reveals real patterns.</Tip>