Quick update to trace explorer doc

docs/product/explore/trace-explorer/index.mdx

@@ -12,10 +12,10 @@ The [**Trace Explorer**](https://sentry.io/orgredirect/organizations/:orgslug/tr
 
 ### Traces
 
-- A trace represents a single transaction or request through your system. This includes things like user browser sessions, HTTP requests, DB queries, middleware, caches and more.
-- It captures a series of operations (_spans_) that show how different parts of your application interacted during that transaction.
+- A trace represents a series of transactions or requests through a single system. This includes things like user browser sessions, HTTP requests, DB queries, middleware, caches and more.
+- It captures a series of operations (_spans_) that show how different parts of your application interacted during each transaction.
 - Each trace is identified by a **Trace ID**, which you can use to follow a request across services or projects.
-- A [distributed trace](/platforms/javascript/tracing/trace-propagation/#what-is-distributed-tracing) is made of spans that traverse multiple servers, clients, edge workers, etc. and is assembled by passing the Trace ID through browser headers.
+- A [distributed trace](/platforms/javascript/tracing/trace-propagation/#what-is-distributed-tracing) is made of transactions and spans that traverse multiple servers, clients, edge workers, and other parts of your system. It is assembled by passing the Trace ID through browser headers.
 
 ### Spans
 
@@ -26,7 +26,7 @@ The [**Trace Explorer**](https://sentry.io/orgredirect/organizations/:orgslug/tr
 
 ### Span Metrics
 
-- [Span metrics](/concepts/key-terms/tracing/span-metrics/) are derived from applying a function to your span attributes (default or custom), like `p50(cart.value)` or `sum(ai.token_use)`, over a granular time frame. This calculation extrapolates metrics that then populate dashboards, alerts, etc. based on that rolling time window.
+- [Span metrics](/concepts/key-terms/tracing/span-metrics/) are derived from applying a function to your span attributes (default or custom), like `p50(cart.value)` or `sum(ai.token_use)`, over a granular time frame. This calculation extrapolates metrics that then populate dashboards and alerts. based on that rolling time window.
 - These 'metrics' aren't stored separately from your span data. Rather, they're queried on the fly. This reduces your need to manage, ingest, and store custom metrics.
 
 ## Practical Examples
@@ -47,7 +47,7 @@ With these tools, the new Trace Explorer gives you powerful ways to understand y
 Trace Explorer allows you to browse span and trace samples and inspect them. Here's how:
 
 1. **Search for Samples**:
-   - Use the search bar to filter results based on default or custom attributes, tags, etc. like `http.request_method is "GET`
+   - Use the search bar to filter results based on default or custom attributes, tags, and strings like `http.request_method is "GET`
    - **Edit and add** columns in the span samples table to view any attribute
    - **Sort** by clicking the column header to toggle between ascending and descending
    - Switch between **Span Samples** and **Trace Samples** tabs depending on your focus.
@@ -90,12 +90,14 @@ Dive deeper into your data with aggregation capabilities in Trace Explorer.
 
 <Arcade src="https://demo.arcade.software/rgVB85wJiopGNPO3KFJS?embed" />
 
-## Create Alerts and Dashboard Widgets From Queries
+## Create Alerts and Dashboard Widgets From Queries or Compare Queries
 
 You can create Alerts and Dashboard widgets from your queries by clicking the "Save As" button:
 
 ![Trace Explorer Screenshot](./img/trace_explorer_save.png)
 
+You can also run side-by-side comparisons of different queries to analyze changes or differences in span data.
+
 ## Practical Examples
 
 - **Diagnosing slow pages**: