diff --git a/.gitignore b/.gitignore
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+++ b/.gitignore
@@ -71,3 +71,6 @@ env/
 env.bak/
 venv/
 venv.bak/
+
+# Claude Code files
+CLAUDE.md
diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -26,15 +26,27 @@
 The following table provides a detailed list of all tables materialized within this package by default.
 > TIP: See more details about these tables in the package's [dbt docs site](https://fivetran.github.io/dbt_linkedin/#!/overview?g_v=1&g_e=seeds).
 
-| **Table**                          | **Description**                                                                                                        |
-| ---------------------------------- | ---------------------------------------------------------------------------------------------------------------------- |
-| [linkedin_ads__account_report](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__account_report)        | Each record represents the daily ad performance of each account.                                                       |
-| [linkedin_ads__campaign_report](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__campaign_report)       | Each record represents the daily ad performance of each campaign. Linkedin campaigns map onto ad groups in other ad platforms.                                                      |
-| [linkedin_ads__monthly_campaign_country_report](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__monthly_campaign_country_report)       | Each record represents the monthly performance of a campaign at the country level.                                                      |
-| [linkedin_ads__monthly_campaign_region_report](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__monthly_campaign_region_report)       | Each record represents the monthly performance of a campaign at the region level.                                                      |
-| [linkedin_ads__campaign_group_report](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__campaign_group_report) | Each record represents the daily ad performance of each campaign group. Linkedin                                                 |
-| [linkedin_ads__creative_report](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__creative_report) | Each record represents the daily ad performance of each creative.                                                |
-| [linkedin_ads__url_report](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__url_report) | Each record represents the daily ad performance of each url.                                                |
+| **Table** | **Details** |
+|-----------|-------------|
+| [`linkedin_ads__account_report`](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__account_report) | Represents daily performance aggregated at the account level, including `spend`, `clicks`, `impressions`, and `conversions`.<br><br>**Example Analytics Questions:**<ul><li>How does performance compare across different accounts by account manager?</li><li>Are currency fluctuations affecting results across markets?</li></ul> |
+| [`linkedin_ads__campaign_report`](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__campaign_report) | Represents daily performance aggregated at the campaign level (equivalent to ad groups in other platforms), including `spend`, `clicks`, `impressions`, and `conversions`.<br><br>**Example Analytics Questions:**<ul><li>Which campaigns have the strongest engagement relative to their budget?</li><li>Do certain campaigns dominate impressions within a campaign group?</li><li>Are new campaigns ramping up as expected after launch?</li></ul> |
+| [`linkedin_ads__monthly_campaign_country_report`](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__monthly_campaign_country_report) | Represents monthly performance aggregated at the campaign level by country, including `spend`, `clicks`, `impressions`, and `conversions`, enriched with geographic context.<br><br>**Example Analytics Questions:**<ul><li>Which countries are delivering the highest return on ad spend for each campaign?</li><li>Are there seasonal performance variations by geographic region?</li></ul> |
+| [`linkedin_ads__monthly_campaign_region_report`](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__monthly_campaign_region_report) | Represents monthly performance aggregated at the campaign level by region, including `spend`, `clicks`, `impressions`, and `conversions`, enriched with geographic context.<br><br>**Example Analytics Questions:**<ul><li>Which regions are driving the most efficient campaign performance?</li><li>How do regional performance trends correlate with local market conditions?</li></ul> |
+| [`linkedin_ads__campaign_group_report`](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__campaign_group_report) | Represents daily performance aggregated at the campaign group level (equivalent to campaigns in other platforms), including `spend`, `clicks`, `impressions`, and `conversions`.<br><br>**Example Analytics Questions:**<ul><li>Which campaign groups are most efficient in terms of cost per conversion?</li><li>Are paused or limited-status campaign groups still accruing impressions?</li><li>How does performance vary by advertising channel type across campaign groups?</li></ul> |
+| [`linkedin_ads__creative_report`](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__creative_report) | Represents daily performance at the individual creative level (equivalent to ads in other platforms), including `spend`, `clicks`, `impressions`, and `conversions`.<br><br>**Example Analytics Questions:**<ul><li>Which creative formats are driving the lowest cost per click?</li><li>Do video creatives perform better than static image creatives?</li><li>How do performance trends change after refreshing creative content?</li></ul> |
+| [`linkedin_ads__url_report`](https://fivetran.github.io/dbt_linkedin/#!/model/model.linkedin.linkedin_ads__url_report) | Represents daily performance at the individual URL level, including `spend`, `clicks`, `impressions`, and `conversions`, enriched with creative context.<br><br>**Example Analytics Questions:**<ul><li>Which landing pages are driving the highest conversion rates?</li><li>Are certain URLs performing better with specific creative combinations?</li></ul> |
+
+Many of the above reports are now configurable for [visualization via Streamlit](https://github.com/fivetran/streamlit_ad_reporting). Check out some [sample reports here](https://fivetran-ad-reporting.streamlit.app/ad_performance).
+
+### Example Visualizations
+
+Curious what these tables can do? The Linkedin models provide advertising performance data that can be visualized to track key metrics like spend, impressions, click-through rates, conversion rates, and return on ad spend across different campaign structures and time periods. Check out example visualizations in the [Fivetran Ad Reporting Streamlit App](https://fivetran-ad-reporting.streamlit.app/ad_performance), and see how you can use these tables in your own reporting. Below is a screenshot of an example dashboard; explore the app for more.
+
+<p align="center">
+  <a href="https://fivetran-ad-reporting.streamlit.app/ad_performance">
+    <img src="https://raw.githubusercontent.com/fivetran/dbt_linkedin/main/images/streamlit_example.png" alt="Fivetran Ad Reporting Streamlit App" width="100%">
+  </a>
+</p>
 
 ### Materialized Models
 Each Quickstart transformation job run materializes 25 models if all components of this data model are enabled. This count includes all staging, intermediate, and final models materialized as `view`, `table`, or `incremental`.
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