> For the complete documentation index, see [llms.txt](https://docs.clearout.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.clearout.io/data-pulse/features-and-functionality.md).

# Features & Functionality

The core functionality of the **Data Pulsing Engine** is to act as a real-time data quality layer to validate and qualify your contacts in CRMs (e.g., HubSpot, Salesforce, Zoho) by eliminating any external automation platforms/tools.

### Data Verification & Validation

Currently, Data Pulse supports **email**, **phone**, and **name** fields in your contact record for validation.

* **Email Verification** - Classifies addresses as Valid, Deliverable, Risky, or Invalid. It also flags disposable email providers.
* **Name Validation** - Detects gibberish, random strings (e.g., `asdfgh`), and placeholder values (e.g., `N/A` or `Test`).
* **Phone Number Validation** - Verifies international formats and retrieves metadata, determining line type as Mobile, Fixed, or VoIP, along with carrier, location, and timezone details.

### Reports and Insights

#### Weekly Reporting

A data quality report is generated and delivered every **Monday**. The report summarizes key validation metrics, trends, and data health indicators based on processed contact data.

**Enable or Disable Weekly Reports**

Go to the **Data Pulse Settings** page to enable or disable weekly report delivery.

<figure><img src="https://93738666-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FEXQQW0hsXyH0YD4ePoxb%2Fuploads%2FQcmhbbcZdWNY2f0W3qDY%2Fimage.png?alt=media&amp;token=206b8361-e7ea-474c-9c15-eea4e5fd43af" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
You can opt in or opt out of receiving weekly reports at any time from the [**Settings page**](http://app.clearout.io/settings/data_pulse)**.**
{% endhint %}

#### Analytics Dashboard

A live view of validation trends, allowing teams to see which sources are providing the highest (or lowest) quality data.

The dashboard reveals:

* Patterns in valid, invalid, and risky data
* Common data issues (e.g., increased gibberish names, disposable emails, etc.)
* Trends affecting overall data health

These insights help **monitor and track data quality** over time.


---

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