> 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/faqs.md).

# FAQs

## Frequently Asked Questions

### General Questions

<details>

<summary>What does Data Pulse validate?</summary>

Data Pulse validates key contact data such as email addresses, phone numbers, and names. It checks for correctness, deliverability, formatting, and classification (e.g., valid, invalid, risky).

</details>

<details>

<summary>What problem does Data Pulse solve?</summary>

Data Pulse solves the problem of data degradation in your CRM by continuously validating and monitoring contact data after it is created. It ensures emails, phone numbers, and names remain accurate, standardized, and usable, while providing clear visibility into data quality, trends, and issues - without requiring manual effort or multiple tools.

</details>

<details>

<summary>Does Data Pulse update data back to the source?</summary>

Yes, validated and standardized data is written back to the source, ensuring your system always reflects the latest and most accurate information.

</details>

<details>

<summary>What is the frequency at which reports are sent by Data Pulse?</summary>

Data Pulse sends reports weekly, every Monday, based on the user's configured time zone.

</details>

<details>

<summary>Can I opt out of reports?</summary>

Yes. You can opt out at any time by disabling reports from the **Data Pulse Settings** page.

</details>

<details>

<summary>How is "Cost Saved" calculated?</summary>

Cost saved is an estimate of the value Data Pulse delivered by catching bad data before it does damage, not money billed, refunded, or transferred. It's a directional figure, calculated based on your activity.

{% code title="The formula" expandable="true" %}

```
Cost saved = ($2 × bad fields caught) + ($0.01 × contacts monitored)
```

{% endcode %}

* Why is each bad field worth $2?\
  A "bad field" is any invalid email, name, or phone, plus valid-but-disposable emails and valid-but-gibberish names.

  Left live in your CRM, each one quietly costs you downstream: a hard bounce that erodes your sender reputation, an SDR's time wasted dialing a dead number, budget spent emailing or advertising to someone who doesn't exist, and the deliverability hit that drags down your next campaign too.

  We anchor the $2 to the 1-10-100 rule, a *data-quality framework first published by Labovitz and Chang in 1992*: roughly $1 to prevent a bad record at entry, $10 to fix it later, and $100 if it's left unchecked. Data Pulse works at the prevention end—catching bad fields on arrival—so we price each catch at a conservative $2, near that prevention floor and far below the $10–$100 a bad record costs once it has spread through your campaigns, reports, and outreach.
* Why $0.01 per monitored contact?\
  Beyond catching bad data, Data Pulse keeps every contact under continuous watch so decay is caught as it happens rather than discovered in a future bulk clean-up.

  We value that ongoing monitoring at a fraction of a cent per contact.

{% code title="Example" expandable="true" %}

```
For an account with 50 bad fields caught and 47 contacts monitored:
($2 × 50) + ($0.01 × 47) = $100 + $0.47 = $100.47
```

{% endcode %}

* What this number is not:\
  The $2 and $0.01 rates are Clearout's assumptions, informed by the framework above but not a guaranteed return.

  Your actual savings depend on your send volume, how you use these contacts, and your cost of a bounce or bad call.

  We chose conservative, round rates so the estimate stays easy to audit — you can recompute it yourself from the formula at any time.

</details>

### Connections & Accounts

<details>

<summary>How many HubSpot accounts can I connect to one Clearout account?</summary>

There is no limit to the number of HubSpot accounts you can connect to a single Clearout account. You can connect and manage multiple accounts without any restrictions.

</details>

<details>

<summary>Can real-time Data Pulse be active for a HubSpot account on multiple Clearout accounts?</summary>

No. At any given time, real-time Data Pulse can only be active on one Clearout account per HubSpot account.

</details>

<details>

<summary>How do I validate my existing data in HubSpot CRM before connecting Data Pulse?</summary>

To validate data already in your HubSpot CRM, use Clearout's native integrations:

* Use **Clearout Email Verification** to validate email addresses
* Use **Clearout Phone Validation** to validate phone numbers

Once validated, the results can be synced back to HubSpot, ensuring your existing data is clean and standardized before enabling Data Pulse.

</details>

### Credits & Billing

<details>

<summary>How many credits are charged for data validation and verification?</summary>

2 credits are charged per validation. This applies to all validated fields including name, email, and phone.

</details>

<details>

<summary>Will credits be charged if verification fails?</summary>

No. Credits are not charged if the verification fails or returns an unknown status.

</details>

<details>

<summary>What happens if my credits are exhausted?</summary>

Once your credits are exhausted, the system stops accepting any new requests from the data source. All existing requests in the queue will fail with an error. An email notification is also sent to the account owner informing them that Data Pulse has been disabled.

</details>

<details>

<summary>Can real-time Data Pulse re-enable itself after credits are exhausted?</summary>

Yes. If Data Pulse was disabled due to exhausted credits, it will automatically re-enable once credits are replenished. The Clearout account owner will be notified when Data Pulse is reactivated.

</details>

<details>

<summary>How can I verify data left unprocessed due to exhausted credits?</summary>

You can use **Bulk Email Verification** and **Bulk Phone Validation** to process any remaining data. Once completed, export the results and update them back to your data source.

</details>


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