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

# Get Overall Analytics

> Get account-wide overall statistics for date range with sent, opened, replied metrics

## Path Parameters

<Note>No path parameters</Note>

## Query Parameters

<ParamField query="api_key" type="string" required>
  Your SmartLead API key
</ParamField>

<ParamField query="start_date" type="string" required>
  Start date in YYYY-MM-DD format
</ParamField>

<ParamField query="end_date" type="string" required>
  End date in YYYY-MM-DD format
</ParamField>

<ParamField query="timezone" type="string">
  Timezone string (e.g. "America/New\_York"), optional
</ParamField>

<ParamField query="client_ids" type="string">
  Comma-separated client IDs (optional)
</ParamField>

<ParamField query="campaign_ids" type="string">
  Comma-separated campaign IDs (optional)
</ParamField>

<ParamField query="is_agency" type="string">
  Set to "true" to filter for agency accounts (optional)
</ParamField>

<ParamField query="full_data" type="string">
  Set to "true" to return full data set (optional)
</ParamField>

## Request Body

<Note>No request body required</Note>

<RequestExample>
  ```bash cURL theme={null}
  curl "https://server.smartlead.ai/api/v1/analytics/overall-stats-v2?api_key=YOUR_KEY&start_date=2024-01-01&end_date=2024-01-31&timezone=America%2FNew_York"
  ```

  ```python Python theme={null}
  import requests

  API_KEY = "YOUR_API_KEY"

  response = requests.get(
      "https://server.smartlead.ai/api/v1/analytics/overall-stats-v2",
      params={
          "api_key": API_KEY,
          "start_date": "2024-01-01",
          "end_date": "2024-01-31",
          "timezone": "America/New_York"
      }
  )

  result = response.json()
  print(result)
  ```

  ```javascript JavaScript theme={null}
  const API_KEY = 'YOUR_API_KEY';

  const response = await fetch(
    `https://server.smartlead.ai/api/v1/analytics/overall-stats-v2?api_key=${API_KEY}&start_date=2024-01-01&end_date=2024-01-31&timezone=America%2FNew_York`
  );

  const result = await response.json();
  console.log(result);
  ```
</RequestExample>

## Response Codes

<ResponseField name="200" type="Success">
  Request successful
</ResponseField>

<ResponseField name="400" type="Bad Request">
  Invalid request parameters or malformed request body
</ResponseField>

<ResponseField name="401" type="Unauthorized">
  Invalid or missing API key. Check your authentication.
</ResponseField>

<ResponseField name="404" type="Not Found">
  The requested resource (campaign, lead, email account, etc.) does not exist or you don't have access to it
</ResponseField>

<ResponseField name="422" type="Validation Error">
  Request validation failed. Check parameter types, required fields, and value constraints.
</ResponseField>

<ResponseField name="429" type="Rate Limit Exceeded">
  Too many requests. Please slow down and retry after the rate limit resets.
</ResponseField>

<ResponseField name="500" type="Internal Server Error">
  Server error occurred. Please try again or contact support if the issue persists.
</ResponseField>

<ResponseField name="503" type="Service Unavailable">
  API is temporarily unavailable or under maintenance. Please try again later.
</ResponseField>

<ResponseExample>
  ```json 200 - Success theme={null}
  {
    "success": true,
    "message": "Overall Stats fetched successfully!",
    "data": {
      "overall_stats": {
        "sent": "345805",
        "opened": "0",
        "replied": "1732",
        "bounced": "2015",
        "unique_lead_count": "299503",
        "unique_open_count": "0",
        "positive_replied": 280,
        "open_rate": "0.00%",
        "reply_rate": "0.58%",
        "positive_reply_rate": "16.17%",
        "bounce_rate": "0.67%"
      }
    }
  }
  ```

  ```json 401 - Unauthorized theme={null}
  {
    "message": "Invalid API Key"
  }
  ```

  ```json 404 - Not Found theme={null}
  {
    "error": "Resource not found"
  }
  ```

  ```json 422 - Validation Error theme={null}
  {
    "error": "Invalid parameters provided"
  }
  ```
</ResponseExample>

## How these metrics are calculated

<Note>
  The rules below (inclusive date boundaries, unique vs raw counts, the rate formulas, and how positive replies are counted) are shared across every Global Analytics endpoint. See [How Analytics Metrics Are Calculated](/api-reference/analytics/how-metrics-are-calculated) for the full explanation.
</Note>

The fields in `overall_stats` are not all the same kind of number. Some are raw event counts and some are unique (deduplicated) counts, and this affects how they behave across date ranges.

### Field definitions

<ResponseField name="sent" type="number">
  Total emails sent in the range. Raw event count.
</ResponseField>

<ResponseField name="opened" type="number">
  Total open events in the range. Raw event count (a single lead opening twice counts twice).
</ResponseField>

<ResponseField name="replied" type="number">
  Total reply events in the range. Raw event count.
</ResponseField>

<ResponseField name="bounced" type="number">
  Total bounce events in the range. Raw event count.
</ResponseField>

<ResponseField name="unique_lead_count" type="number">
  Count of **distinct leads** that were sent at least one email in the range, deduplicated per campaign by email address. This is `COUNT(DISTINCT lead)` across the whole range, **not** a sum of per-day values.
</ResponseField>

<ResponseField name="unique_open_count" type="number">
  Count of **distinct leads** that opened at least one email in the range. Like `unique_lead_count`, this is deduplicated across the whole range.
</ResponseField>

<ResponseField name="positive_replied" type="number">
  Count of **distinct leads tagged as positive** (`sentiment_type = 'positive'`) that sent a genuine reply (replied, not ignored, not bounced), attributed to the **date the reply was received**, within the range. Because it's a distinct-lead count deduplicated across the range, it is **not additive** — summing per-day calls over-counts. The lead category is mutable, so re-categorising a lead changes historical counts.
</ResponseField>

### Rates

All rates are computed against the unique counts above, not against raw sends:

| Rate                  | Formula                                                                                                                 |
| --------------------- | ----------------------------------------------------------------------------------------------------------------------- |
| `open_rate`           | `unique_open_count / unique_lead_count`                                                                                 |
| `reply_rate`          | `replied / unique_open_count` (falls back to `unique_lead_count` when open tracking is disabled, e.g. plain-text sends) |
| `positive_reply_rate` | `positive_replied / replied`                                                                                            |
| `bounce_rate`         | `bounced / unique_lead_count`                                                                                           |

<Note>
  `bounce_rate` is reported per unique lead (`bounced / unique_lead_count`), not per email sent. If you need the deliverability-style figure (`bounced / sent`), both `bounced` and `sent` are in the response and you can compute it yourself.
</Note>

### Date range behaviour (important)

`start_date` and `end_date` are **inclusive on both ends** (from `00:00:00` to `23:59:59` in the requested timezone), and they filter on the time the email was **sent**.

Because the unique counts are deduplicated across the entire requested range, **you cannot reconstruct a multi-day range by summing per-day responses**:

* `sent`, `opened`, `replied` and `bounced` are additive — summing three single-day responses equals the 3-day range response.
* `unique_lead_count` and `unique_open_count` are **not** additive. A lead emailed on two different days counts once in a range query, but once in each single-day query — so summing days inflates the unique totals (and every rate derived from them).

For an accurate figure over any period, query that period directly rather than summing individual days.