--- title: "Zendesk Sell" slug: "zendesk-sell" description: "Securely get all available metrics and attributes from Zendesk Sell with Dataddo's connector. Easily create a data source and sync your data with our guide." updated: 2026-07-09T08:42:20Z published: 2026-07-09T08:42:20Z canonical: "docs.dataddo.com/zendesk-sell" --- > ## Documentation Index > Fetch the complete documentation index at: https://docs.dataddo.com/llms.txt > Use this file to discover all available pages before exploring further. # Zendesk Sell **Zendesk Sell**, once known as **Base CRM**, is a sales automation and customer relationship management (CRM) platform. It gives you tools to manage leads, contacts, deals, and tasks. This helps sales teams work faster. It also makes customer relationships easier to handle. Refer to our website for [the list of metrics and attributes available in Dataddo](https://www.dataddo.com/connector/zendesk_sell). Refer to Zendesk's official documentation to see [all available endpoints from the Zendesk API](https://developer.zendesk.com/api-reference/sales-crm/introduction/). ## Authorize Connection to Zendesk Sell To authorize this service, use **OAuth 2.0** to share specific data with Dataddo while keeping usernames, passwords, and other information private. 1. On the **Authorizers** page, click on [Authorize New Service](https://app.dataddo.com/service/new) and select your service. 2. Follow the on-screen prompts to grant Dataddo the necessary permissions to **access and retrieve** your data. 3. **[Optional]** Once your ***authorizer*** is created, click on it to **change the label** for easier identification. Ensure that the account you're granting access to holds at least **admin-level permissions**. If necessary, assign a team member with the required permissions with the [authorizer role](https://docs.dataddo.com/docs/user-roles#authorizer) to authenticate the service for you. For more information, see our article on [***authorizers***](https://docs.dataddo.com/docs/authorized-services). ## Data Coverage Zendesk Sell exposes the following datasets. Each dataset maps to a table you can extract. The example fields are just a sample. Each dataset returns more columns. | Dataset | Description | Example fields | Date range | | --- | --- | --- | --- | | Account | Retrieve a list of accounts | ID, Created At, Currency, Name, Phone, Subdomain (+3 more) | No | | Address | Retrieve a list of addresses | City, Country, Line1, Postal Code, State | No | | Associated Contacts | Retrieve a list of associated contacts | Contact ID, Created_At, Deal ID, Deal Name, Role, Updated At | No | | Call Outcomes | Retrieve a list of call outcomes | ID, Created At, Creator ID, Name, Updated At | No | | Calls | Retrieve a list of calls | ID, Associated Deal IDs, Created At, Duration, Incoming, Made At (+8 more) | No | | Collaborations | Retrieve a list of collaborations | ID, Collaborator ID, Created At, Creator ID, Resource ID, Resource Type (+1 more) | No | | Contacts | Retrieve a list of contacts | ID, Address City, Address Country, Address Line1, Address Postal Code, Address State (+35 more) | No | | Custom Fields | Retrieve a list of custom fields | ID, Choices ID, Choices Name, Created At, For Company, For Contact (+3 more) | No | | Deal Sources | Retrieve a list of deal sources | ID, Created At, Creator ID, Name, Resource Type, Updated At | No | | Deal Unqualified Reasons | Retrieve a list of deal unqualified reasons | ID, Created At, Creator ID, Name, Updated At | No | | Deals | Retrieve a list of deals | Id, Added At, Contact Id, Created At, Creator Id, Currency (+17 more) | No | | Documents | Retrieve a list of documents | ID, Content Type, Created At, Creator ID, Download URL, Name (+4 more) | No | | Lead Conversions | Retrieve a list of lead conversions | ID, Created At, Deal ID, Individual ID, Lead ID, Organization ID | No | | Lead sources | Retrieve a list of lead sources | ID, Created At, Creator ID, Deal ID, Name, Resource Type (+1 more) | No | | Lead Unqualified Reasons | Retrieve a list of lead unqualified reasons | ID, Created At, Creator ID, Name, Updated At | No | | Leads | Retrieve a list of Leads | ID, Address City, Address Country, Address Line1, Address Postal Code, Address State (+23 more) | No | | Line Items | Retrieve a list of line items | ID, Created At, Currency, Deal ID, Description, Name (+8 more) | No | | Loss Reasons | Retrieve a list of loss reasons | ID, Created At, Creator ID, Name, Updated At | No | | Notes | Retrieve a list of notes | ID, Content, Created At, Creator ID, Is Important, Resource ID (+4 more) | No | | Orders | Retrieve a list of orders | ID, Created At, Deal ID, Discount, Updated At | No | | Pipelines | Retrieve a list of pipelines | Id, Created At, Disabled, Name, Updated At | No | | Products | Retrieve a list of products | Id, Active, Cost, Cost Currency, Created At, Description (+7 more) | No | | Sequence Enrollments | Retrieve a list of sequence enrollments | Id, Actor Id, Created At, Current Step Position, Step Action Estimated Executed At, Step Action Executed At (+25 more) | No | | Sequences | Retrieve a list of sequences | Id, Created At, Creator Id, Name, Email Template Id, Email Is Reply (+8 more) | No | | Stages | Retrieve a list of stages | Id, Active, Category, Created At, Likelihood, Name (+3 more) | No | | Tags | Retrieve a list of tags | Id, Created At, Creator Id, Name, Resource Type, Updated At | No | | Tasks | Retrieve a list of tasks | Id, Completed, Completed At, Content, Created At, Creator Id (+7 more) | No | | Text Messages | Retrieve a list of text messages | Id, Associated Deal Ids, Content, Created At, Incoming, Resource Id (+6 more) | No | | Users | Retrieve a list of users | ID, Confirmed, Created At, Deleted At, Email, Group Id (+14 more) | No | | Visit Outcomes | Retrieve a list of visit outcomes | ID, Created At, Name, Updated At | No | | Visits | Retrieve a list of visits | ID, Created At, Creator ID, Outcome ID, Sales Representative's Verification Status, Resource Address (+5 more) | No | ## How Data Extraction Works None of this connector's datasets use a date range. Every run pulls all currently available data. ## Metadata Columns When you create a source, you can add these Dataddo metadata columns to the extracted data: - **dataddo_hash** - a fingerprint built from each record's key fields. It works as a natural key, so it is ideal for upserts (updating existing rows in your destination instead of creating duplicates). - **dataddo_extraction_timestamp** - the date and time the row was extracted. Use it to track how records change over time, for example to build slowly changing dimensions. ## How to Create a Zendesk Sell Data Source Creating a data source takes you through six steps, shown in the progress bar at the top of the wizard. Each step is explained below. **1. Pick the connector** On the **Sources** page, click **Create Source**, then select the connector from the catalog. Use the search bar or the category tabs if you do not see it right away. You can rename the source at any time using the pencil icon next to its name. **2. Select the dataset** A dataset defines the shape of your data: which fields you get and how they relate. Select the dataset you want; you can still fine-tune the exact fields later. - Each dataset has a short description of what it contains. Use the search box to find a dataset, attribute, or metric by name. - The panel on the right previews the selected dataset's fields. For each field you can see its **data type**, whether it holds **sensitive** data (personal fields such as name or email are flagged), and which **other datasets it links to**, so you can see how the datasets relate. **3. Choose the account** This step selects what Dataddo reads from. - **Authorizer:** Select an account you have already authorized from the drop-down. If you have none yet, choose **Add new account** and follow the prompts. If no authorizer is selected, Dataddo asks you to authorize before you continue. - **What to extract from:** Select the exact entity you want to pull data from. Depending on the service this may be labelled an account, property, profile, workspace, or similar, sometimes with a sub-level to choose as well. - **Multiple accounts:** To pull the same data from every entity you can access, turn on **Automatically collect data from all ...**. This is multi-account extraction. Leave it off to choose them by hand. **4. Refine the attributes and metrics** The dataset already sets the structure. Here you fine-tune it: tick or untick the specific attributes and metrics you want to keep, and use the search box to find a field quickly. Click **Test on Sample Data** at any point to preview the result before you continue. **5. Add metadata columns (optional)** Two optional columns help your destination handle the data. - **Dataddo Hash (Include Row Hash):** a fingerprint built from the columns you pick. It works as a natural key, so your destination can deduplicate rows and run upserts instead of creating duplicates. Turn it on, then select the columns that uniquely identify a row. - **Dataddo Extraction Timestamp:** the time each row was extracted. Use it to watermark the data, for example to build slowly changing dimensions or to track when a value last changed. **6. Set the schedule** Decide how often Dataddo runs the extraction. - **Frequency:** how often the pipeline runs, for example daily. Click **Show advanced settings** to also set the exact hour and minute (UTC). - **Date range:** the relative window each run extracts, for example "Yesterday". The window moves forward on every run. - **Historical data:** a new source starts from the current window. To load older data, run a [full data re-sync](https://docs.dataddo.com/docs/data-backfilling) after the source is created. - **Allow Empty Data Extractions:** when on, a run that returns no data records zero rows instead of failing. Turn it on if the source can legitimately have periods with no data. Click **Save**. Your data source is ready. ## Troubleshooting ### Data Preview Unavailable No data preview when you click on **Test Data** might be caused by an issue with your ***source*** configuration. The most common causes are: - **Date range**: Try a smaller date range. You can load the rest of your data afterward via [manual data load](https://docs.dataddo.com/docs/data-backfilling). - **Insufficient permissions**: Please make sure your authorized account has at least admin-level permissions. ## Related Articles Now that you have successfully created a ***data source***, see how you can connect your data to a dashboarding app or a data storage. **Sending Data to Dashboarding Apps** - [Simple Data Integration to Dashboards](https://docs.dataddo.com/docs/simple-data-integration-to-dashboards) - [Data Backfilling to Dashboarding Apps](https://docs.dataddo.com/docs/data-backfilling-to-dashboarding-apps) **Sending Data to Data Storages** - [Batch Ingestion to Data Warehouses](https://docs.dataddo.com/docs/ingestion-to-data-warehouses) - [Data Backfilling to Storages](https://docs.dataddo.com/docs/data-backfilling-to-storages) **Other Resources** - [Troubleshooting](https://docs.dataddo.com/docs/troubleshooting) - [Extraction Logs](https://docs.dataddo.com/docs/extraction-logs) - [Data Duplication](https://docs.dataddo.com/docs/data-duplication)