--- title: "RD Station Marketing" slug: "rd-station-marketing" description: "Connect RD Station Marketing to Dataddo and sync its data to any dashboard, database, or data warehouse. No coding required." updated: 2026-07-09T08:35:39Z published: 2026-07-09T08:35:39Z canonical: "docs.dataddo.com/rd-station-marketing" --- > ## 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. # RD Station Marketing **RD Station Marketing** is an all-in-one marketing automation platform, popular in Brazil and Latin America. Businesses use it to manage their inbound marketing funnel. It includes email marketing, landing pages, social media, lead scoring, and analytics. Refer to our website for [the list of metrics and attributes available in Dataddo](https://dataddo.com/connector/rd_station_marketing). Refer to RD Station Marketing's official documentation to see [all available endpoints from the XXX API](https://developers.rdstation.com/reference/welcome). ## Authorize Connection to RD Station Marketing 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 RD Station Marketing exposes the following datasets. Each dataset maps to a table you can extract. Example fields are a representative sample; each dataset returns more columns. | Dataset | Description | Example fields | Date range | | --- | --- | --- | --- | | Contact Associated Events | Returns a list of events associated with the contact. | Uuid, Created At, Email, Event Family, Event Identifier, Event Timestamp (+3 more) | No | | Contact Funnels | Returns list of funnels associated with the contact. | Uuid, Contact Owner Email, Created At, Email, Fit, Interest (+4 more) | No | | Contacts from Segmentation | Returns list of contacts associated with the segmentations. | Uuid, Segmentation Id, Bio, Birthdate, City, Country (+16 more) | No | | Conversion Asset Statistics | The purpose of this API is to provide conversion indicators for marketing assets, in order to bring more clarity regarding the performance of your asset. | Asset ID, Asset Updated At, Account ID, Asset Created At, Asset Identifier, Assets Type (+5 more) | Yes | | Custom Fields | Returns a data with all the custom fields in the account. | UUID, API Identifier, Custom Field, Default Label, Label (en-UD), Label (en-US) (+12 more) | No | | Email Statistics | Returns analytics of emails. | Campaign ID, Send At, Account ID, Campaign Name, Contacts Count, Email Bounced Count (+12 more) | Yes | | Email Statistics Through Automated Workflow | Returns the engagement and performance indicators of emails sent through automation flows during the requested period | Workflow ID, Account ID, Contacts Count, Count Processed, Created At, Email Bounced Unique Count (+16 more) | Yes | | Emails | Returns a list with all the emails in the account. | ID, Updated At, Account ID, Campaign ID, Component Template Id, Created At (+12 more) | Yes | | Events From Segmentation | Returns list of events associated with the segmentations. | Uuid, Created At, Email, Event Family, Event Identifier, Event Timestamp (+9 more) | No | | Sales Funnel Statistics | Returns analytics of Sales Funnel. | Reference Day, Account ID, Contacts Count, Opportunities Count, Qualified Contacts Count, Reporting End Date (+4 more) | Yes | | Segmentation lists | Returns a list of account segmentations. | ID, Created At, Name, Process status, Standard, Updated At | No | ## How Data Extraction Works What each extraction pulls depends only on whether a dataset supports a date range (see the Date range column above): - **Date range supported (Yes):** the source reads a relative window (for example "last 7 days"), and that window slides forward with the current date. Every run re-reads the window, so a range of "1 day ago" always pulls the previous day (D-1). Each run replaces the window's data rather than adding older history. To load records from before the window, run a full data re-sync with a wider range. See [Data Backfilling](/docs/data-backfilling). - **No date range (No):** every run pulls all currently available data. Set the relative date range when you create the source. ## 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 RD Station Marketing 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. ### Metric and Ad Recall Data Don't Match The **Reach** and **Recall** metrics cannot be summed to get the totals for longer time periods. As these metrics measure the **daily unique users** who view your ad (= reach) or will remember the ad (=ad recall), it is **not possible to get data for a specific time period and/or aggregate the data**. To avoid this, you can 1. Get **daily** breakdowns: The daily values will match, but not when summed up over a longer time period. 2. Extract data **weekly or monthly**: These weekly/monthly values will match. Simply create a **new source** and a **new flow** with the particular breakdown (for example, a source and a flow with daily breakdowns/synchronizations). Read more about the metrics, and why the data may not be matching [here](https://blog.dataddo.com/why-the-numbers-in-your-bi-tool-dont-always-match-your-source-data?_gl=1*ipsbl8*_ga*MjAwMjE2NTU4NC4xNjUxNzM0NTI4*_ga_NQ4TN4KP4V*MTY1MTc2NzQwMC40LjEuMTY1MTc2Nzg4OS4z). ## 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)