Salesforce Pardot B2B is a marketing automation tool by Salesforce designed for organizations that primarily focus on business-to-business (B2B) sales and marketing automation. This email marketing system offers automated support for the longer timespan and multi-step decisions associated with B2B sales and helps marketers create more leads, generate more pipelines, and empower sales to close more deals.
This Data Connector is in Beta. For more information, contact support@treasuredata.com.
The Salesforce Pardot input connector automates the end-to-end solution for our customers, which is ingesting data from Pardot into the Treasure Data database and activating a custom segment back to Pardot.
This topic includes:
Prerequisites
Basic Knowledge of Treasure Data.
Basic knowledge of Salesforce Pardot.
- A working Salesforce Pardot account.
Your Business Unit ID.
- You have the ability to create your own Salesforce Pardot connected app, or you have permission to grant access to the Treasure Data app to access your Pardot data.
Requirements and Limitations
- The imported values for timestamp columns are saved as string types in the Treasure Data database; the timezone is not available.
- Use Export API for importing large amounts of data and does not support incremental loading.
Static IP Address of Treasure Data
The static IP address of Treasure Data is the access point and source of the linkage for this Integration. To determine the static IP address, contact your Customer Success representative or Technical support.
Follows steps in the Pardot Export document to obtain the Business Unit ID.Obtain the Pardot Business Unit ID
Import from Salesforce Pardot via TD Console
Create Authentication
Follows steps in the Salesforce Pardot Export document to create an authentication.
Create a Source
1. Open TD Console.
2. Navigate to Integrations Hub > Authentications.
3. Locate your new authentication and select New Source.
Create a Connection
Parameter | Description |
---|---|
Data Transfer Name | You can define the name of your transfer. |
Authentication | The authentication name that is used for a transfer. |
1. Type a source name in the Data Transfer Name field.
2. Select Next.
The Create Source page displays with the Source Table tab selected.
Identify a Source Table
Parameter | Description |
---|---|
Data Object | Pardot Object to import supported objects:
|
Deleted? | Request Objects that were deleted. If you use Export API it is Prospects deleted if filter by PROSPECT_UPDATED_AT |
Use Export API | Use Export API to import data. When you have a large number of data to import, Export API is more efficient. Additionally, Export API can help you avoid meeting the API rate limit to your account. |
Filter by | Filter the data by CREATED_AT, UPDATE_AT, or PROSPECT_UPDATED_AT. The PROSPECT_UPDATED_AT is supported by PROSPECT_ACCOUNT and VISITOR Data Object in Export API mode only. |
Visitor IDs | Comma-separated Visitor IDs (no spaces). This field available for Visit Object only |
Prospect IDs | Comma-separated Prospect IDs (no spaces). This field available for Visit Object only |
Start Time | Import data since this start time. The format must match: "yyyy-MM-dd HH:mm:ss". If not specified, data will be imported for one year to the specified End Time for Export API mode. |
End Time | Import data to this time. The format must match: "yyyy-MM-dd HH:mm:ss". If not specified, data will be imported for one year from the specified Start Time for Export API mode. |
Incremental Loading | Only import new data from the last import. This option is not available when Export API mode is used. |
Select Next.
Config the Data Settings
The Data Settings allows you to fine-tune the HTTP request to Salesforce Pardot. Update your designed config settings and select Next.
Parameter | Description |
---|---|
Extra Columns (Optional): | Comma-separated list of columns name. If API response contains data, it saves the column as string. This field allows you import data for columns that's not specified in Pardot document, but the data is present when requested. |
Max retry count per API call: | Max retry count per API call |
Initial retry interval per API call: | Initial retry interval per API call in seconds |
Max retry interval per API call: | Max retry interval per API call in seconds |
HTTP Connection Timeout: | Set the HTTP connection timeout in seconds |
Preview Your Data
You can see a preview of your data before running the import. The data that displays in the data preview is approximated from your source and no filter is applied. It is not the actual data that is imported.
- Select Next.
Data preview is optional; skip to the next page of the dialog if you want. - To preview your data, select Generate Preview. Optionally, select Next.
- Verify that the data meets your expectations.
- Select Next.
Define Your Data Placement
Select the target database and table where you want your data placed, and then indicate how often the import should run.
- Select Data Placement.
- Select a Database > Select an existing or Create New Database. Optionally, enter a database name.
- Select a Table> Select an existing or Create New Table. Optionally, type a table name.
- Choose the method for importing the data.
- Append (default): Data import results are appended to the table.
If the table does not exist, it will be created. - Always Replace: Replaces the entire content of an existing table with the result output of the query. If the table does not exist, a new table is created.
- Replace on New Data: Only replace the entire content of an existing table with the result output when there is new data.
- Append (default): Data import results are appended to the table.
- Select the Timestamp-based Partition Key column.
If you want to set a different partition key seed than the default key, you can specify the long or timestamp column as the partitioning time. As a default time column, it uses upload_time with the add_time filter. - Select the Timezone for your data storage.
- Choose when and how often you want to run this query:
- Run once:
- Select Off.
- Select Scheduling Timezone.
- Select Create & Run Now.
- Repeat the query:
- Select On.
- Select the Schedule. The UI provides these four options: @hourly, @daily, and @monthly or custom cron.
- You can also select Delay Transfer and add a delay of execution time.
- Select Scheduling Timezone.
- Select Create & Run Now.
- Run once:
To see the results of your transfer, go to Data Workbench > Databases.
Import from Salesforce Pardot via Workflow
You can import data from Salesforce Pardot by using td_load>: operator of workflow. If you have already created a SOURCE, you can run it; if you don't want to create a SOURCE, you can import it using a yml file.
Using a Source or YML File
Data Type | Pros | Cons |
---|---|---|
Source |
|
|
yml file |
|
|
Using a Source
1. Identify your source.
2. To obtain a unique ID, open the Source list and then filter by Salesforce Pardot.
3. Open the menu and select Copy Unique ID.
4. Define a workflow task using td_load> operator.
+load: td_load>: unique_id_of_your_source database: ${td.dest_db} Table: ${td.dest_table}
5. Run a workflow.
Using a yml file
1. Identify your yml file. If you need to create the yml file, review Amazon S3 Import Integration Using CLI as a reference.
2. Define a workflow task using td_load> operator.
+load: td_load>: config/daily_load.yml database: ${td.dest_db} Table: ${td.dest_table}
3. Run a workflow.
Parameters Reference
See the CLI Parameter Reference.
Sample Workflow Code
Visit Treasure Boxes for sample workflow code.
Import from Salesforce Pardotvia CLI (Toolbelt)
Before setting up the connector, install the most current TD Toolbelt.
Create Configuration File (load.yml)
in: type: salesforce_pardot client_id: xxxx client_secret: yyyy refresh_token: zzzz data_object: prospect business_unit: 0Uv4W00000111111 filter_by: 'created_at' incremental: true # use_export_api: true start_time: "2020-12-13 03:20:00" end_time: "2021-12-20 03:30:00" out: mode: append
Parameters Reference
Name | Description | Value | Default Value | Required |
---|---|---|---|---|
type | The connector type. | salesforce_pardot | yes | |
client_id | The connected app consumer key. | yes | ||
client_secret | The connected app consumer secret. | yes | ||
refresh_token | The refresh token after completing the steps described in Using Your Custom Connected App. | yes | ||
business_unit | Your Salesforce Pardot Business unit. See Obtain the Pardot Business Unit ID. | yes | ||
data_object | Pardot Object to import, supported objects:
| yes | ||
use_export_api | Use Export API to import data. When you have a large number of data to import, Export API is more efficient. | false | no | |
deleted | Request Objects that were deleted. If you use Export API it is Prospects deleted if filter by PROSPECT_UPDATED_AT | no specified | ||
filter_by | Filter the data by CREATED_AT, UPDATE_AT, or PROSPECT_UPDATED_AT. Note, the PROSPECT_UPDATED_AT is supported by PROSPECT_ACCOUNT and VISITOR Data Object in Export API mode only. | no | ||
start_time | Import data since this time, the format must match: "yyyy-MM-dd HH:mm:ss". If not specified, data will be imported for one year to the specified End Time for Export API mode. | no | ||
end_time | Import data to this time, the format must match: "yyyy-MM-dd HH:mm:ss". If not specified, data will be imported for one year from the specified Start Time for Export API mode. | no | ||
visitor_ids | Comma-separated Visitor IDs (no spaces). This field available for Visit Object only | no | ||
prospect_ids | Comma-separated Prospect IDs (no spaces). This field available for Visit Object only | no | ||
incremental | Only import new data from the last import. This option is not available when Export API mode is used. | false | no | |
extra_columns | Comma-separated list of columns name. If API response contains data, it saves the column as string. This field allows you import data for columns that's not specified in Pardot document, but the data is present when requested. | |||
maximum_retries | The maximum number of retries when the request failed. | 8 | no | |
initial_retry_wait | The initial amount of time before the first retry in seconds. | 120 | no | |
maximum_retry_wait | The maximum amount of time to wait for a retry in seconds. | 300 | no | |
connection_timeout | The HTTP connection time out for a request to Pardot in seconds. | 300 | no |
To preview the data, use the td connector:preview command.
$ td connector:preview load.yml +-------+---------+----------+---------------------+ | id | company | customer | created_at | +-------+---------+----------+---------------------+ | 11200 | AA Inc. | David | 2015-03-31 06:12:37 | | 20313 | BB Imc. | Tom | 2015-04-01 01:00:07 | | 32132 | CC Inc. | Fernando | 2015-04-01 10:33:41 | | 40133 | DD Inc. | Cesar | 2015-04-02 05:12:32 | | 93133 | EE Inc. | Jake | 2015-04-02 14:11:13 | +-------+---------+----------+---------------------+
Execute Load Job
Submit the load job.
It might take a couple of hours depending on the size of the data. Be sure to specify the Treasure Data database and table where the data should be stored.
Treasure Data also recommends specifying --time-column option because Treasure Data’s storage is partitioned by time (see data partitioning). If this option is not provided, the data connector chooses the first long or timestamp column as the partitioning time. The type of the column specified by --time-column must be either of long and timestamp type.
If your data doesn’t have a time column, you can add a time column by using add_time filter option. For more details see add_time filter plugin.
$ td connector:issue load.yml --database td_sample_db --table td_sample_table \ --time-column created_at
The connector:issue command assumes that you have already created a database(td_sample_db)and a table(td_sample_table). If the database or the table does not exist in TD, this command fails. Create the database and table manually or use --auto-create-table option with td connector:issue command to auto-create the database and table.
$ td connector:issue load.yml --database td_sample_db --table td_sample_table --time-column created_at --auto-create-table
The data connector does not sort records on the server-side. To use time-based partitioning effectively, sort records in files beforehand.
If you have a field called time, you don’t have to specify the --time-column option.
$ td connector:issue load.yml --database td_sample_db --table td_sample_table
Import Modes
You can specify file import mode in the out section of the load.yml file. The out: section controls how data is imported into a Treasure Data table. For example, you may choose to append data or replace data in an existing table in Treasure Data.
Mode | Description | Examples |
---|---|---|
Append | Records are appended to the target table. | in: ... out: mode: append |
Always Replace | Replaces data in the target table. Any manual schema changes made to the target table remain intact. | in: ... out: mode: replace |
Replace on new data | Replaces data in the target table only when there is new data to import. | in: ... out: mode: replace_on_new_data |
Scheduling Executions
Create a Schedule Using the TD Toolbelt
A new schedule can be created using the td connector:create command.
$ td connector:create daily_import "10 0 * * *" \ td_sample_db td_sample_table load.yml
Treasure Data also recommends that you specify the --time-column option, because Treasure Data’s storage is partitioned by time (see also data partitioning).
$ td connector:create daily_import "10 0 * * *" \ td_sample_db td_sample_table load.yml \ --time-column created_at
The `cron` parameter also accepts three special options: `@hourly`, `@daily`, and `@monthly`.
By default, the schedule is set up in the UTC timezone. You can set the schedule in a timezone using -t or --timezone option. `--timezone` option supports only extended timezone formats like 'Asia/Tokyo', 'America/Los_Angeles', etc.
Timezone abbreviations like PST, CST are not supported and might lead to unexpected schedules.
List All Schedules
You can see the list of currently scheduled entries by running the command td connector:list.
$ td connector:list +--------------+--------------+----------+-------+--------------+-----------------+------------------------- ------+ | Name | Cron | Timezone | Delay | Database | Table | Config | +--------------+--------------+----------+-------+--------------+-----------------+--------------------------------+ | daily_import | 10 0 * * * | UTC | 0 | td_sample_db | td_sample_table | {"in"=>{"type"=>"..","acces... | +--------------+--------------+----------+-------+--------------+-----------------+--------------------------------+
Show Schedule Settings and History
td connector:show shows the execution setting of a schedule entry.
% td connector:show daily_import Name : daily_import Cron : 10 0 * * * Timezone : UTC Delay : 0 Database : td_sample_db Table : td_sample_table Config --- in: type: salesforce_pardot client_id: xxxx client_secret: yyyy refresh_token: zzzz data_object: prospect business_unit: 0Uv4W00000111111 filter_by: 'created_at' incremental: true ...
td connector:history shows the execution history of a scheduled entry. To investigate the results of each individual run, use td job <jobid>.
% td connector:history daily_import +--------+---------+---------+--------------+-----------------+----------+---------------------------+----------+ | JobID | Status | Records | Database | Table | Priority | Started | Duration | +--------+---------+---------+--------------+-----------------+----------+---------------------------+----------+ | 578066 | success | 10000 | td_sample_db | td_sample_table | 0 | 2015-04-18 00:10:05 +0000 | 160 | | 577968 | success | 10000 | td_sample_db | td_sample_table | 0 | 2015-04-17 00:10:07 +0000 | 161 | | 577914 | success | 10000 | td_sample_db | td_sample_table | 0 | 2015-04-16 00:10:03 +0000 | 152 | | 577872 | success | 10000 | td_sample_db | td_sample_table | 0 | 2015-04-15 00:10:04 +0000 | 163 | | 577810 | success | 10000 | td_sample_db | td_sample_table | 0 | 2015-04-14 00:10:04 +0000 | 164 | | 577766 | success | 10000 | td_sample_db | td_sample_table | 0 | 2015-04-13 00:10:04 +0000 | 155 | | 577710 | success | 10000 | td_sample_db | td_sample_table | 0 | 2015-04-12 00:10:05 +0000 | 156 | | 577610 | success | 10000 | td_sample_db | td_sample_table | 0 | 2015-04-11 00:10:04 +0000 | 157 | +--------+---------+---------+--------------+-----------------+----------+---------------------------+----------+ 8 rows in set
Delete Schedule
td connector:delete removes the schedule.
$ td connector:delete daily_import
FAQs for the Salesforce Pardot Integration
How can I schedule an incremental import for a large data set?
As recommended, when importing a large dataset from Pardot you should use the Export API. However, export API doesn't support incremental import. To solve this issue:
- Use Export API to import to a recent date. For example, today by specifying the Filter By and End Time will import all data to the End Time value.
- Modify the job config, uncheck the Use Export API checkbox, set the Start Time equals the End Time from the previous execution, and set enable the Incremental Loading.