Salesforce Pardot Import Integration

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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.

The Salesforce Pardot import integration 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.

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 Integration

If your security policy requires IP whitelisting, you must add Treasure Data's IP addresses to your allowlist to ensure a successful connection.

Please find the complete list of static IP addresses, organized by region, at the following link:
https://api-docs.treasuredata.com/en/overview/ip-addresses-integrations-result-workers/

Obtain the Pardot Business Unit ID

Follows steps in the Pardot Export document to obtain the 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

Complete the following table for the connection.

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

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.

Data Preview

You can see a preview of your data before running the import by selecting Generate Preview. Data preview is optional and you can safely skip to the next page of the dialog if you choose to.

1. Select Next. The Data Preview page opens.
2. If you want to preview your data, select Generate Preview.
3. Verify the data.

Data Placement

For data placement, select the target database and table where you want your data placed and indicate how often the import should run.

1. Select Next. Under Storage, you will create a new or select an existing database and create a new or select an existing table for where you want to place the imported data.

2. Select a Database > Select an existing or Create New Database.

3. Optionally, type a database name.

4. Select a Table> Select an existing or Create New Table.

5. Optionally, type a table name.

6. 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.

7. 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.

8. Select the Timezone for your data storage.

9. Under Schedule, you can choose when and how often you want to run this query.

Run once

1. Select Off.
2. Select Scheduling Timezone.
3. Select Create & Run Now.

Repeat Regularly

1. Select On.
2. Select the Schedule. The UI provides these four options: @hourly, @daily and @monthly or custom cron.
3. You can also select Delay Transfer and add a delay of execution time.
4. Select Scheduling Timezone.
5. Select Create & Run Now.

After your transfer has run, you can see the results of your transfer in 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

You can use an existing source to set up your workflow. You can use the Treasure Data Connected app if you don't have permission to create your custom Connected app.

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 Yaml file

You have full control of the config with Yaml config file.

1. Identify your Yaml file. If you need to create the Yaml 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.

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)

The following is an AWS example to prepare a seed.yml file. Replace the code with the correct code for your product.

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

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

Scheduling Executions

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.

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.