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SurveyMonkey

SurveyMonkey

Marketing Analytics

Sync SurveyMonkey data anywhere.

Survey Monkey uses the power of the web to enable individuals and companies to reach unprecedented numbers of respondents to gain insights into almost anything. An experience management company, Momentive Inc. (formerly SurveyMonkey Inc.) uses a cloud-based software to provide service solutions for businesses and individuals needing brand or market insights, information regarding consumers’ product experiences, employee and customer experiences—information of any kind for which surveys can provide useful information to improve products, events, experiences.

  • Standard
  • Generally available
Sync SurveyMonkey dataRead the docs
  • 50+Destinations
One connector

Everything SurveyMonkey can do in Airbyte

  • Sync to your warehouse

    Land SurveyMonkey data in 50+ destinations on a schedule you control.

  • Cloud or self-hosted

    Run the SurveyMonkey connector on Cloud, Self-Managed Enterprise.

Sync capabilities

  • Available onCloud, Self-Managed Enterprise
  • Destinations50+ Airbyte connectors
  • Connector version0.3.48

Set up in 10 steps

  1. First, navigate to the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.
  2. Click on the "Add Source" button in the top right corner of the screen.
  3. Select "SurveyMonkey" from the list of available sources.
  4. Enter a name for your SurveyMonkey source connector.
  5. Enter your SurveyMonkey API token in the "API Token" field. You can find your API token by logging into your SurveyMonkey account and navigating to the "My Account" section.
  6. Click on the "Test" button to ensure that your credentials are correct and that Airbyte can connect to your SurveyMonkey account.
  7. Once the test is successful, click on the "Create" button to save your SurveyMonkey source connector.
  8. You can now use your SurveyMonkey source connector to create a new pipeline or add it to an existing pipeline in Airbyte.
  9. To use your SurveyMonkey source connector in a pipeline, simply select it from the list of available sources when creating a new pipeline or editing an existing one.
  10. Follow the prompts to configure your pipeline and start syncing data from your SurveyMonkey account to your destination of choice.
FAQ

Common questions

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What data can you extract from SurveyMonkey?

SurveyMonkey's API provides access to a wide range of data related to surveys and responses. The following are the categories of data that can be accessed through SurveyMonkey's API:

1. Survey data: This includes information about the survey itself, such as the survey title, description, and questions.
2. Response data: This includes information about the responses to the survey, such as the respondent's answers to each question.
3. User data: This includes information about the users who created the survey, such as their name, email address, and account type.
4. Team data: This includes information about the teams that the user belongs to, such as the team name and members.
5. Template data: This includes information about the survey templates available on SurveyMonkey, such as the template name and description.
6. Collector data: This includes information about the collectors used to distribute the survey, such as the collector type and status.
7. Analytic data: This includes information about the survey results, such as the response rate, completion time, and average score.

Overall, SurveyMonkey's API provides access to a comprehensive set of data related to surveys and responses, which can be used to gain insights and make data-driven decisions.

How do I transfer data from SurveyMonkey?

1. First, navigate to the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.
2. Click on the "Add Source" button in the top right corner of the screen.
3. Select "SurveyMonkey" from the list of available sources.
4. Enter a name for your SurveyMonkey source connector.
5. Enter your SurveyMonkey API token in the "API Token" field. You can find your API token by logging into your SurveyMonkey account and navigating to the "My Account" section.
6. Click on the "Test" button to ensure that your credentials are correct and that Airbyte can connect to your SurveyMonkey account.
7. Once the test is successful, click on the "Create" button to save your SurveyMonkey source connector.
8. You can now use your SurveyMonkey source connector to create a new pipeline or add it to an existing pipeline in Airbyte.
9. To use your SurveyMonkey source connector in a pipeline, simply select it from the list of available sources when creating a new pipeline or editing an existing one.
10. Follow the prompts to configure your pipeline and start syncing data from your SurveyMonkey account to your destination of choice.

What are top ETL tools to transfer data from SurveyMonkey?

The most prominent ETL tools to transfer data to include: Airbyte, Fivetran, StitchData, Matillion, Talend Data Integration. These tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into and other databases, data warehouses and data lakes, enhancing data management capabilities.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

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