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Log in to your Delighted account using your browser. Ensure that you have the necessary permissions to access and export the data you require.
Once logged in, go to the survey or data section from which you wish to export responses. This is typically found by selecting the project or survey dashboard you are interested in.
Delighted provides an integrated export feature for downloading data. Look for the 'Export' option in the survey or data section. This is usually represented as a button or link.
When prompted, choose the CSV format for your export. CSV (Comma-Separated Values) is a widely used format that can be easily handled by spreadsheet applications and other data processing tools.
If Delighted offers customization options, select the specific fields or data range you need. This may include filtering by date, survey type, or respondent details, allowing you to export only the relevant data.
After setting up the export parameters, initiate the download. The CSV file should be saved to your local computer. Make sure to choose a location where you can easily find the file, such as your desktop or a designated folder for data exports.
Open the downloaded CSV file using a spreadsheet application like Microsoft Excel or Google Sheets to verify that all the necessary data has been correctly exported. Check for completeness and accuracy to ensure no data is missing or incorrectly formatted.
By following these steps, you can efficiently move your data from Delighted to a local CSV file without the need for third-party connectors or integrations.
FAQs
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.
Delighted assists businesses connect with their customers learning, improving, and delighting.It is well known for delivering some of the most innovative functionality for customer experience management. Delighted is completely the self-serve experience management platform of choice for the worldwide top brands. It helps to collect and analyze survey feedback through Delighted. Get set up in minutes, no technical knowledge needed. Delight helps to build long-lasting relationships and deliver great service experience.
Delighted's API provides access to various types of data related to customer feedback and satisfaction. The categories of data that can be accessed through Delighted's API are:
1. Survey Responses: This includes all the responses received from customers through Delighted's surveys. It includes both quantitative and qualitative data.
2. Metrics: This includes various metrics related to customer satisfaction, such as Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), and Customer Effort Score (CES).
3. Trends: This includes trends related to customer feedback and satisfaction over time. It helps businesses to identify patterns and make data-driven decisions.
4. Segmentation: This includes data related to customer segments, such as demographics, location, and behavior. It helps businesses to understand their customers better and tailor their offerings accordingly.
5. Integrations: Delighted's API also provides access to data from various integrations, such as Salesforce, HubSpot, and Slack. It helps businesses to streamline their workflows and improve their customer experience. Overall, Delighted's API provides a comprehensive set of data that businesses can use to measure and improve their customer satisfaction.
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.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
