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OCR (optical character reader) Definition

Automatic computer input process whereby the computer scanner is able to read printed characters and convert them to electronic data.

An Optical Character Reader (OCR) is a technology that converts printed or handwritten text in scanned documents, images or forms into machine-readable digital data. In market research, OCR is used to digitize paper-based surveys, questionnaires and other written materials for analysis and storage.

Who relies on an OCR in market research?

Market researchers, data analysts, survey administrators and organizations conducting research or collecting data in paper-based formats rely on OCR to streamline the digitization process. Industries with extensive form-based data collection, like health care, finance and retail also use OCR technology.

What are key aspects of OCRs in market research?         

Key OCR aspects include:

• Text recognition: Converts printed or handwritten text into digital formats.
• Efficiency: Speeds up the process of digitizing large volumes of paper-based data.
• Data accuracy: Reduces manual entry errors but may require verification for high accuracy.
• Integration: Compatible with data analysis tools and databases for streamlined processing.
• Versatility: Supports various formats, including surveys, forms and invoices.

Why are OCRs important in market research?    

OCRs are important because they save time and reduce costs associated with manual data entry, especially when dealing with large volumes of paper-based surveys or responses. They enhance efficiency, improve accuracy and enable researchers to focus on data analysis and insights rather than data collection and transcription.

How do market researchers use OCRs?  

Market researchers use OCRs to digitize responses from paper surveys, customer feedback forms or other handwritten or printed materials. Once converted, the data can be easily integrated into databases or analysis tools for statistical evaluation, reporting, and visualization. OCRs allow researchers to process large datasets efficiently, ensuring timely and accurate insights.