getWizer, an automated, fully tailored consumer insights platform, now enables market researchers to constantly utilize real-time automated data cleansing throughout the data collection process.

This latest unique feature to the getWizer platform uses artificial intelligence algorithms to deploy a mix of approaches, including natural language processing, to analyze text in open-ended responses for relevancy and readability. The algorithm automatically identifies problematic data, such as curse words, typos and gibberish, detects suspicious answer patterns, response inconsistencies, and removes ‘speeders’ — respondents who finish the survey too quickly to provide quality answers.

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Real-time data cleansing using advanced algorithms sets getWizer apart from other available solutions making it unique when it comes to ensuring data quality. This means that when data is available within the getWizer platform it will be immediately ready to analyze and run statistics on.

This data cleansing process also works for image-based responses using machine vision algorithms to examine the content of images uploaded by respondents before automatically tagging and categorizing them.

“Data quality in market research is a big issue,” says Alon Ravid, Co Founder & CEO. “Bad or ‘dirty’ data undermines the validity of the entire research dataset and any insights derived from it. getWizer’s real-time automation of data cleansing assures quality, lowers cost, eliminates the need for manual labor and reduces overall time-in-field.”

This new innovative data cleansing tool joins several other recent additions to the getWizer platform, strengthening its position as the one-stop-shop consumer research platform. getWizer replaces slow, labor-intensive manual research tasks, to automate the entire research process. With getWizer’s latest new tool, users can access quick, cost effective and consistently clean research data automatically filtered to ensure the optimization of research insights.

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