Data Collection & Analysis
If you know the questions you want to ask but need help reaching the right audience, we can take care of every aspect of your research fieldwork for you.
Your competitive edge demands high-quality data collected and delivered quickly and analysed efficiently.
Through our in-house data collection and analysis experts, audience access consultants and proprietary technology, we can satisfy all of your market research fieldwork needs, including Survey design, Survey programming and hosting, Translations and coding, Audience access, Advanced statistical analysis techniques, Data processing, Data visualisation.
Data Collection
Surveys, interviews, focus groups, and direct observations are popular and effective methods of data collection. Do you need to administer customer or employee surveys, or are you conducting market research or program evaluations? Research Matters offers data collection services to assist you with all of this and more.
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Our web scraping services are designed specifically to empower companies by taking unstructured data from internet and turning it into structured data ready for consumption.
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Research Matters is a reliable outsourcing partner for companies that want to get insights from their data while skipping the technicalities. We take care of the data analytics infrastructure and apply advanced data analysis to provide our customers with rigorous reports. Our team is composed of experts in qualitative and quantitative data analysis.
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Research Matters performs a quality inspection that ensures you are using the right data and helps to optimize the entire data analysis process.
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Research Matters detects and removes inaccurate records and replaces them with correct data.
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Research Matters determines common patterns and threads to facilitate possible comparisons among several groups of data.
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Research Matters takes a closer look at outlying data points to assess how relevant they are.
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Research Matters assesses missing variables, calculates the potential impact and helps you fix the problem if it exists within your data.
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