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The brainchild of our Research Director, John McCusker, Kwest was established in 1989. John remains very much hands on with the research work we do and in the day to day running of the company.

We are proud to have remained loyal to our core values of being at the forefront of social research and providing high quality service to our clients. We achieve this by ensuring the staff we hire are the best around and by continuously investing heavily in cutting edge software tools.

At Kwest, we believe in the value of partnership and building long lasting, mutually beneficial relationships with our clients. The fact that the majority of work comes from word-of-mouth recommendations is clear evidence of our commitment to performing beyond clients’ expectations.

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Quality


Quality defines everything about us. We have a series of stringent quality control procedures in place throughout the projects we undertake to ensure that high standards are maintained. But it isn't simply about compliance with the proper procedures, it is also about our unwavering focus on engaging with our clients' requirements and making sure these are reflected in all that we do. Nothing is outsourced at Kwest - we keep firm control on quality by using our own, highly trained team for everything we do.

We are a Market Research Society Company Partner, fully compliant with the MRS Code of Conduct. We also adhere to other industry codes which provides assurance to the general public with whom we interact, our clients and other interested parties that our research is carried out in a professional and ethical manner. As would be expected, we are registered under the Data Protection Act.

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Analytics


Kwest’s in-house analytics consultants are at the cutting edge of market research development, keeping abreast of trends and advances in knowledge and practice.

Our analytics team has been involved in a number of projects aimed at contributing to the body of knowledge in social housing research. Such projects include the development of a satisfaction model that takes into consideration and removes the external demographic variables of a population which are known to distort resident satisfaction. By undertaking demographic compensation of the raw data, this model allows valid comparisons of satisfaction between organisations.