Using quality information is analysis - with experiment

Using quality information for analysis, or staying with just quantity based information is always a good base for debate: Either relying on quantitative measurements and data (which is sad to be more accurate and easier to rely on) or use quantitative measurements (which is sad to be human / easier to understand and answer). In both ways the collected data will require further processing to be used in decision-making. An experiment was made on customer satisfaction on an imaginary service. The service was a web based TTS (Text-To-Speech) software test. Of course, all the voices were pre-recorded, so the participants were all chosen not to realize that (every member with low IT knowledge). After the end of the reading everyone had to answer a few questions regarding the quality. Group "A" had to answer the questions (which were sounding more scientific) with numbers related the current measure - help provided if needed. Group "B" had to answer the same questions with open answers, as they like. -- quality data ; quality measures ; qualitative and quantitative measurements for CRM/BI