Mixed methods research
Mixed methods research combines quantitative and qualitative data in one study and integrates them, so the numbers show how much or how many and the qualitative evidence explains why. The integration is what makes it mixed, beyond running two studies side by side.
How it works
Three core designs are common. In a convergent design, quantitative and qualitative data are collected at the same time and compared. In an explanatory sequential design, a survey or analytics study comes first and interviews follow to explain its results. In an exploratory sequential design, interviews come first and a survey then tests how widely their findings hold.
Fetters and colleagues place integration at three levels. In the design, one phase is planned to build on the other; in the methods, the datasets are linked, for instance by drawing the interview sample from survey respondents; and in reporting, a joint display sets statistics and quotes in one table or figure so they are read together.
A worked example
In a hotel group's survey of 2,000 guests, intent to stay again is 22 points lower among guests who complained during their stay. Following an explanatory sequential design, the team interviews 25 of those guests. The main reason, heard 17 times, is that nobody told them what happened after they complained.
Related
Automate this in Pulse
Pulse can field the survey and the interviews of a mixed methods design in one study with one audience, leaving the team to integrate the counts and the reasons.