Why: improved quality
Sharing experiences becomes easier and more inviting when research addresses the specific situation. By adapting the content to the situation, the interaction becomes more of a targeted dialogue rather than a standard questionnaire. Adapting to circumstances can be achieved by:
Addressing a characteristic of the person or transaction
Zooming in on given answers
Making questions dependent on previously provided input
By cleverly combining these above-mentioned possibilities, the content can be extensively customized to the situation and previous responses. Employees can express their experiences more effectively, feel better heard, and are more inclined to share feedback.
Shaping data-driven research
The quality of data-driven research depends on the design process and a technical framework to define interactivity. The technical framework should provide sufficient capabilities to make explanations, questions, and answers dependent on the available data. In the design process, knowledge or dependencies in the process are brought together with technical possibilities.
To give you an idea of the possibilities, here's an overview of different concepts for data-driven research, including examples that demonstrate how you can dynamically adjust the content of your research.
Referencing - this involves directly referring to a specific situation. A good example is referencing a ticket number or description when evaluating a closed ticket. Email invitations often refer to the specific situation (transaction or ticket), but being able to reference this data within the survey itself makes the research even more direct.
Conditional questions - making the decision to ask a specific question depending on the situation. For example, depending on the channel through which a request is received, you may want to specifically ask about accessibility over the phone but not in other cases. Similarly, if availability of facilities depends on location, only the relevant questions can be presented to the employee based on conditions.
Interactive questioning - by interactive questioning, we mean tailoring the questionnaire based on previously provided answers. Creating a "route" is a well-known form of interactivity. With more advanced forms of interactive questioning, you can delve even deeper. For example, probing further on selected or non-selected items. A good example is first asking about the items the employee has experience with, then having them rate those items, and then probing further on only the poorly rated items.
One-dimensional lookup - looking up and using a related value. For example, the name of the CEO per branch. This allows you to have each invitation signed by the local branch director.
Two-dimensional lookup - you can take the concept of looking up related values even further. For example, by creating a "matrix" with the most-used company applications per department. In online research, you can individualize the list of company applications by using this matrix. This way, you can gather information about dozens of different company applications in a continuous survey.
By leveraging these data-driven capabilities, you make research highly relevant to the employee. They can recognize themselves in the situation and are more inclined to provide feedback. The importance of utilizing these possibilities becomes greater as the research becomes more extensive in terms of scope, geography, or frequency of repetition.
Data-driven research checklist:
Referencing in email invitations
Referencing in online research