Before the battle between declarative data versus behavioral data, there was a time when relying on declarative data was at the core of what market researchers knew. As we know, declarative data is simply just self reported data: information collected through active participation in a research study, where the participant personally relays their own responses.
There's always been issues with declarative data though, such as memory failure and social desirability. Especially in regards to sensitive information or long term recall, the possibility of self reported data being skewed has always been a critical limitation.
Thankfully, we now have new forms of data collection for online research.
*Cue behavioral data*
Declarative data may or may not always remain an integral part of our industry because there’s new processes stealing center stage. Behavioral data is beginning to take on the leading role of current research practices because of its clear advantage over declarative data.
You might be wondering a few questions such as:
- What exactly is the difference between declarative and behavioral data?
- What exactly makes behavioral data much more accurate at times?
- Why do we still use declarative data?
Declarative Data Versus Behavioral Data
Declared data collection, as mentioned above, is the process of acquiring information from participants through self reporting; where self-reporting can take on a variety of forms. On the other hand, behavioral data collection is the process of gathering information about participants based on observational tracking methods. The essential difference between the two forms of data collection comes down to how we gather information about our participants.
Methods of Collecting Data
• Traditional opinion surveys
• In-depth interviews
• Focus groups
• Online communities
• Virtual Environments / Virtual Reality
• Offline / Online mystery shoppers
• Conjoint and Maxdiff
• Client satisfaction measurement (i.e. NPS)
• Online diaries
• Mobile diaries
• Social media listening
• Offline/online facial coding
• Offline/Online eye tracking
• Other neuroscience techniques
• Geolocation research
• Online behavioral research
• E-commerce sales measurement
• Internet of Things (IoT) data
• Audio matching
• STV & radio audiences
As you can see in the table above, declarative data is always collected through a medium where the participant gives their own feedback. Whether it’s rating something on a Likert scale or filling out an opened ended questionnaire or recalling behaviors in the form of a diary—any type of data collection that is acquired through self report is considered declarative.
Behavioral data is quite the opposite. With this form of data collection, the participant is not responsible for providing any proactive feedback via questionnaires, surveys, diaries, etc. Rather, the researcher collects observational data about the participant by listening, tracking, coding, and other techniques.
For example, say we wanted to determine the most populated websites of our participants. Asking the participants what websites they visit most would be a form of declared data collection. Whereas, simply tracking their online behavior (with permission of course, but that’s a blog for another day) would be considered a form of behavioral data collection.
In short, an easy way to remember the difference is that declarative data is collected based on what one declares and behavioral data is based on how one behaves.
When and Why You Should Use Behavioral Data
Whenever you have the opportunity, use behavioral data. I’m sure you’re wondering why though. Let’s dive deeper.
In recent decades, the consumer has changed, and therefore, so has the way we conduct research. A large majority of consumer activity is now conducted and accessed online thanks to the rise of the Internet. Meaning, many consumers are leaving data trails that can help market researchers better understand them.
Research has even provided evidence that behavioral data has a clear advantage over declarative data being as people often struggle to provide accurate information declaratively. When social desirability or memory failure are high concerns, it’s good to rely on behavioral data, which cannot lie or forget information.
To better explain, let’s take another look at our previous example. When asking participants about their web browsing activity (declarative), we are at an increased risk of receiving skewed information for two reasons. In some cases, the participants may not be able to accurately recall which websites they have visited, especially if we’re asking about activity from a long time ago. In other cases, if the participants are embarrassed or protective about what websites they have visited they may not disclose the entire truth.
We can altogether avoid the risks of social desirability and recall failure if we simply collect behavioral data instead of declarative data. Behavioral data in this case cannot be manipulated; the browsing history, clickstream data, and other IoT data of the participants would be considered cold hard evidence monitored and collected through advanced technological techniques.
If Behavioral Data is So Great, Why Use Declarative?
As stated in “When should we ask, when should we measure” (M. Revilla, C.Ochoa, R. Voorend & G. Loewe), we believe that different forms of data collection, instead of competing with each other, can complement each other. Understanding the whole consumer, from what they report about themselves to what their behavior discloses, can be an invaluable combination of data.
But the real reason declarative data has remained important is because behavioral data is not always accessible. As research methods continue to advance with the help of technology and the Internet, behavioral data will become more accessible… And may eventually entirely replace declarative data.
The market research industry is evolving faster than ever. Stay informed by downloading our ebook, The new types of data for market research.