Uncovering Deeper Insights from Survey Responses with Passive Data

Utilising quant surveys alongside Gener8’s passive datasets, connected together via a single user ID, enables richer analysis of people’s eating and food delivery habits

At Gener8 we sit on a vast lake of passive user data. This not only helps us to better understand the search, web browsing, purchase and app usage behaviour of our users but also leads to a strong understanding of each users’ interests and purchase intent. However there are certain demographics, like household size, and attitudes, such as those towards healthy eating, that are best unlocked by surveying the users directly.

In early November, we launched the Gener8 Snapshot survey to our user base to address this gap. This initiative provided us with a deeper and a more comprehensive understanding of our users across an additional 50+ demographic, attitudinal, and interest questions.

But what are the benefits of using these responses to the Gener8 Snapshot survey in conjunction with our other passive datasets? For the purposes of this article we looked at diet-related question responses and compared them with the eReceipt food delivery purchase behaviour across the Deliveroo and Uber Eats.

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Learn more about your survey respondents with passive data

Utilising surveys is an incredibly valuable method for gaining a deeper understanding of your target audience and uncovering meaningful insights that can effectively guide media campaigns and inform critical business decisions. However, what if there were a way to take this understanding even further?

Using Gener8’s single user ID connection, it becomes possible to draw comparisons between the declared survey responses and the actual behaviours of users. By analysing the survey respondents’ average number of food delivery orders over the past 90 days and comparing this data to their answers in the Gener8 Snapshot survey, we were able to uncover, validate, and confirm some fascinating relationships.

For instance, survey respondents who said that they consistently or frequently maintain healthy eating habits were found to have placed significantly lower food delivery orders. In contrast, individuals who reported never following healthy eating habits made, on average, 3.6 times more orders per user compared to those who always stick to a diet.

Clearly, by leveraging passive behavioural data alongside surveys researchers can gain deeper insights for their projects.

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Mitigate survey bias with passive behavioural data

It’s no surprise that survey respondents often say one thing when answering questions but may behave differently in real-life situations. Addressing these response biases, along with the challenges posed by nonresponse biases, can be quite difficult within the confines of a single survey. However, this is precisely where passive behavioural data can play a valuable role in providing deeper insights.

For instance, the passive data collected from food delivery orders appeared to align closely with the insights we gathered through our Gener8 Snapshot survey.

Individuals who primarily cook at home or prepare meals at home every day of the week were observed to place the fewest average food delivery orders per user. In contrast, those who reported that they "mostly eat out or order takeaway" were found to make six times as many food delivery orders compared to those who cook at home seven days a week.

While this correlation serves to confirm the validity of our survey responses, it could also play a significant role in mitigating survey bias in other contexts. Media and marketing professionals aiming for a higher level of confidence in their results have the opportunity to delve much deeper into user data. By doing so, they can identify and eliminate potential outliers in responses as well as detect and address answers that are likely to be biased.

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Focus on the survey questions key to your campaign

Certain demographic questions, such as age and gender, are considered mandatory fields in survey design because they allow for the identification and analysis of trends that may be influenced by the respondent’s personal background and characteristics.

And indeed, these fields add significant value to research. For example, when examining food delivery orders across different generations, it becomes very clear that younger generations are responsible for the majority of the frequent orders, while the food delivery activity is almost entirely absent among Baby Boomers.

With core user demographics such as age and gender integrated into Gener8’s user flow, you can confidently rely on having high demographic completion rates for your targeted passive behaviour cohorts. Furthermore, with the introduction of the Gener8 Snapshot survey, this level of understanding has been broadened to incorporate additional demographic questions. This expansion ensures that you can cut down the length of your surveys, allowing you to focus exclusively on the questions that are most relevant to your research and limiting respondent question fatigue, without compromising the quality or depth of your research.

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How can I access this data?

We utilised Gener8's Snapshot survey responses alongside eReceipts and Demographic datasets to uncover deep insights into people’s eating and food delivery habits.

Gener8 Labs’ complete data and insights solution empowers media and marketing businesses to find actionable consumer and market insights, using our unique, consented, first party panel data sets that are all connected around one user ID.

Discover how you can power your decisions and gain a competitive edge from our behavioural truth set by contacting us today!