Surveying Demographics Without Smartphones: We Can Still Reach Them

by | Aug 10, 2022


Conducting surveys using the Premise smartphone app is a fast and easy way to reach a large number of people, but how do we reach older demographics less likely to use smartphones? Our solution: a mixed-mode approach that includes separate samples for the app-based surveys and face-to-face interviews. 

A Premise partner recently put this to the test with a survey for which they needed to collect perception data across several strata, including age, gender, and geographic location. Some hardest-to-reach groups were included in this sampling frame, including rural-dwellers, women, and persons over the age of 60.

A peace-building and youth-focused USAID activity in Colombia needed to understand the general population’s perceptions of youth (defined as ages 15-29) regarding their trustworthiness, work ethic, and community roles and responsibilities. 

Premise’s network in Colombia skewed younger and male, and network sizes tended to be smaller in rural areas. To work through the issue, our partner first deployed a “youth in your community” questionnaire as a standard app-based survey. Then, to supplement in specific strata for which more responses were needed, e.g. women over the age of 60 living in rural areas, our partner tasked the Premise network with conducting face-to-face interviews with people over 60 using our app’s enumerator features.

Age verification was easy—Premise included a required question to take a photo of the interviewee’s national ID card, which in Colombia’s case, displays the birthday on the back with no other personal identifiable information shown.

With this method, Premise was able to obtain the rest of the needed responses by using Premise Contributors to conduct interviews in their communities, targeting individuals in the hard-to-reach strata the partner was looking for.

Surveying populations in low and middle countries frequently poses challenges not found in high-income countries, but high quality survey data is critical for making development and humanitarian programs more efficient and effective. Premise has developed the data quality control protocols to ensure mixed-method survey data is accurate and captured from the correct demographics and geographies. 

Our in-house team of research scientists, survey methodologists, and statisticians continue to develop tools that blend traditional statistical methods with cutting-edge techniques to ensure our customers get the most representative data possible in a timeframe that facilitates data-driven decisions and at a budget they can afford. 

To learn more about our international development work, check out our tech demo video or get in touch with us today. Be on the lookout for guides on using Premise for app-based surveys, face-to-face interviews, and mixed-method approaches soon!