Traditional conversations – whether they are face-to-face discussions or phone calls – may still be a valuable way to communicate, but one has to wonder, how much truth is being disclosed in these interactions? Without a record of what was said to refer back to, the value of an exchange may be diminished.

In May, a survey conducted by the University of Michigan revealed that users are more truthful when discussing matters via text message than in a voice conversation. The study was conducted by interviewing 600 participants, asking a series of standard interview questions such as how often they worked out and how much they drank in a given week. The results indicated that answers varied depending on whether they were given via text or spoken word. According to the researchers, text message responses revealed more information and were considered more truthful.

"The preliminary results of our study suggest that people are more likely to disclose sensitive information via text messages than in voice interviews," said Fred Conrad, a cognitive psychologist and Director of the Program in Survey Methodology at the University of Michigan Institute for Social Research. Conrad admitted he was surprised by the results. "Many people thought that texting would decrease the likelihood of disclosing sensitive information because it creates a persistent, visual record of questions and answers that others might see on your phone and in the cloud."

This is important data for marketers engaging in SMS polling research. For one thing, it suggests that users are more apt to find value in messages displayed in text form. Additionally, they could be more likely to respond by disclosing valuable information.

Businesses that wish to capitalize on these findings should acquire the tools needed to formulate a mobile messaging campaign. Swift SMS Gateway is long experienced providing marketers with a simple network solution to enable text-back polling. Moreover, Swift SMS's experience provides a toolset that is flexible for easy customization for collection of data analytics.