November 13, 2019
It is estimated that 30-50% of surveys are now taken on mobile devices, and yet many survey platforms lack the ability to adjust the questions to be mobile-friendly. In other words, the user experience is lacking. Have you ever taken a survey on your phone or gone to a website where it clearly is not mobile compatible? The font is too big and the website doesn’t automatically resize, and all of these issues create an immense amount of frustration to the user. This interaction results in people discontinuing the survey or not even starting it because they are not on a laptop or desktop. We will continue to see survey programs and software make a shift towards mobile compatibility or they will run the risk of losing business.
We are also seeing growing fatigue among respondents with longer surveys. Time is valuable and in a “busy” culture, surveys over fifteen minutes see higher dropout rates. A way to combat this will be shorter surveys that pop up on websites or on phones after a purchase. Some of these will be chatbot interactions which will receive feedback and insights in real-time. These shorter, micro surveys will make data collection a more automated and seamless process.
Lastly, artificial intelligence in research will also contribute by effectively analyzing open text responses – saving researchers time and creating more value for clients. Currently, researchers code open-ended responses into categories or buckets, but if AI could do this for researchers, it would be a much more time efficient process. Another hope is that AI will be able to measure the sentiment of responses which can help marketers know if the response if positive or negative.
Clients want to hear directly from their consumers. While traditional qualitative research can be time-consuming and expensive, other methods to get qualitative feedback have improved significantly. Online focus groups allow researchers to speak to more people in a shorter time frame while testing out messages and content all in real-time. Respondents can share video responses or record how they are interacting with a website. All this information is helpful to clients looking for more of the “color” qualitative research can provide while doing it in a budget-friendly way. We will also see a growth in online communities where people can also share open dialogue. Respondents can submit video diaries for studies over a certain time frame and it gives researchers more flexibility to adjust or ask to follow up questions during a project. These methodologies offer researchers different ways to collect information and to interact with consumers.
Quantitative research will remain valuable as companies will continue to measure and benchmark awareness, satisfaction, and perceptions. Quantitative research can also help measure brand attributes and associations. None of these measures are going away, especially as the costs of conducting research continue to decrease and the ability to reach people grows through the use of technology.
As consumers, we are constantly hearing the term “big data”, and how our personal information is more available than ever. While the thought of this may some people uncomfortable, when this data is used correctly, research shows the customer values and appreciates brand experiences curated and customized just for them. For example, brands that use social media analytics and listening tools to gain insights from online conversations and consumer behavior end up having more success at providing specialized experiences for their target consumer’s needs. But social is just one piece of the puzzle. The blending of these forms of data will likely result in some mistakes and road bumps along the way, but the end result will be a better understanding of the ‘why’ behind how people make decisions and the emotions that are involved in the process.
In the past, mixed-mode research was defined as an “approach to research in the social, behavioral, and health sciences in which the investigator gathers both quantitative (closed-ended) and qualitative (open-ended) data, integrates the two, and then draws interpretations based on the combined strengths of both sets of data to [better] understand research problems.” That definition may need an update that incorporates qualitative, quantitative, and other sources of data such as social media and marketing analytics — information that was not available to us just a few decades ago. Companies that know their consumers the best and align their brand to meet their consumers’ needs and expectations are bound to see greater success as we move into a new decade.
Check out more of our 2020 predictions: