Due to the ever-growing footprint of social media, it’s becoming increasingly important to monitor and derive sentiments from public, online conversations. And because social media is a highly emotive space, there is a broader, more colorful scope available to examine.

Using social listening to get to the root of ideas, behaviors, and macro and micro trends, researchers can isolate the data that matters most while keeping a pulse on other, more peripheral patterns that emerge over time. Because of this, social listening will become one of the biggest socio-cultural trends in marketing research and undoubtedly be a major element of future ethnographic research.

Using AI-assisted data collection methods is drastically improving research efficiency and efficacy for brands. By limiting human interactions and increasing point-of-experience research, there is a significantly greater chance of collecting the right data from the right people. It also allows teams to focus more on deriving insights from the data, rather than wasting time on the data collection itself.

AI-based sentiment analysis helps researchers collect and categorize insights from long-form and open-ended text-based data, without requiring a human team member to manually interpret it. Getting the right real-time data into the hands of the right stakeholders is quickly becoming a new success benchmark for research teams.

The bottom line is that research is king when developing advertising campaigns for our clients.  It determines exactly “Who” we target, exactly “When” to target them and of course “Where” to reach them.  All with content that we know, through social listening and AI data, will generate engagement and interaction. 

Source:  fuelcycle.com