Social Listening Data: Massive, Ever-Changing, and Vital for Understanding Audiences

Did you know that 90% of people make purchases from brands they follow on social media? That’s a ridiculously large number! It makes sense, then, that brands should understand how their audience is scrolling, interacting, posting, and chatting on social media platforms. Valuable data appears to be there for the taking from these digital interactions and activities, but the sheer volume can seem overwhelming.

Social listening can mean many different things to different businesses. Some consider watching their own channels for interactions is enough. Others monitor the social media ecosystem for direct brand mentions, possibly comparing volume and reach to key competitors. Add in the layers of keywords that could be associated with your brand or business, topics that fall under your umbrella, and other discussions happening in your specific industry, and you have some big data on your hands.

 

A Social Listening Case Study

Let’s look at one example of a large, multinational brand that obtained data along these lines from multiple social media sites. The brand had planned to run it through an AI-powered classification tool to determine the basics, such as sentiment and behavioral segmentation. In fact, AI-driven solutions with advanced language recognition can be key for structuring and analyzing data to help brands better understand their consumers.

However, for this particular brand, the data set was so large that they would have had to split it up into several files to process it, losing some of the story in translation when stitching the data back together at the output stage. This can often be the case when it comes to social listening on a large scale, there can literally be millions and millions of disparate data points that must be matched up to uncover important insights that will ultimately advise brand communications, marketing, product development, and more.

In this particular situation, the global brand needed to explore its social media listening data inside out.

This meant finding a solution that could:

• Ingest and organize large, diverse data sets, like the kind that comes from scraping social media, quickly without having to break the data down into smaller pieces.
• Provide a single environment for not only handling the gargantuan data processing tasks but also take the data all the way through to analysis, visualization, dashboards, and reporting.
• Allow team members to investigate and interact with the data, by doing things like sorting results by concept or key phrase to examine a specific data point.
• Give researchers easy ways to share the insights and democratize the data across multiple geographic locations and company departments.

 

Options for Social Listening

There are multiple solutions available for brands to explore social listening data, and the technology selection must be made based on company goals. From a market researcher’s standpoint, being able to dig into the data, and combine it with other information, such as survey findings or sales data, can be important in building an in-depth understanding of audience sentiment and behavior. Getting the most out of the data also helps to prove value, making it essential for the insights teams to easily share their findings.

Informing and supporting business activities with social media data has taken on renewed importance recently. Current events are driving social media usage up, and there’s no doubt people are sharing important information on these platforms. As brands try to understand a consumer who is living in an entirely different reality than they were a few short months ago, powerful ways to investigate and leverage social data are vital for success.

 

Photo by Hugh Han on Unsplash