How can businesses take control of social data analytics?

As companies start to realise the benefits of social data analytics, several considerations and challenges are also popping up. There are questions about how to bring the skill in-house and how to apply the data across the board in a meaningful way.

To get a better understanding of how businesses can take control of social intelligence, we delved into this topic during the SI Tech Demo Day 2021 with Angela Berger, Director of Insights & Analytics at Walmart; Melissa Davies, Real-Time Insights Manager at Mondelez; and Nichole Held, Media Intelligence Strategist at 3M.

Menaka Gopinath, who currently heads the Ipsos Social Media Exchange for North America hosted the session, where we explored the current role of social data in organisations and how to make better use of it.

The current state of social intelligence in organizations

For many companies, including Walmart, Mondelez, and 3M, social intelligence is a decentralized function. There’s typically a “network” of social intelligence experts spread across the business. But social media intelligence can’t exist in a silo. It’s relevant for every department – from social media strategists to product development teams to customer care departments.

So although these experts focus on their individual departments, they still need to work together in alignment to bring value to the organization as a whole. For this, companies need to democratize social listening data, methodology, and tools for subject matter experts across the business.

Understanding data democratization and data hybridization

“Data democratization” is a term that often comes up in discussions about social listening and social data. Angela explains it as a process of slowly introducing data to people within the organization, giving them more visibility. But a huge part of data democratization is to gradually upskill people so that they can easily get the information they need without having to go to one person or team every time.

When discussing data democratization, we should also consider data hybridization, i.e. combining different data sources for a more complete view. It’s important to note that there isn’t just a single source of truth and social media is only one part of the story. Besides social media, there’s also search data, transaction data, information on stock trends, consumer confidence, and so on. Companies need to bring all the pieces together to build the bigger picture.

Leveraging social data to support the business as a whole

As mentioned, social data isn’t just useful for the social media team or for the marketing team. It plays a crucial role in informing decisions within every aspect of the business.

And one of the best ways to leverage social data to support the business as a whole is by incorporating it into other data analysis. In doing this, companies can add a human element to the data and tell a story that will help them build a stronger connection with the audience.

Melissa explains that the Mondelez Real-Time Insights team uses a robust and quantitative survey system. But as comprehensive as the insights may be, it still lacks the “human element.” Social data helps to bring in that personal touch by incorporating the voice of the customer alongside other types of robust research. Combining those insights can help to tell a bigger story for the organization as a whole.

Even if it’s just adding quotes or Tweets, it “helps people digest the information you’re presenting rather than just seeing all these numbers and charts and glossing over it,” according to Angela.

Can social data help with future predictions?

While social listening has proven its value in providing data for “the now,” there’s still room for improvement in the use of the data to predict future trends. One of the biggest challenges that analysts face is figuring out what’s a short-term fad and what’s going to be a long-term trend.

It’s easy to understand the big themes from looking at certain conversations. But to use those same conversations for predicting the future, companies need to look at the smaller signals in the data, the anomalies, and the things that are quietly developing.

As Nicole puts it, it involves “looking at the things that aren’t so loud and following their path.” Companies need to pick up on the micro signals and figure out how to act on it before it grows into a huge issue, or how to build on an opportunity before the competitors can.

The ideal state of social intelligence in organizations

When defining the “ideal state” of social intelligence in organizations, centralization seems to be a common theme. Having a centralized internal team that manages things locally can help to maintain consistency in terms of approach and level of expertise. So there’s a need to have somewhat of a “centre of excellence” that everything comes back to.

At the same time, it’s also crucial to have skills and capability embedded in the local markets, especially for global organizations. This will allow them to apply local languages and nuances into the data from a native speaker standpoint.