Business Insights using Social Intelligence
Innovations made possible by technology are a way of life today, helping to improve the way we do business. A great example would be how artificial, and social intelligence is helping us to gain advanced insights into customer preferences.
Social Intelligence, also known as social media intelligence, is a collection of tools which gather analytical information from open sources or closed social networks, using a combination of intrusive and non-intrusive methods.
Social Intelligence for Business Learning
Managers continuously search for genuine insights which would help them design products that resonate well with their customers. Social listening provides great insights which help them gain such business intelligence.
To illustrate, let’s see how Barclays realized the real value of social listening when they launched their banking application PingIt. Real-time customer insights helped Barclays gauge customer preferences and make critical changes to their application. Sentiment analysis of the data collected from social media showed that there was some negative chatter building around the lack of banking provisions for teenagers (under 18s) in the app. Responding quickly to the customer feedback, Barclays added the missing feature within a week.
Barclays PingIt was downloaded more than 120000 times in just 5 days.
Layers of Social Intelligence
There is an ever-growing number of companies willing to invest in and try social intelligence. However, the term has been loosely used and has left much confusion in its wake.
Social intelligence is often confused with social listening and social monitoring. Though they fall under the same umbrella, each one is different and unique in its own way. Social listening and social monitoring are tools we use to gain social intelligence.
Social intelligence is about gaining a thorough understanding of the available social data. It has many layers which make the overall analysis easy and flexible.
Social Monitoring and listening
Social monitoring and listening help assimilate the data from all the built-up chatter.
The chatter collected can house historical data about your brand, search queries, social media comments or conversations, and review board entries etcetera. The source of data also determines the quality of the data and the final analysis in turn.
Often, the social data collected is unstructured. Data management aids appropriate filtration and segmentation which makes it worthy of further investigation. Sometimes, a brand with a generic name (say, a brand called lemon), can draw in a lot of non-relevant chatter, but data management helps to weed out the unnecessary bits.
The usual filters include:
Time specific: Data ranging from a few minutes to a few years
Geography: Data from specific geographical areas
Media type: The source of the data – Facebook/ Twitter/ Instagram/ Google reviews
Sentiment: Positive, negative or neutral
Advanced analytics takes care of anything that goes beyond the scope of data management. Businesses seek actionable insights which can be translated directly into a corrective strategy.
Using advanced analytics like Boolean processing, you can bridge the gap between an action and its outcome. Social listening enables you to draw relevant mentions and conversations while data management helps filter it. Analytics, on the other hand, translates the meaning of the conversation extracting the most key perceptions.
Social intelligence has evolved dramatically over the years. Analytics is no more limited to a dashboard, with options for customizations. Real-time insights also come in the form of reports, alerts and command centers. When choosing a social intelligence platform, its ability to deliver actionable insights is the desired feature, for companies.
The analysis of relevant social media chatter and the references drawn from it can help your business outperform your competition in a hundred ways. Social media intelligence helps you deliver on that promise by making your business evolve furthermore.