The world’s largest social networks are storing massive amounts of never-before-analysed data that could reveal crucial information about consumers — from how people arrive at purchase decisions, to what services or goods they may need in the near future.
Potentially, this data could also make social networks like Facebook and Pinterest do a better job of showing users what they want to see, rather than content and ads they’d rather not waste time on. However, as much as 90% of the data is “unstructured,” meaning it’s spontaneously generated and not easily captured and classified.
In a new report from BI Intelligence, we show how advances
in “deep learning,” cutting-edge artificial intelligence research that attempts to program machines to perform high-level thought and abstractions, are helping social networks and their advertisers glean insights from this vast ocean of unstructured consumer data. Thanks to deep learning, social media has the potential to become far more personalised. New marketing fields are quickly emerging, too:
audience clustering, predictive marketing, and sophisticated brand sentiment analysis.
Here are some of the key takeaways from the report:
- Seventy-one per cent of chief marketing officers around the globe feel their organisation is unprepared to deal with the explosion of big data over the next few years, according to an IBM survey. They cited it as their top challenge.
- Targeted and personalised marketing using social data is expected to be the business area that benefits the most from mining big data — 61% of data professionals say big data will overhaul the practice for the better, according to Booz & Company.
- Facebook ingests approximately 500 times more data each day than the New York Stock Exchange(NYSE). Twitter is storing at least 12 times more data each day than the NYSE.
- By deciphering image and video-based data, marketers will be more effective and comprehensive in their “social listening” efforts. Large companies spend a great deal of money monitoring people’s attitudes toward a specific brands or product, and despite all the photo-and video-sharing happening on social media, these mediums were formerly mostly invisible to their analytics tools.
In full, the report: