New applications for analytics
Crucially, outside of private individuals, brands seeking to understand consumers are no longer the only players in the social media space. This trend was witnessed over the course of 2016 and is set to strengthen in 2017.
As Brexit and the results of the US election revealed, accurate social media analytics has uses far beyond the purely consumer-oriented – with as yet untapped potential for governments, aid organisations and other monitoring bodies seeking to anticipate key outcomes.
With developments in the field, social media activity can now be leveraged to generate detailed data and insight. While simple numbers of likes and shares will remain relevant, the new year will usher in an era of exploring the deeper significance of these social signals and what they mean at their core for corporates, social movements and countries. Monitoring sentiment will be key.
The implications hereof are many. Not only will new opportunities for brands and other entities looking to understand or reach highly targeted audiences emerge, but also consumers will be the recipients of ever more customised and reactive brand experiences.
On the corporate front particularly, insight into consumer behaviour – understanding how people think and feel based on what they share voluntarily across social media – has applications not only for marketing and PR, but, crucially, for business intelligence, market research and strategy.
In the public and governmental arenas, on the other hand, greater insight will mean fewer surprises when it comes to the progression of elections, conflict and social movements. For the consumer, greater targeting and customisation means exposure to less scattershot advertising and less irrelevant information.
Although algorithmic analysis of the social media landscape has become more sophisticated, pure machine processing remains not fully up to the task of reliably classifying and categorising the entire nuance inherent in how we communicate.
There are myriad issues. Among them are slang, sarcasm, local references, acronyms and double meanings – all integral parts of how we share information and all of which negatively affect computers’ ability to sort, classify and rate social media information for relevance and underlying sentiment. The result is often distortion and uncertainty.
Given that major business decisions will likely rely increasingly on social media data, accuracy is key. Analysis that leverages the power of actual human insight generates far more accurate data than can machine processing alone. In this line, by coupling algorithmic with human-integrated (crowd) analysis, we were able to call Brexit and the outcome of the 2016 US presidential election correctly.
With aspersions cast on traditional polling techniques (which failed to anticipate either outcome), results such as these have ushered in a new era and role for social media analytics – broadening the field’s application from the purely commercial to the social, civil and beyond.
Moving on to social media campaign drivers, emotion (and content that evokes it) will also likely be key in the year ahead. When media saturation is high, eliciting a strong emotional response remains one of the few ways in which content can be made to stand out. Emotive content is also, often, action inducing via tweets and shares. Here particularly the need to accurately assess consumer sentiment becomes crucial and is a space in which human integration comes into its own.
Leveraging data available through social media campaigns will allow brands not only to isolate key target groups, but deliver them highly personalised and relevant content that has the ability to be heard above the white noise of today’s media-saturated landscape.
The start of new era for sentiment-driven, human-integrated analytics was marked by the correct call first around Brexit and later the outcome of the US presidential election. With the capabilities of purely algorithm-driven approaches beginning to plateau, the approach represents the industry’s next big leap forward.
Next year will see the application of human-integrated analytics both deepened and broadened. Instead of remaining the exclusive preserve of marketing departments, the technology is poised to become an integral driver of strategic business decisions across a wide variety of organisations, both public and private. In this capacity in particular, a very high degree of accuracy is necessary – something human assisted analytics is able to provide.
With an increasingly impressive track record in 2016, 2017 will likely be the year that sees human-integrated, sentiment-driven analytics begin to come of age.
