There are many emerging trends in the social media space. Many of these are in the area of social media analytics. Over the last two years, there has been a broadening and deepening of social media analytics. The focus is now on deep data extraction, human insight and the amplification of emotive content. As we move forward, accurate sentiment analysis is also needed.
The following are some of the key social marketing analytics trends for this year and beyond.
1 Beyond Business
In the aftermath of Brexit and the US Presidential election, one can't argue with the fact that social media analytics has use beyond consumer-oriented applications. The potential for politicians, governments, non-profit organizations and the like is untapped. As we move forward, new applications for social media analytics will come up as people and organizations seek to generate detailed insights and explore the deeper significance of social signals and their implications.
2 Personalization and Accurate Forecasting
One of the marketing challenges for decades has been the ability to tailor make marketing messages that are highly personalized. Social media analytics made this possible and is getting better at it every day. Brands are now able to understand and reach highly targeted audiences. Consumers are receiving more and more customized marketing messages. More customization means that customers no longer have to be subjected the traditional "broad spectrum" advertising approach that is responsible the high levels of "ad blindness" that we see today.
On the corporate arena, “getting into people's heads” to understand how they perceive and feel based on their behavior on social media, has application not just in marketing and public relations but is invaluable to accurate forecasting, business intelligence, strategy, and market research.
For government and non-profits, improved insights mean fewer surprises in the area of elections, social conflict and issues of major concern in the society.
3 Human Insight Remains Key
Artificial intelligence (AI) and machine learning have pervaded all spheres of life and social media analytics is no different. However, in spite of the great strides AI has made in social media analysis, machine processing hasn't quite evolved to the point where you can "set it and forget it". At the core of the problem is a number of issues, key among them being the complicated nature of human language. Slang, colloquialisms, local references, the use of two or more languages in the same sentence, double meanings and so forth are all nuances inherent in human communication. They make it difficult for computers to accurately sort, classify and even rate social media data for relevance and meaning. Often, the result, when computers can't make sense of the data, is distortion and uncertainty.
Since business decisions are increasingly relying on social media data, accuracy is of paramount importance. Human insight provides much more accurate data but is slow. To get maximum benefit, it is imperative to combine both machine processing and human insight. This is how the company BrandsEye was able to correctly predict the outcome of the Brexit vote and the 2016 US Presidential election.
4 Emotive Content
Our lives are inundated with media. From television and radio to email, Twitter, Facebook, the Internet, messaging, and much more. This has led to high media saturation. In a media-saturated environment, the only way for a message to get across is to elicit a strong emotional response. Emotive content is content that induces action. It could be a tweet of Facebook share. In order to be heard above the noise, brands must accurately assess consumer sentiment. Data available from social media campaigns is now allowing brands to ultra-target distinct groups and deliver highly personal, relevant and emotive content.
The beginning of a new era where human integrated social media analytics tools rule was marked by accurate predictions of Brexit and the US Presidential election. This new approach represents the future especially with the capabilities of pure algorithm based social media analytics beginning to wane.
The next 12 months will see the use of human integrated social media analytics deepen and broaden. Rather than remain the preserve of marketers, technology is set to become a key driver of business decisions in many industries. The high level of accuracy required is almost guaranteed by human integrated social media analytics. If the impressive track record is anything to go by, the next few months will see integrated social media analytics come of age.