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Finding social media influencers with predictive analytics

By September 14, 2016 No Comments

One bad Yelp review can severely damage a brand’s online presence. The good news is a positive review might also go viral and cause numerous individuals to jump on the band wagon. This is what happened when a young student praised a local pizza company for its excellent service and quality products, according to Customer Service Guru.

Clever social media posts made by children are often popular, as our reviews of brands by celebrities or well-known YouTube critics. There are many individuals who have a huge amount of followers and the trust of their audiences. How can brands recognize these consumers and make the most of their influence?

Many companies implement predictive forecasting tools to see which online demographics are popular on public networks and how to improve communication with these individuals.

Social media can be difficult
There are a variety of reasons companies may have a problem leveraging social media data. Platforms like Twitter and Facebook are relatively new, while innovative channels like SnapChat pop up every day. The sites encourage casual conversation like slang that is difficult to turn into hard data. Not to mention, the large number of brands that recognize the potential of social media means there’s plenty of competition when trying to contact influencers.

A Software Advice research report found 46 percent of marketers said it was difficult to identify social media influencers. The main reasons for problems included privacy concerns and an inability to predict the actions of social audiences. Social users, however, expect brands to make use of their public details and prefer when businesses send them personalized deals.

Over two-thirds of marketers said they have yet to utilize predictive analytics when working with social media. Using intelligent business systems can help businesses sort through great amounts of public data and find what actions will bring about desired effects.

Predictive analytics on social media
Automated data systems can collect information from sources based on assigned criteria. With enough material to reference, solutions can quantify content like slang to identify recurring trends. When a brand wants to see which channels matter the most to a particular brand’s goals, it may need custom BI solutions.

This allows companies to see which public information discusses certain topics the most and which social media users influence trends. Martech Advisor said predictive modeling tools can do more than just identify. Automated marketing systems instantly respond to certain users with content proven to encourage participation from their demographics. This creates consistent strategies to engage and communicate with individuals most likely to affect a business’s bottom line.

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