With more people being involved in online social networking every day, social media have become an indispensable part of marketing strategies for businesses of all kinds. According to the Global State of Digital Report, there were 4.388 billion internet users worldwide in 2019, and 79% of them were active social users. When used strategically, social media marketing can contribute to a company’s revenue, engagement and awareness, but simply being on social media does not mean making use of all that social media have in store for businesses. What really matters is the way you use social channels, and that’s where opportunities may be revealed through machine learning.
We’re going through the explosion of data, but this data is useless unless it’s analyzed. Machine learning makes it possible to analyze limitless data sets and find patterns hidden behind them. Typically deployed with the help of machine learning consultants, this technology improves the way data is transformed into knowledge and enables businesses to make accurate predictions and fact-based decisions.
These are not all of the benefits, so let’s have a closer look at the other business facets that can be improved with machine learning.
Brand monitoring
Business success today is determined by a number of factors, and perhaps one of the most impactful of them is online reputation. According to the Local Consumer Review Survey, 82% of consumers check out online reviews for businesses, with each reading 10 reviews on average before trusting a business. This proves that good publicity is crucial for brands, that’s why executives need to find a way to manage business reputation effectively.
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Brand monitoring is a perfect solution, which is the search of any mentions of a brand in all available sources, including social media, forums, blogs, online reviews, and articles. Allowing businesses to spot problems before they grow into crises and react in time, brand monitoring also gives executives a thorough understanding of their target audience, and thus contributes to better decision making.
How machine learning helps
As the foundation for predictive analytics, machine learning contributes to decision makers’ thorough understanding of all the processes going on in their companies, so that their decisions become more data-driven and customer-oriented, and thus more effective.
Now think about all the mentions of your business available online — how many of them will there be? Hundreds? Thousands? Collecting and analyzing them manually is hardly a manageable challenge, while machine learning speeds up the process and provides a brand’s most detailed review.
Unless unhappy customers contact you directly by phone or email, the fastest way to find and assist them is sentiment analysis — the set of machine learning algorithms that evaluate public opinion about your business. In particular, brand mentions are filtered by negative or positive context so that your business can quickly react to cases that can affect your brand. Deploying machine learning lets businesses track customers’ opinions regardless of the language in which they are written, which expands the area of monitoring.
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