How Machine Learning Can Solve your PR Problems

Most organisations want to get noticed by customers to attract more business opportunities. Companies use public relations (PR) as one the means to communicate their strategy to the public. PR is a tough nut to crack, that's why experts are now leveraging machine learning (ML) techniques to solve the most complicated communication problems.

Before delving deeper into PR problems, we should first understand the meaning of public relations (PR) stands. Public relations is the management of the flow of information between groups and their users. To be more precise, it is a strategic communication process that builds mutually beneficial relationships between organizations and their audience.

PR aims to unite businesses or individuals with the public for a cause. For any organization to create a good relationship with their audience, it is vital to understand their preferences. In order to do so, there is a need for a PR mentor who will act as an advisor. PR practitioners have to deal with challenging situations such as tough competition, misinformation and loss of public interest in a brand.

Innovative technologies can help PR practitioners address such issues. ML is revolutionizing various industries. So why not implement it to solve PR problems as well?

Most Common PR Problems Faced by Organisations

Some of the most common PR problems faced by organisations are:

• False news - False news creates distrust amongst institutions and their audience, bringing down businesses and their reputation.
  
  
• Differing opinions - Quite often two different groups or institutions (newspapers for example) do not have the same position on a topic or debate (Brexit for instance). This leads to a polarized audience.
  
  
• Loss of faith - Due to the rise of fake news, the public is no longer interested in several brands and marketing campaigns leading to trust issues and loss of credibility.

Machine Learning to Solve PR Problems

Andrew Heyward and his co-workers from the MIT’s Media Laboratory are amongst the first researchers to use machine learning technology to solve PR problems. According to Heyward, there are several machine learning applications that can solve PR problems. Machine learning algorithms can understand vast amounts of data that humans cannot analyse on their own by analyzing large datasets. Heyward’s group uses machine learning algorithms as their primary tool to map and track the overall health of the public sphere. 

Machine learning algorithms can analyze massive amounts of data from multiple sources. This helps in mapping market trends accurately. They can also predict audience preferences by recommending advertising campaigns that will have a positive impact on consumers. Thanks to large dataset gathered from social media platforms, machine learning can predict an audience’s areas of interest, helping PR mentors work on these preferences accordingly.

By finding common factors that connect polarized groups, it is now possible to create PR campaign that can unite people. Machine learning can also handle catastrophes and scandals. Heyward and his teams were also able to prevent PR crises by predicting several realistic outcomes. 

ML can predict the length and depth of a crisis, providing insight around which rumours are spreading and which are likely to be disproved. Andrew Heyward and his team were able to successfully analyse upcoming critical situations and make recommendations. Machine learning may be the cure to the current fragmented business environment.