.
As artificial intelligence and machine learning technologies approach the forefront of groundbreaking new transformations, social media and the algorithms it uses to generate user media feeds will ultimately become more personalized and precise for both individuals and businesses, and truly scalable social media advertising may soon become a reality. However, as social media platforms continue to change these dynamics, two questions should be raised: will businesses be able to keep up with these increasingly complex algorithms? And is social media really necessary to the growth and success of future businesses?
While the recent changes in social media algorithms across platforms such as Facebook, Twitter, Instagram and LinkedIn may have many businesses scrambling to change the methods by which they target audiences, these changes may prove to be quite beneficial for businesses in the long run. Balancing post timeliness with personal relevance, the algorithms created by data scientists are becoming increasingly precise and personalized—though the approach to this balance differs from platform to platform. While Facebook has traditionally been the most business-friendly social media platform, for example, recent changes in its algorithm have prioritized meaningful interactions over a more chronologically driven timeline. In order for brands to appear more frequently, it is crucial to prioritize content that triggers engagement—not just through likes, reactions and shares, but also through healthy discussion in the comment section.
Similarly, Twitter puts post relevance before timeliness, placing tweets users are most likely to want to see—based on past interactions with different Twitter accounts—at the top of their feed. Twitter’s search function has also begun to optimize machine learning that works to bring anyone using the search function diverse yet relevant results by balancing the number of tweets, accounts, videos and pictures that appear when certain keywords are searched for. LinkedIn’s algorithm also presents updates by individual relevance, using factors such as a user’s personal identity, engagement and behavior on the website to bring users as much relevant content as possible. LinkedIn’s algorithms analyze aspects such as time spent reading and user experience research to continually improve their machine learning algorithms.
Unlike other social media platforms, however, Instagram’s chronological timeline prioritizes newest posts first—meaning that post timeliness and time of distribution are the most important factors to a business’s success on Instagram. Interestingly, a recent study from SocialBakers reveals that brands are getting three times more engagement on Instagram than Facebook, perhaps due to the fact that Instagram’s user base appears to be fairly brand-conscious, with 53 percent of users following brands. With 100 million new users last year alone and 800 million monthly users, Instagram is emerging as a fierce competitor for Facebook and a potential new home for both startups and established businesses.
On a general level, transformations in social media algorithms reveal several trends that are shaping the social media landscape today. First, videos appear to not only be the future of social media, but the Internet in general, with Cisco forecasting 82 percent of all consumer Internet traffic in 2018 being used on videos. With the promise of scalable and targeted advertising for businesses in particular, nearly half of all companies are already implementing social media videos, with another 26 percent planning to implement videos into their social media agendas within the next year. However, it is crucial for businesses to remember that it is undeniably more important to target customers who will actually engage with them and their products rather than simply focusing on going viral.
Perhaps most encouraging of all for businesses, many of the tasks that have troubled businesses in the past—such as scheduling optimal posting times and locating relevant content to share with audiences—are becoming increasingly automated by advanced machine learning algorithms. Emerging technology that enables the testing of hundreds of social media ad variations simultaneously, for example, has becoming a promising future tool by which businesses can increase the success of their social media ad campaigns dramatically. By automating campaigns so that the best performing posts are automatically boosted to the biggest audience, a vast amount of the guesswork that businesses had to deal with in the past is being taken away and replaced with algorithms that can seemingly solve the guesswork in mere milliseconds—and with more accuracy and precision than human scientists have been able to accomplish thus far.
In addition to more targeted social media ad campaigns, artificial intelligence also has the ability to increase a business’s efficiency in a plethora of other ways. In order to improve customer experience, for example, companies are increasingly implementing the use of chatbots on their websites to help customers with questions and even assist with picking products based on personal preference. Similarly, companies can use machine learning to analyze customer behavior and identify when customers are about to churn in order to entice customers to stay using special offers, check-up emails and similar methods. Artificial intelligence also has the ability to help businesses with dynamic pricing in order to allow companies to become more agile and respond more accurately to fluctuations in supply and demand. Lastly, artificial intelligence has become increasingly adept at generating content such as article titles, simple content generation and even lengthy data-driven reports.
Ultimately, the increasing sophistication of artificial intelligence, machine learning and complex algorithms is beginning to allow businesses to reach their customers in a truly meaningful and personalized way the likes of which have not before been possible. While social media feeds will continue to see radical change as artificial intelligence advances, it is important for businesses to keep up with this transformation. And while the overall impact of artificial intelligence and machine learning on social media still remains somewhat unknown, it is undeniable that social media will have the profound ability to lead businesses to unique insights and new levels of success.
The views presented in this article are the author’s own and do not necessarily represent the views of any other organization.
a global affairs media network
How Social Media Algorithms Are Transforming Global Business
June 25, 2018
As artificial intelligence and machine learning technologies approach the forefront of groundbreaking new transformations, social media and the algorithms it uses to generate user media feeds will ultimately become more personalized and precise for both individuals and businesses, and truly scalable social media advertising may soon become a reality. However, as social media platforms continue to change these dynamics, two questions should be raised: will businesses be able to keep up with these increasingly complex algorithms? And is social media really necessary to the growth and success of future businesses?
While the recent changes in social media algorithms across platforms such as Facebook, Twitter, Instagram and LinkedIn may have many businesses scrambling to change the methods by which they target audiences, these changes may prove to be quite beneficial for businesses in the long run. Balancing post timeliness with personal relevance, the algorithms created by data scientists are becoming increasingly precise and personalized—though the approach to this balance differs from platform to platform. While Facebook has traditionally been the most business-friendly social media platform, for example, recent changes in its algorithm have prioritized meaningful interactions over a more chronologically driven timeline. In order for brands to appear more frequently, it is crucial to prioritize content that triggers engagement—not just through likes, reactions and shares, but also through healthy discussion in the comment section.
Similarly, Twitter puts post relevance before timeliness, placing tweets users are most likely to want to see—based on past interactions with different Twitter accounts—at the top of their feed. Twitter’s search function has also begun to optimize machine learning that works to bring anyone using the search function diverse yet relevant results by balancing the number of tweets, accounts, videos and pictures that appear when certain keywords are searched for. LinkedIn’s algorithm also presents updates by individual relevance, using factors such as a user’s personal identity, engagement and behavior on the website to bring users as much relevant content as possible. LinkedIn’s algorithms analyze aspects such as time spent reading and user experience research to continually improve their machine learning algorithms.
Unlike other social media platforms, however, Instagram’s chronological timeline prioritizes newest posts first—meaning that post timeliness and time of distribution are the most important factors to a business’s success on Instagram. Interestingly, a recent study from SocialBakers reveals that brands are getting three times more engagement on Instagram than Facebook, perhaps due to the fact that Instagram’s user base appears to be fairly brand-conscious, with 53 percent of users following brands. With 100 million new users last year alone and 800 million monthly users, Instagram is emerging as a fierce competitor for Facebook and a potential new home for both startups and established businesses.
On a general level, transformations in social media algorithms reveal several trends that are shaping the social media landscape today. First, videos appear to not only be the future of social media, but the Internet in general, with Cisco forecasting 82 percent of all consumer Internet traffic in 2018 being used on videos. With the promise of scalable and targeted advertising for businesses in particular, nearly half of all companies are already implementing social media videos, with another 26 percent planning to implement videos into their social media agendas within the next year. However, it is crucial for businesses to remember that it is undeniably more important to target customers who will actually engage with them and their products rather than simply focusing on going viral.
Perhaps most encouraging of all for businesses, many of the tasks that have troubled businesses in the past—such as scheduling optimal posting times and locating relevant content to share with audiences—are becoming increasingly automated by advanced machine learning algorithms. Emerging technology that enables the testing of hundreds of social media ad variations simultaneously, for example, has becoming a promising future tool by which businesses can increase the success of their social media ad campaigns dramatically. By automating campaigns so that the best performing posts are automatically boosted to the biggest audience, a vast amount of the guesswork that businesses had to deal with in the past is being taken away and replaced with algorithms that can seemingly solve the guesswork in mere milliseconds—and with more accuracy and precision than human scientists have been able to accomplish thus far.
In addition to more targeted social media ad campaigns, artificial intelligence also has the ability to increase a business’s efficiency in a plethora of other ways. In order to improve customer experience, for example, companies are increasingly implementing the use of chatbots on their websites to help customers with questions and even assist with picking products based on personal preference. Similarly, companies can use machine learning to analyze customer behavior and identify when customers are about to churn in order to entice customers to stay using special offers, check-up emails and similar methods. Artificial intelligence also has the ability to help businesses with dynamic pricing in order to allow companies to become more agile and respond more accurately to fluctuations in supply and demand. Lastly, artificial intelligence has become increasingly adept at generating content such as article titles, simple content generation and even lengthy data-driven reports.
Ultimately, the increasing sophistication of artificial intelligence, machine learning and complex algorithms is beginning to allow businesses to reach their customers in a truly meaningful and personalized way the likes of which have not before been possible. While social media feeds will continue to see radical change as artificial intelligence advances, it is important for businesses to keep up with this transformation. And while the overall impact of artificial intelligence and machine learning on social media still remains somewhat unknown, it is undeniable that social media will have the profound ability to lead businesses to unique insights and new levels of success.
The views presented in this article are the author’s own and do not necessarily represent the views of any other organization.
