The social media industry has grown leaps and bounds in the past decade, but some challenges have persisted. Major networks such as Facebook have struggled to meet revenue targets. Facebook’s IPO stock price was based off revenue growth figures that have failed to materialize over the past few years, raising concerns that the site couldn’t monetize its users as well as analysts hoped. Companies utilizing social media have also had trouble customizing their messages to the right demographics.
The social media industry has grown leaps and bounds in the past decade, but some challenges have persisted. Major networks such as Facebook have struggled to meet revenue targets. Facebook’s IPO stock price was based off revenue growth figures that have failed to materialize over the past few years, raising concerns that the site couldn’t monetize its users as well as analysts hoped. Companies utilizing social media have also had trouble customizing their messages to the right demographics.
Social networks are addressing these challenges through the inception of big data. They are collecting as much information as possible not only on user demographics, but also on user engagement. The algorithms built on big data will revolutionize the social media industry in ways pundits never predicted.
The Growing Role of Data Science in Social Media Business Models
While social media engagement has surged in recent years, profitability has barely budged. Monetization has been the core focus for Facebook, Twitter and other leading social networks. Big data may be the savior they have been searching for as they strive to maximize the revenue of their ever growing user base.
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Big data has been a game changer for many industries over the course of the past few years. The market for Advanced and Predictive Analytics (APA) software industry was over $2.2 billion in 2013 and is expected to rise to $3.3 billion within the next two years. Algorithms relying on big data are playing an especially important role in global businesses.
Ironically, the social media industry has lagged others in adapting big data. Pinterest and auto instagram likes took a major step towards using big data this past year. Pinterest began developing a business model that involves selling pins for users wishing to expand the reach of their content.
In order to launch their new monetization strategy, Pinterest acquired significant data via new user registrations. They also kept close track of user engagement metrics to develop policies for the new program. Data will help them ensure that the paid pins model will be viable for marketers without diminishing the user experience.
Instagram released a similar model shortly thereafter. They created a new system that allowed users to purchase items that were listed on Instagram. Items are tailored to the interests of different user demographics, giving the site a significant edge over most other publishers offering media buys to advertisers.
Allowing Brands to Tailor their Messages
Many brands serve multiple demographics, which makes it difficult for them to deliver a uniform message that resonates with every customer. Helena Schwenk, principle analyst at MWD Advisors, told Forbes that big data has allowed them to create customized messages that appeal to the whims of their customers through social media.
“[Employees] need to respond in a proactive and timely manner on the social channel of choice and be able to tailor the communication or content that they provide to different audiences with the right reply, the right response, the right content and the right tone of voice,” said Schwenk.
Facebook currently has 1.49 billion active users. This gives marketers access to a huge pool of potential customers. However, the ability to narrowly target their demographic is arguably even more important. Facebook has been collecting data on their users for years, giving marketers more control over the delivery of their messages.
Challenges With Big Data
Social networks will be able to continue improving the user experience and the service for their marketers as they accumulate more data. However, a new report from BI Intelligence states that they still face one major flaw: 90% of the data they gather is spontaneously generated, which means that it is difficult to capture and capitalize on.
Social networks are improving their algorithms and server infrastructure to better capture data and use it to serve their customers and advertisers. Big data may be the ticket to helping them reach their monetization goals in the years to come.