Data is the powerhouse behind every big company. Without it, you’re operating without a clear direction or set destination. In spite of this, the term “big data” is relatively new. It refers to an old concept of harnessing data and analyzing it to make better strategic decisions. Data collection sources are vast and present in every aspect of a company, from financial transactions and revenue reports to marketing campaigns and social media.
However, it’s not enough to simply collect the data – that’s only the first phase. The more complex part is interpreting it in order to uncover trends, understand inconsistencies and design strategies to improve your business. Too many companies fail to utilize the data they have to reduce costs, expand user reach and optimize product offerings.
Data Is the Driver
One of the most important types of data available is consumer data. Businesses collect this type of information at all levels when connecting with a consumer, whether it’s when a user lands on their social media page or after they make a purchase. Analyzing users’ behavior during these interactions is key in identifying potential pain points and discovering underutilized areas. Using consumer data is also how companies create predictive models for existing and upcoming products.
One good company to examine is the online streaming service Netflix. Its entire business model centers around big data. The site uses analytics from user activity to predict what users might want to watch, and updates it to match ever-changing demands. This drives everything from show and film recommendations to the creation of original series for the platform. These services are not based on intuition, but rather on the data that promotes Netflix’s growth.
Mining for Data Gold
The same concept utilized to create the prediction algorithms on Netflix also applies to marketing. Many companies have an easy market entry that allows them to grow in popularity quickly. Advertisers often rely on outdated methods that focus on broad user segments instead of bringing it down to the granular level. However, when the market becomes saturated with similar business models, it’s harder to stand out. BuzzFeed, known for producing viral content, is a great example of a lack of optimal data utilization. The internet media company failed to leverage the vast amount of data they had to increase their revenue streams. This led to a 15 to 20 percent revenue shortfall in 2017, followed by employee cutoffs and a plan to restructure their advertising department.
With data mining tools like machine learning and artificial intelligence, advertisers can now build marketing campaigns at scale that target specific users at the right time. Moreover, this is done at a much faster rate than before. While it may be difficult to keep up with constant changes in the online landscape, the insight you can obtain will prove to be invaluable.
Sustainability Through Data
The reason why many tech companies succeed in the way they do is due to the value they place on data analysis. Regardless of the type of service a business may offer, its sustainability in today’s market is highly contingent on its ability to leverage data to advance business goals. Recent studies show that almost a quarter of businesses don’t perform proper analysis on the data they have. This might be due to a lack of structure in what they wish to gain from their data.
Having specific business goals when performing data analysis is very important, as it creates a framework from which the data can be understood and analyzed. When you already have structured data in place, your unstructured data will serve as a way to support your current business model or help restructure it.
Another big obstacle that companies face with data collection and analysis is a lack of system integration. Many businesses use several software systems that do not communicate with each other, which leads to duplicate data and slow processing. The effects of this can usually be felt not only in the data, but especially in the company’s day-to-day functioning. Integrating data is a huge undertaking for a company, because it requires synchronizing data in varying formats and legacy systems. A company may also struggle with storage capacity and an unfamiliarity with data management.
With a detailed strategy that is managed by a project leader, companies can homogenize their data into one system and begin to handle inconsistencies. Ultimately, if companies continue to ignore the value that data brings, they will fall behind in doing what’s most important: meeting consumers’ needs.