Big Data Analytics, in layperson terms, can be defined as the intricate task of untangling and examining the data accumulated from various sources (organizations, websites, etc.) in an attempt to discover patterns, trends, and correlations in the same. The insights derived can be extremely valuable for businesses as they can then make important growth decisions based on the same.
For instance, in 2015, Coca-Cola strengthened its customer retention strategy with the help of big data analysis through a loyalty program. Netflix is also known to use it for its personalized recommendations and targeted advertising efforts by studying the behavioral data it collects.
Today, we would be focusing on the how to’ part of using Big Data. But before we move on to that, let’s take a quick look at the why’ as well.
Why Is Big Data Analytics Important?
Reaching an understanding of why we insist on analyzing a vast data mine is of crucial significance. Unless we realize why an act is being done, it cannot be carried out optimally and data analysis is not a place where you’d want to be any less than thorough.
Following are some of the reasons that make data analytics as important as it is.
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Realistic Goal Setting: Ambitious yet attainable goals can be set according to the market conditions and the company’s own standing, backed by the data.
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Effective Marketing: The efforts put into marketing and promotional activities can be more target-oriented and personalized, thus being more effective than generic hit-and-miss.
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New Revenue Opportunities: Unexplored potential markets can be discovered and aimed for, thus uncovering new business growth opportunities.
How To Leverage Big Data Analytics?
For many companies, success with big data analytics is often limited. This is due to the lack of know-how about how to use data optimally for better business decisions and results.
But while every organization has its own ways of going about it, here are three key ways to start gaining some amazing results with big data analytics for your business.
Marketing and Targeted Advertising
Although analytics has now become the heart and soul of marketing activities, its entry into the industry can be traced back to the period where companies began realizing what ideas enticed the consumer towards their products and services.
Ever since then, data analysis has been used for several purposes, from A/B testing to experimenting with new marketing channels. Gaining a deeper understanding of the markets as well as the potential and existing consumers also helped focus the advertising efforts in a more targeted manner.
For instance, big data analytics can help provide insights on what particular customers are most interested in, and that information can be used to target them with more personalized email campaigns.
Analyzing customer behavior and buying patterns for enhanced personalization is now a favorite of marketers around the world. In eCommerce, search intent analysis also enables marketers to devise stronger eCommerce SEO strategies.
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HR and People Analytics
Admittedly, information on consumer behavior is of significant importance as we discussed above. However, data about the efficiency, wellness, and welfare of employees working in your organization is also vital to creating a productive and happy work environment.
When used in the human resources department, data analysis can help in a wide range of tasks ” sorting qualified resumes, keeping a track of the impact of training provided, and collecting performance data of the workers alongside their pain points ” to name a few. By figuring out and resolving your employees’ problem areas, you not only help your staff out of a bottleneck but also enable them to focus on crucial tasks by freeing up their time.
Qlik and Visier are two tools that can assist you with this process.
Supply Chain
Out of the three main entities in any business transaction, we have covered the use of data analytics for two. Now comes the third one, your vendors and suppliers.
Supply chain management has always been a complex activity and even though the traditional ways have come a long way, they can still be improved significantly using big data analytics.
For example, with the predictive analytical models, a supplier can monitor their inventory along with determining the chances and timeline of potential delays in delivery and preemptive replenishment, if any. The supply routes can also be optimized which can prevent them from suffering major losses.
Modern supply chain systems based on big data allow for more complex B2B supplier networks. PepsiCo is one of the major market players that relies on data analytics for an efficient supply chain management process.
Closing Thoughts
As a business owner, what ultimately matters is the fact that your enterprise is on track for growth, and an assurance that it will continue to do so in the future.
Big data analytics is an important enabler for that, so it’s time to start leveraging it for your business.
