Big Data is turning out to be a driving force of an analytical revolution in the world. Big Data is nothing but the capturing of a large amount of, and complex data related to, or useful for a firm. Now, this data captured is recorded, analyzed and worked upon to churn out better strategies for the company.
There is simply no doubt about the fact that Big Data drives the company to a better decision making. It helps to get hold of the customer interest and behavior, and capturing the customer’s interest is the first step towards curating bang on marketing and sales plans.
Big Data as we know is anything starting from the recorded data stating that a customer bought your product, or a person liked your company on any social media account. It is an extensive repository of important information. Only latest and innovative statistical tools and algorithms are used by companies to analyze the data.
Now, this is about the role of Big Data in the developing marketing and sales strategies. However, have you ever wondered how Big Data can help you in managing online reputation?
Online Reputation of a company in simpler words is the ‘image’ of the organization on digital platforms. It is the positives and negatives of the company which are floating in the market. And, it is very much obvious that every company would like to have a positive online reputation. Though, various technological tools are being developed to enable companies manage their online status, but a comprehensive study of the Big Data can help a company develop a solid online presence. Also, business these days are using the big data to douse fires online before they have a chance to spread.
Tips to manage online reputation through Big Data:
Identifying potentially risky customers
Big Data is an accumulation of voluminous amount of data as we know. Hence, it is necessary to make the full use of the diverse data captured. Through the tools and algorithms, the data scientists should be asked to find out the rate and ratio of potentially risky customers. Now, potentially risky customers are the ones who would try to hamper the company’s reputation. If we are able to identify the risky ones, we would be ready to tackle the reputation attacks. Plus, we would also be able to identify the behaviors and causes of dislike of the likely risky customers. This is going to help us in a variety of ways: Firstly, it will allow us to create a shield for the possible reputation attacks. Plus, it will also help us to reduce the negative affect by planning various ways of managing the reputation.
Identifying the risk areas
Ones we have the information about potentially risky customers, the next step is to find out the potentially risky areas. By areas we mean the platforms where the risky customers can attack our online reputation. Can be social media platforms or some of the other platforms as well. Getting information about the areas will help us to create strategies to safeguard those places, either by employing online reputation managers or by altering the privacy settings.
Identifying the competitor’s attacks
Plenty of times, the attack on online reputation is a deliberate attempt of the competitor to put you down. Though, it is not a cakewalk to find out whether the attack was through the competitor or a customer. However as we know that Big Data is a collection of great amount of information, and the right techniques can actually help to get any answers from this massive chunk of information. Hence, figure out ways to distinguish between the potentially risky customers or the competitors. This will help the company largely to take actions against the competitor, plus, will enable the business to determine workable strategies to tackle with a risky competitor.
Of lately, people have started realizing the need, and the importance of Big Data analytics consulting. Though, we have various theories proving the fact that ‘Big Data’ is a game changer in churning out efficient marketing and sales plans, but soon, companies have started realizing that Big Data can help them manage their online reputation as well. Therefore, with proper evaluation of related data points, companies can devise plans to strengthen their online presence!
Business Analyst / Business Intelligence Analyst as well as Experienced programming and software developer with Excellent knowledge on Hadoop/Big data analysis, Data Warehousing/Data Staging/ETL tool, design and development, testing and deployment of software systems from development stage to production stage with giving emphasis on Object oriented paradigm. James can be reached at[email protected]