One of the most important sources of Big Data for generating leads is social media. The previous two years alone have seen the collection of 90% of the world’s data, and 80% of that data originates from “unstructured” sources. Every day, massive amounts of data are produced by Facebook and other social media outlets. For your business, using big data software is crucial.

Combining social media with big data, computer program Hadoop may transform your company by generating several business scenarios. After analyzing the data, it can produce a variety of prediction trends. Big data is only useful if it conveys a narrative. You’ll be able to benefit from your data more effectively the more complete the story it conveys. While spotting a pattern might aid in better decision-making, knowing the root of the trend is much more beneficial.

Social media gives marketers a previously inconceivable perspective on a story’s life. Views, likes, shares, following, retweets, comments, and downloads are all forms of information that pertain to content. Therefore, it is important to first understand that social media and big data are not mutually exclusive.

The effectiveness with which you utilise social media and big data software solutions will determine the success of your organisation. To be useful, any analysis of social media marketing data must take into account a company’s overall market penetration, brand engagement, and other return-on-investment measures.

Predictive Techniques Using Hadoop and Social Media Data

Businesses may quickly access new data sources and use various data kinds (both structured and unstructured) to extract value from that data thanks to Hadoop. As a result, companies can utilise Hadoop to gain insightful business information from data sources like social media, email correspondence, or clickstream data.

Analysis of marketing campaigns can be done using Hadoop. Big Data supports innovative marketing tactics. One benefit of using big data is the ability to develop analysis methods that are more prognostic. This means that instead of solely relying on historical performance, marketers can now see more clearly into the future to assess the anticipated effectiveness of a strategy. This can reduce costs and aid in the creation of new strategies aimed at anticipating consumer behaviour.

Big data analytics using specialised algorithms

Large data sets can be processed and produced using the MapReduce programming model and related implementation. Individual businesses can analyse their marketing efforts in highly specific terms that are completely different from and perhaps not even relevant to their competitors thanks to customised algorithms based on customer requirements. You stop worrying about what your rivals are doing and can concentrate more on internally optimising the use of the data you already have.

New customized forms of data analytics will help SMEs (small medium businesses) with limited resources to compete on a more even-playing field with even their bigger, wealthier competitors. More and more marketing success will be measured not by the quantity of interactions with your data but the targeted relevance of it in relation to your own specific goals and objectives.

“Satisfying your clients is no longer sufficient. You must make them happy. Robert Kotler

Big Data tools can help you boost productivity, make better decisions, and cut expenses while allowing you to surprise your customers with the power of information. You can forecast customer behaviour and purchasing patterns using data. You are the only one who truly understands your clientele.