The term Big Data has created a lot of hype already in the business world. Chief managers know that their marketing strategies are most likely to yield successful results when planned around big data analytics. For simple reasons, use of big data analytics helps improve business intelligence, boost lead generation efforts, provide personalized experiences to customers and turn them into loyal ones. However, it’s a challenging task to make sense of vast amounts of data that exists in multi-structured formats like images, videos, weblogs, sensor data, etc.
In order to store, process and analyze terabytes and even petabytes of such information, one needs to put into use big data frameworks. In this blog, I am offering an insight and analogy between two such very popular big data technologies – Apache Hadoop and Apache Spark.
Let’s First Understand What Hadoop and Spark are?
Hadoop: Hadoop, an Apache.org. Project, was the first big data framework to become popular in the open source community. Being both a software library and a big data framework, Hadoop paves the way for distributed storage and processing of large datasets across computer clusters using simple programming models. Hadoop is a framework composed of modules that allow automated handling of common hardware failure occurrences…read full blog here- Apache Hadoop vs Apache Spark: Two Popular Big Data Frameworks Compared
People are looking for information (read products and services) all across the web. You, as a salesperson might have an offering but the problem is – what are the chances that the person interested in it will find you and reach across to you? Frankly, the chances are quite less. So what do you do to increase your chances to make a sale? Well, obviously the best thing you can do is to find and reach across to that person before he decides to give his money to someone else. But how to do that? Traditional lead generation methods are only so effective as to give you an excuse of an alternate to shooting in the dark. The generated lead data is limited, the windows are short, the targets are big, the work is harder and the results are uncertain. The conversion rates can well be compared to the conversion rate of a toiling army of bees for one drop of honey.
A decade ago, most salespeople would agree that the traditional methods only took them so far in terms of conversion rates. The data was too limited or redundant and took too long to accumulate but the silver lining, if we can call it that, was that because it was too little, it was easy to process. You got 30 leads, you go and do your salesperson thing with 12 based on some quick prospecting/scoring and depending on how good or lucky you are, you score a couple.
Then five years ago to until recently, salespeople were agreeing that the contemporary methods with the power of web and social media, brought improved capabilities in data acquisition and reach but still something was keeping them from milking that cow. You’d think with all that talk about shrinking degrees of connection, businesses increasing their online presence and all, you’d be better off than mere 3% growth.
Yes, something was definitely missing from the picture. And that something was to do with this – “Having access to a lot of data means nothing if you don’t have a way to utilise it…to its full potential.”.. Know more about- How Will Big Data Impact Effective Lead Generation for better Conversions?