Digital marketing

In the early phase of digital marketing marketing efforts were wasted and marketers had to spend sleepless nights thinking as to where their strategy went wrong and how to push forward with their efforts. Later on after the growth of various analytics platforms there was a greater ability for the marketers to measure the effectiveness of the campaigns as well as to fine tune the campaigns.

Metrics and dimensions like click through rates, bounce rates, visits have all come into place and marketing has become more disciplined and analytical. And often excel and GDocs have become primary tool of choice for reporting.

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What is Big Data Analysis?

As the user base on internet started to grow marketers was able to choose which spectrum to use for marketing like SEO, PPC, Social Media, Affiliate marketing, E-Mail marketing etc. Now along with it comes the rise of digital marketing and the data from huge variety of sources has led to the era of Big Data. This data includes engagement, visitor behaviour, search rankings, conversions, leads, and click data etc. which can provide tremendous insights and business intelligence.

For example : 10 years back I had a small collection of photos (taken when I was young) and have assembled it in an album but as I got older the collection kept getting bigger, soon I had to get he'll loads of albums. It used to take a lot of time to look over it and to refresh my memories.

But now we are using a digital camera which can shoot pictures instantly without missing a moment adding to that they are also able to store the pictures and now viewing the pictures has become extremely easy.

Big Data is almost the same thing.

Big Data analysis as the name suggests relates to analysing large data sets (like the ones mentioned in the first paragraph) which can help an organization to underpin new growth areas & innovation, check competition, consumer analysis, sentiment analysis, brand coverage etc. The increasing complexity of volume of analytics data captured by an online marketing company and the rise of digital media, social media and other platforms has fuelled the growth of data that can help an organization to foresee the future of the brand online.

Big Data Dimensions

Big data spans four dimensions: Volume, Velocity, Variety & Variability. Let us take a look at these dimensions in details.


Organizations are now flooded with data every day in the form of terabytes and even petabytes of information. For example you can turn terabytes of tweets created to improved sentiment analysis.


Velocity can be simply described as the pace at which the data is generated and consumed. As the volume of the data keeps increasing the data points will have a tendency to diminish over time.


There are various levels of data complex data, structured & unstructured data such as text, audio, clicks etc. and this complexity has always been a matter of concern for traditional analytics.


Variability refers to methods through which this data can be interpreted and how this answers different questions and interpretations.

Big Data Concept A Deeper Look

Big data is a hypernym for the explosion of the quantity of high frequency data. This data holds the potential for marketers to track the development progress, increase social exposure and to understand the campaigns and programs that require adjustments.

Converting the Big Data like call logs, mobile-banking transactions, blogs, social networking trends, search queries, images, videos etc. in actionable information will require the use of computation techniques and tools. This means that leveraging various tools developed by multiple organizations will be required to reveal trends and patterns. The real time information gathered through such data mining can be used by companies for gathering survey data, human behaviour and statistics.

The computation techniques may rely on powerful algorithms that will be able to detect patterns, trends from various sources and offer an advanced visualization of things. The algorithms will then be able to evolve itself integrate the information (even real-time) and will help make predications based on trends.

Harnessing the power of Big Data is not new there are already many evidences of using the data beyond the field of science. Google Flu Trends is one example of it; this tool launched by Google is based on search queries for flu like symptoms. A research paper has found that it was able to accurately detect epidemics based on web searches.

Another example would be an experiment by few computer scientists based on analysing 1.6 million tweets posted in US between May 2009 & October 2010. Another example has proved that Facebook posts and updates can help to identify drinking problems among the youth. The main difference between the social networking giants is that Facebook is closed network and twitter tweets are public and can be accessible for analytics.

What Big Data means for Digital Marketers?

With Big Data online marketers needs to evolve themselves from web analyst to digital analyst and extend their focus from website centric to channel specific strategy. The more we concentrate on the channel points the more strategic and business oriented we get, but since the website is the core of digital space don't forget your website details as well

Mastering the tools for effective analysis is extremely important and even though we are masters of leveraging the web analytics tools we need to be familiar with tools that offer broader business intelligence. A digital marketer should be able to identify all forms of data such as social media, call centre logs, emails, clicks and social sentiment analysis.

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Posted in Marketing and Advertising Post Date 02/15/2017