Every now and then when we think the dust rose due to the stampeding by the excited marketers searching for Holy Grail is finally settling down and new innovation starts making sense, somebody introduces a new terminology and the rush begins all over again. This has happened one more time with something called “Big Data”, which has an implication for social media as well. So it is but natural that I should tackle this issue and help you see the real picture behind this new buzz word, and in turn help you make use of it in your business.
What is big data?
As Wikipedia puts it, “Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications.”
Big data refers to massive volume of structured and unstructured data which is expanding on three sides as shown in the image below.
The currently used definition of big data was proposed by Doug Laney in 2001. He proposed the 3 Vs of big data: Volume, variety, and velocity, and estimated that worldwide information is growing on at 59 percent annually, on the least.
How big is big data?
Are you aware of terms like petabyte (PB) and exabyte (EB)? Do you know how big is that? One exabyte is 1024 petabyte, and one petabyte is 1024 terabyte, and 1 terabyte is 1024 gigabyte. This is how big a exabyte or a petabyte is. And big data is as big, if not bigger (which hardly is the case), it is.
Is it a good or a bad news?
Like everything else, it depends on how you take it. Big data can be a boon for business (and also for social media campaign) if harnessed effectively, but if it is not used to its capacity, collecting it, storing it, and maintaining it can be a very, very expensive affair. To help you understand its business use, an example of the way eBay uses big data should be sufficient. eBay uses big data for search, merchandising, and customer recommendation using 90PB data on consumer transactions and behaviour on its websites across the globe. The shopping giant stores the data on 3 systems: in 7.5PB and 40PB warehouses, and 40PB in commodity Hadoop. The company is using big data to build a customer-friendly shopping ecosystem to assist its customers buy the things they want.
How does it affect social media?
As pointed above, big data is a massive collection of data from various sources (variety) coming at various speed (velocity), and in various quantity (volume), and social media websites are collectively responsible for adding massive chunk of data of all three kinds to the big data pool. But unlike other data sources, information produced and collected by social media websites are unstructured, and it is so enormous in volume that it is not humanly possible to collect, process, and manage such a huge set of unstructured data. It even falls out of range of commonly used software applications. But the scenario is not all that bleak. There are tools to help you make sense of onslaught of messages sent to and fro on various social media platforms by bringing all together and providing a structure to it, and making it useful for marketers.
Every day social media is abuzz with communication around brands. Thousands and thousands of likes are recorded, comments posts, tweets and retweets sent out, chick-ins on Foursquare, image clicked and shared on Instragram, posts curated and pinned on Pinterest, video shared, viewed, liked, and left midway, to name a few things that social media adds to the variety of big data, and what makes analyzing these so complicated is the absence of any tagging system to make it readable even within a state-of-the-art marketing analytics software application.
If you want to get a glimpse of how confusing it can be, go through a twitter feed of any popular brand, and also to its Facebook page among other social profiles (variety in big data) should you wish to be more confused, and then try to make sense of this all from a marketing point of view. And here we are just talking about making sense of an instance of spontaneously generated, untagged, and uncategorized data churned out. What will it be like if we factor in all the data which was generated before now, which will generate hence forth! Add to this the data being generated now, as you read this, in real time (the velocity aspect of big data).
3 Vs of big data vis-à-vis social media
Variety: The variety aspect of big data in context of social media means what kind of data has been shared by the users: is it a like or a tweet or a comment or a share? Is it an image or a video or text or an audio clip or check-in or GPS location or combination of some of them? Has it been shared on Facebook or twitter or Google Plus, or YouTube or Foursquare or Pinterest or shared on more than one places?
Velocity: Velocity in this context may refer to the following: is it real time or near-real time data? Is it one-time or repeated event? Has it been shared as part of a batch or has it been shared as a standalone?
Volume: Volume refers to how many units of data has been shared, or how much has been shared?
Some facts about big data and social media
- Facebook takes in 500 times more data each day than the New York Stock Exchange. (Source: BI Intellegence)
- Twitter produce 12 times more data each day than the New York Stock Exchange. (Source: BI Intellegence)
- Facebook tracks every computer IP a user has logged in from, and other users who have logged before and after you from the same computer up to 800 pages size of data per users. (Source: com)
- More than 4 Billion hours of videos are watched on YouTube each month. (Source: IBM Big Data Hub)
- More than 30 billion pieces of content is shared on Facebook each day. (Source: IBM Big Data Hub)
- By 2016, there will be 18.9 billion network connections, i.e., 2.5 connections per person. (Source: IBM Big Data Hub)
How big data helps in social media marketing
In the wake of changes brought in by big data, a brand needs to stop hiring a college student, and fresher to curate its twitter feed or Facebook timeline, or any of its social profiles, for that matter. The brand also needs to stop guesstimating the future course its prospects and consumers will take and waste money based on that. Instead a brand should look for more and more data on its customers and prospects, other than what they share with you through their various interaction. In this, big data can help you a great deal. It can help you find out:
Who buys from you?
This is as relevant as relevancy goes. In order to build a relationship and foster loyalty, the first and foremost thing you need to know is who is your customer, and that too not only in the demographic sense as suggested by market segmentation strategy of yore. Market segmentation is not sufficient anymore. Now you need to know more about your buyers’ preferences, places they hang out at, the things they talk about, the issues they are concerned with, the topics that excites them, etc., to target messages better on social media.
How your customers feel?
It is not just the customers’ life that you should be interested in. In order to make your messages more useful for your brand and your customers you also need to gauge customers’ sentiment around your brand and your competitors. Big data can help you understand your customers’ sentiment about your brand as well as your competitors.
What they want?
This is one thing every brand tries to get a definite answer of. And I am not saying harnessing big data can give you a definite answer, but it will give you a much clearer picture of your customers’ needs and wants than you can get from any other source. By tapping into their interactions, things they talk about, things they say, products they buy, and places they visit, etc., big data can be help you estimate your customers’ demand.
How do they satiate their information need?
By harnessing big data you can know a great deal about how your customers get the information they need. An understanding of the information sources your customers use to seek information you need, you can wisely select the vehicle to send your marketing message, and fine tune your message to match the vehicle and mood of your customers.
How do they arrive at the buying decision?
The most important information a marketer wants is the knowledge of the process its customers took right from the 1st stage in the buying cycle; from gathering information to shortlisting product options to evaluating alternatives to shortlisting items to buy from to finally making the decision, and then its post-purchase interaction with the brand. This is a gold mine of information, and an access to it will help a marketer fine tune its social media marketing campaign at each stage of customers’ buying cycle.
Should You use big data for your campaign?
To answer this question, you need to ask the following questions and if you find the answers of these questions be yes than you most definitely need to seek help of big data for your marketing campaign.
- Do you want to know how your customers feel about your brand?
- Do you want to get insight from and also look beyond the internal sources you used to collect data (like survey, purchase behaviour, customer interaction, etc.) to understand your customers’ sentiment?
- Do you want to boost customer loyalty by giving them more than what they want now?
- Do you want to tap into your customers’ latent needs and wants and address them before any other brand does and thus build loyalty?
- Do you need more information about your customers than the ones that are available to you now?
- Do you want to know what your customers do when they are not interacting with you in any manner?
- Do you want to know where they go, what they eat, and what they like to talk about?
Big data is going to be a big business, which means ignoring them is not going to be a healthy decision. It will not be wrong to posit that the more you learn about your customers the better you will be able to target them with your social media campaign, and seeing the gigantic size of data produced by various social channels, it becomes imperative that you make use of big data in your social media marketing campaigns. By giving you a far deeper understanding of your customers and their relationship with your brand, big data will help you fine tune your social media messages, and choose the right social media platform to disseminate information.