What is Big Data and What Are its 3 Big Benefits for Marketers? By Stevie Langford | 16, January 2020 Data. It’s a word that’s ever-present; that we just can’t ignore, especially now that we’ve entered the (new) roaring 20’s. That’s right, 2020, and beyond, is a decade that people have anticipated, dreamt of and made crazy predictions about for a long time… like forecasting that 2020 would be the year where humans evolve from having five toes to just one, large toe. Wow. Fortunately, Richard Clement Lucas, the 1911 surgeon who predicted this didn’t quite hit the mark.
Whilst this prediction is good for a giggle, the majority of speculations for the year 2020 onwards center around technology, and it’s clear to see why. Huge digital advancements like Artificial Intelligence, Virtual Reality, and Digital Voice Assistants are already rife and a normalized aspect of our lives. Most people have their smartphones with them at all times, meaning we have 24/7 access to search engines like Google.
There is now an incomparable wealth of information right at our fingertips. And it’s all thanks to big data.
What is big data? Essentially, big data refers to huge sets of raw data, both structured, semi-structured and unstructured, that can be utilized and analyzed by organizations in order to draw actionable insights and aid strategic decision making. Or, as Gartner puts it: ‘Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.’
‘Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.’
Big data is easiest to understand in terms of the ‘3 Vs’: Volume, Velocity, Variety.
Volume The amount of data that there is.
Volume is what first comes to mind when we hear ‘big data’ and it’s no surprise because the amount of data at present is almost incomprehensible, and it’s growing continually. Take Facebook, for example; Facebook recently revealed that an average of 350 million new photos are uploaded each day, that’s 14.58 million picture uploads per hour. And there are no signs of this slowing down.
Velocity The speed at which data is generated.
There’s more data now than ever before. The constant stream of data is due to the rapid growth and popularity of social media channels, peoples’ growing inquisitiveness and therefore reliance upon search engines, advanced research capabilities, rapidly generating UIDs (Unique Identifiers) and then, of course, the IoT.
Side note… what is IoT?
The IoT stands for the Internet of Things. It refers to anything that is connected to the internet or devices that are integrated with technology, such as sensors or functional software. The IoT varies greatly from smartphones, smart, wearable accessories and digital home assistants, like the Amazon Echo, to devices that track your dog’s health. And yep, you guessed it, they all generate and add to the unquantifiable wealth of data that is big data.
Thanks to phenomenons like the IoT, the growth of big data now has such momentum that it requires distinct processing techniques, which is one of the primary things that separates it from regular data.
An example of high-velocity data would be the 3.5 billion searches that are conducted on Google, the 0.4 million hours of video are uploaded on Youtube or the 500 million tweets that are posted on Twitter - and that’s just on a daily basis!
Variety The mixture or variation of data.
When we describe different varieties of data we mean they have come from one of 3 types: structured, unstructured data or semi-structured:
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Structured data tends to be the simplest to group and analyze, it accounts for things like demographic data, accounting transactions or location data from smart devices.
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Unstructured data is tougher to collect and analyze as it doesn’t follow the same, row-column model as structured data and requires different processing methods. Unstructured data describes everything from photos, videos and social media content to website content, open-ended survey responses and call center transcripts, for example.
However, with great advancements like Artificial Intelligence and Machine Learning, unstructured data can now be automatically processed with distinct algorithms and utilized as a valuable resource for organizations globally.
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Semi-structured data is essentially a mix of the two. It doesn’t offer the same predictability or ease of analysis as structured data, but it’s not as raw and diverse
as unstructured. Emails, Zip fi les, and CSV fi les are all examples of semi-structured data.
Each of these distinct and varied data types requires a different means of processing.
So, whether you’re a doctor publishing an article which offers new insights into biomedicine, an Instagram user uploading a cute picture of your dog, someone who is sending emails to top retail clients or simply someone who has made a note on their phone to buy bread later, it’s all data. It’s all data that can be collected, analyzed, utilized
or stored in one way or another.
Have you ever wondered why when you search for a product on Amazon, it then appears as an ad on Facebook? That’s remarketing. Which is only possible because, you guessed it, both Amazon and Facebook have collected your data and distributed it accordingly.
So now that you know what big data is, here are 3 big benefits for marketers:
Like standard data, big data is just masses of information. But this information can be utilized by brands and marketers to draw actionable insights that impact, inform and streamline business strategies for the benefit of both brand and consumer.
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Optimized decision-making
Big data offers a wealth of consumer insights that allow for things like predictive analytics. By analyzing consumer data, particularly behavioral, businesses are able to plan, predict, and make informed decisions for the future based on the past actions of their users.
Predictive analytics analyzes historical data which enables the consumer insights that predict the future behaviors of target consumers and their responses to brand actions and offerings. The optimized decision-making that big data enables aids customer acquisition and retention and guides marketing strategies and meticulous market segmentation based on in-depth and vast behavioral data and insights.
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Advanced user experience (UX)
Organizations are able to discover how users and consumers view their brand through particular sources of big data, such as social media, online reviews, and sentiment analysis.
Being aware of user experiences and comprehending a target market’s perception and attitude means organizations understand what they’re doing right. Similarly, these processes help to uncover what users think they’re doing wrong, and/or how they can make improvements to their products, services, and therefore, UX. Aside from improved user experience, big data allows organizations to influence brand affinity and online reputation. Brands can utilize the insights gained through big data analysis to alter aspects of their brand such as how they communicate, their actions, their products, and their content, etc.
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Improved product development
The wealth of big data available today means that brands can pinpoint exactly what is and isn’t working in their own company and the wider market. It also means that brands are able to better understand current market conditions: by analyzing big data, and identifying patterns, you can clearly understand the market trends which guide the actions of organizations, enabling them to be disruptors in their market and to get ahead of their competitors.
So, in gaining a deeper understanding of the market and competitors, big data paves the way for innovation, disruption, and modernization. Big data can also predict potential bad decisions or failures so that organizations can develop their brand and products without the worry of making mistakes.
“Deep learning craves big data because big data is necessary to isolate hidden patterns and to find answers without over-fitting the data. With deep learning, the more good quality data you have, the better the results.” Wayne Thompson SAS Product Manager
Source: SAS
Conclusion
Big data is constantly being generated from a multitude of sources, and each piece of data contains valuable insights that have the power to positively change the success of a brand; their place in the market, their efficiency, brand perception, and overall performance.

In a fast-paced, ever-changing society, big data stimulates companies and helps them to decipher random information for the benefit of both the brand and their customers. Its power to achieve intelligent, actionable insights is unparalleled, and it’s important for marketers and organizations globally to utilize this advantage.Â
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