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How Big Data and Artificial Intelligence are Changing Marketing

How Big Data and Artificial Intelligence are Changing Marketing

We create dizzying amounts of data every day. By 2020, in each and every second, we will generate 1.7MB of data for every person on earth. On a global basis, we’re now measuring data in exabytes and zettabytes: trillions and quintillions of bytes. Research group IDC has predicted that the world will be creating 163 zettabytes of data a year by 2025. That’s 163 trillion gigabytes each year.

Some of this data growth is driven by the increasing number of connected devices that make up the Internet of Things. IDC also estimates that in eight years’ time, an average connected person anywhere in the world will interact with other devices nearly 4,800 times per day – one interaction every 18 seconds.

By 2020, in each and every second, we will generate 1.7MB of data for every person on earth. 

This data growth reflects the changing way we communicate with each other. On average, in every single minute of 2018, Instagram users posted 49,380 photos, YouTube users watched 4,333,560 videos, and Snapchat users shared 2,083,333 snaps.

This means that much of the 163 trillion gigabytes we’ll be generating by 2025 will be marketing-related. Almost all of it will have the potential to deliver insights that can transform the human – and consumer – experience. But as the quantity of data we hold grows, so does the challenge of holding it, managing it and leveraging it.

How can Marketers Leverage This Wealth of Information to Drive Growth?

The potential that big data offers to inform better marketing decisions is infinite. Think for instance:

  • Post-sale tracking of connected products and devices to deliver insights into how products are used
  • Social media profiling to deliver insights into the needs and desires of customers
  • Social media profiling to identify potential new customers and the marketing approaches that will resonate most strongly with them
  • Demographic data that can predict how the environments in which we operate will change
  • Footfall tracking and loyalty data that can deliver insights into the consumer’s in-store experience and how it can be improved
  • New streams of competitive intelligence and competitor analysis

Given this potential, it is little wonder that data and analytics are racing up the organisational agenda.

Using Data to Maintain Competitiveness

In 2018, an IBM and Forrester report found that 45% of the C-Suite leaders questioned believed that data and analytics will be the most important factor for maintaining business competitiveness within the next three years.

Underpinning it all, of course, has to be the “big data” infrastructures that allow data to be stored cost-effectively and accessed flexibly. 

Plus, we need tools and processes in place to ensure that data is fit for purpose. As Scott Hoover, director of data and analytics at Snowflake, pointed out to Forbes magazine: “The overwhelming majority of effort a typical data scientist puts forth has to do with creating a clean data set with useful information, all before any of the compelling machine learning or statistical models can be applied. This is the part of the job that’s almost considered an art or a craft. Just like any artist or craftsperson, there’s an untold effort that largely goes unnoticed when viewing the final product.”

This requirement has made data scientists, data engineers and business analysts amongst the most sought-after positions in America, according to PwC.

But the tools for understanding the data we hold may be the most exciting source of competitive advantage of all. We are only just beginning to scratch the surface of the exciting possibilities that artificial intelligence (AI) could deliver. 

AI Facilitates the use of Big Data in Marketing

Until now, the use of AI in marketing has tended to be directed towards robotic process automation and the natural language processing used by chatbots. While their contribution to marketing efficiencies help to make customer-facing channels and back-office processes more cost-effective, the net result is doing something we can already do but cheaper.

When it comes to big data, AI promises to do something entirely new: to make sense of the lakes of data we hold to drive better insights and better marketing decisions.

For example, IBM and Forrester found that 89% of firms see a significant opportunity to drive business value by using data and analytics to improve existing products and services. 

The new capabilities of AI are helping us to make sense of ever-greater volumes of data. Scaled up algorithms and machine learning offer the potential for disruptive change.

The relationship between big data and AI is a symbiotic one. The greater availability of data, large data sets, and the emergence of new data sources is helping to improve AI models and capabilities. 

As Randy Bean states in the MIT Sloan Management Review: “Whereas statisticians and early data scientists were often limited to working with ‘sample’ sets of data, big data has enabled data scientists to access and work with massive sets of data without restriction. Rather than relying on representative data samples, data scientists can now rely on the data itself, in all of its granularity, nuance, and detail.”

At the same time, the new capabilities of AI are helping us to make sense of ever-greater volumes of data. Scaled up algorithms and machine learning offer the potential for disruptive change.

To grasp these opportunities, marketers need to work with trusted partners who can guide them through the technologies and the data to point the way to leverage our growing data sets.

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