How to Use Data to Craft Valuable Web Content

Big Data creates a wealth of opportunities for organisations, with an abundance of information available to help with marketing and sales. This treasure trove of data is changing the way in which we all do business. In this short guide we will explore the implications of Big Data and advanced analytics for your organisation.

Since the dawn of mainstream internet, Big Data has provided vital insights, enabling marketing and sales teams to better understand consumer behaviours. Companies who succeed at converting this data into market growth will generally focus on the following activities:

  • Identifying business opportunities using data analytics
  • Using the data obtained to make key business decisions and improve marketing ROI
  • Creating well-designed products and/or service packages based on data insights
  • Delivering these products into the marketplace
  • New technologies make the process of capturing data even easier, with the provision of interfaces to help businesses check and monitor customer trends.


The online risk, insurance and compliance magazine, StrategicRISK, estimates that there are approximately 4.4 zettabytes (4.4 trillion gigabytes) of information in the digital universe, with the number set to reach 44 zettabytes by 2020. From a revenue point of view, clearly the trend is showing no signs of slowing down.

Organisational change

New analytics tools enable better interpretation of data, however, to truly succeed you must address any organisational changes required as a direct impact of Big Data. For example; the evolution of job descriptions, with more focus dedicated to data and change management.

New Technologies

Business leaders need to consider which functions or departments are likely to benefit the most from analytics – and how the technology will be rolled out. Communication is the key to ensuring seamless business operations – get your employees on board with new technologies and processes.


Taking into account any organisational changes required and the software needed to get the job done, it’s time to consider training. The onus is on managers and team leaders to identify any gaps in training and ensure that employees are not only clear on the tasks required of them but also receive adequate training to deal with changes to their job roles. This process can take a little time but with careful planning can yield dramatically positive results.

Real-world Examples

There are countless successful real-life Big Data applications to use as inspiration when formulating your own strategies, here are a few of particular note:

  • Customer Service – MagicBand (Disneyland)

The data-driven innovation MagicBand, pioneered by Disneyland and developed with RFID technology, involved interactions with thousands of sensors strategically placed around its various amusement parks. The aim of the endeavor was to collate stacks of big customer data and process it in order to enhance customer experience and gain insights to benefit long-term business intelligence strategy.

  • Customer Retention – Coca-Cola

Coca-Cola is a great example of a company that uses big data analytics to drive customer retention. The company managed to build its data strategy in 2015 with a digital loyalty program. In an interview by the ADMA managing editor Alicia Tan, Justin De Graaf, Director of Data Strategy and Precision Marketing at Coca-Cola made clear that big data analytics was a key driver behind customer retention. The main loyalty program, My Coke Rewards (MCR), still runs and originally sprung into life back in 2006.

  • Improving Health – ResearchKit (Apple)

Apple’s health app, ResearchKit, turned phones into biomedical research devices. Researchers benefit via the collection of data inputted to user phones for use in health studies. Data such as how many steps a user takes in a day, or how a user feels after chemo, can be monitored and used to increase the number of participants a study attracts and the fidelity of the data. This is a great example of Big Data analytics for the greater good in addition to raising the profile of an individual company.

  • Targeted Adverts – Netflix

For a great example of a brand using big data analytics for targeted advertising, look no further than Netflix. The entertainment giant collects vast amounts of data from its 100 million + subscribers in order to run tailored adverts on user interests, for example, suggestions for a next film or TV series for a user to watch.

The examples above illustrate how Big Data analytics can be used across a wide scope of business activities with impressive results. With time and careful planning you too can reap the benefits of the vast pool of data now available.