The Internet provides masses of information that was impossible to obtain just a few years ago. The growing use of smartphones, Internet of Things (IoT) devices and customer relationship management (CRM) systems

The Internet provides masses of information that was impossible to obtain just a few years ago. The growing use of smartphones, Internet of Things (IoT) devices and customer relationship management (CRM) systems, as well as data gathered from online shopping behaviour, social media profiles and activity, such as likes and dislikes, product reviews,tagged and shared content,have together resulted in a truly vast data universe in the digital space today.

In fact, the International Data Corporation (IDC), the premier global marketing intelligence firm, estimated that in 2020, the amount of data created and copied around the world had reached 44 zetta bytes, or 44 trillion gigabytes. Further, the quantum of data that is being generated every moment of every day is increasing at an ever-growing rate. Currently, it is estimated to be doubling every two years – and the pace is only accelerating.

The problem is that over 80% (some put the figure as high as 90%) of the data that is being generated is in an unstructured form, which makes if far more difficult to analyse than data that is available in a structured format.

Data refers to information represented in a format that is useful for processing and usage.

Structured data, which is usually presented in rows and columns, displays numbers, dates, values and strings. Found most often in closed-end surveys, structured data is great for basic organisation and calculations, as it easily fits into preset parameters and can be analysed by means of programs such as Excel and Structured Query Language (SQL), to reveal patterns and trends that show “what” is happening.

Unstructured data is obtained from a variety of sources, including open-ended questions, responses to customer support queries, as well as online reviews and messages. It lives in emails, audio, text and video files, as well as No SQL (non-relational) databases. As they do not fit into preset parameters, unstructured data is hard and extremely time-consuming to analyse manually. However, they have the potential to provide invaluable insights on not just “what”, but“why” something is happening.

The ability to combine the results of structured and unstructured data provides immense benefits. For example, by using unstructured data, marketers can gain insights into individual customer preferences, while the structured data provides them with information on the number and age of customers. By combining the two, marketers can analyse the level of customer satisfaction, as well as correlate it with customer preferences among different age groups, for instance.

However, combining structured and unstructured data had presented immense challenges till recently, as analysing unstructured data necessitated lengthy, manual activity. It would have taken marketers months, if not years, to understand and react to factors such as consumer sentiment, in order to course correct. By which time, it may have been too late to recover from mistakes that had been made or opportunities that could have been seized

AI and machine learning models, combined with natural language processing, can be programmed to identify unstructured data points that are important. By learning and recognizing data patterns, AI has the ability to rapidly convert unstructured data into a structured format, with the feedback loop being cut short from months and to days or even hours.This is invaluable in order to derive insights in near real-time.

This synergy between AI and unstructured data means that we can rapidly predict upcoming trends, across industries that are as diverse as business, technology, commerce and entertainment, to name just a few.

This marriage of AI with big data means that this is truly the time for marketers who are looking to scale up their understanding of customers and their behaviour. Using AI tools to analyse unstructured data offers companies the opportunity for deep brand and competitor insights to predict customer needs,in order to stay ahead of customer expectations, through the structuring of data that is currently available in unstructured formats.