Did you know that in 2011, approximately 1.8 Zettabytes of data was created? To put this into perspective, such an amount of data would completely fill 57.5 billion standard 32GB Apple iPads, or equate to 200 billion HD movies taking 47 million years to watch.
Unsurprisingly, data production rapidly increases every day due to the popularity of digital and online mediums, allowing for unstructured data points from our digital interactions to be recorded. Such an explosion of data has further created an obsession and sparked a lot of conversation within the advertising and marketing community, in which various ways it can be applied to improve marketing communications are constantly explored. However, along with the hype comes strong criticisms and questions that need to be pondered in order to determine what really is the big fuss about big data and the best way for brands to use it.
The majority of the discussion around data in marketing is the unprecedented personalisation of messages, which was previously once unimaginable. After all, research has proven that tailored marketing campaigns and increased personalisation results in increased consumer engagement and improved ROI. With a strong emphasis on personalisation and individualised campaign messaging, marketers are relying on personal customer data in order to deliver on this demand. Furthermore, a brand that leverages such data and can provide unique experiences has a strong competitive advantage in an overcrowded and noisy marketplace. Take the music streaming giant Spotify for example. The successful streaming platform, boasting of 140 million users, understands how to deliver a unique experience to every single one of their listeners. By collecting data about their music preferences and monitoring consumer behaviour, Spotify has been able to determine an individual’s personality and provide them with an individual playlist of songs that they will enjoy.
With such a hype around how data assists personalisation, it is not a surprise that the big data discussion in the marketing and advertising community also largely centred around its use in artificial intelligence. It is argued that the use of artificial intelligence in marketing fosters personalisation and allows marketers and their digital advertising agencies to focus more on innovation and creativity. Between machine learning algorithms and complex predictive modelling, artificial intelligence is employed by marketers to use the large amounts of data to inform, analyse patterns and automate processes within marketing. With an abundance of data sets available, artificial intelligence has made it possible to discover meaningful insights that any human would be easily overwhelmed by as well as allow for facial recognition, natural language processing and machine learning to constantly improve modern marketing.
The hysteria around data in the industry is also amplified as a result of growing pressure that marketing’s teams face to demonstrate results and be accountable for their efforts. With increased data and analytics available, the ability to satisfy these demands has become easier, and therefore now strengthens all marketing functions. From using consumer-based data to develop a strong understanding of the audience and how best to reach them, to marketing analytics that assesses campaign performance and the effectiveness of an allocated marketing spend, data-driven marketing has become a necessity in today’s environment.
However, while the proliferation of data in recent times promises precise targeting, efficiency and can automate mundane tasks, the sheer volume of data available often overwhelms many marketing teams. Traditionally, the majority of the data collected was structured and had the ability to be easily analysed and organised in databases. However, modern-day connectivity and the digital world has exacerbated both the amount and types of data that can be collected and utilised. In fact, roughly 75% of the data collected today is referred to as unstructured data produced from voice, text and video sources creating complex data sets that require often expensive technology to analyse and understand it. For example, Facebook users upload roughly 100 terabytes of data daily and produce 30 billion pieces of content every month.
While such content that exists on the digital platform can in fact help develop a strong understanding of audiences, it is argued that analysing such data is time-consuming in which the insights would then become obsolete due to digitals fast-paced nature. In fact, it was revealed that as result of the volume of unstructured data, less than one percent is actually analysed, therefore hindering marketers to take full advantage of big data’s big promises.
Data-driven marketing has become an essential component for businesses today however it was discovered that only 4 percent of companies were completely satisfied with their efforts to use data to better engage with their audiences. While many studies suggest that collecting and exploiting consumer insights often results in significant customer satisfaction due to the ability to be more personalised and relevant, other studies demonstrate that for many businesses there is still a long way to go. With no signs of data production slowing down and the prediction that by 2030, 1 Yottabyte (which is the equivalent to storing a video of the lives of every individual) will exist, it is essential to make a necessary investment in data management and quality to ensure actionable insights can be leveraged. The vast amounts of data can allow an in-depth understanding of audiences and determine behaviours that can drive creativity and innovation for consumer engagement and conversions.
Here at RGC Digital Marketing, we offer a range of digital marketing and advertising services to connect consumers to brands. To find out how we can help your brand leverage data and customer insights to better inform your digital strategy, please contact Richard on (02) 8883 2988 or email firstname.lastname@example.org