By Kareem Masri, digital lead, Saudi Arabia, Magna.
Cookie-based data is a key component of digital marketing. Online marketing businesses have got into the habit of resorting to cookies for targeting, retargeting and determining user behaviours. This has caused digital marketers to focus specifically on third-party cookies, which, unlike their first-party counterparts, are set by other websites for cross-site tracking and ad serving. This is the digital marketer’s idea of a juicy steak since third-party cookies are designed to track users’ ‘trail of crumbs’ and, to put it shortly, lead them straight to the candy cottage. This level of dependency on third-party data will change in the coming years, and our industry will need to embrace it.
Let’s focus on this change and the upcoming transformation that comes with it. With the cookie era being almost over, digital marketers are fueled with the challenge to mega-charge their first-party data. Let’s call it the first-party cookie redemption, since it offers businesses plenty of opportunities to self-grow and discover their potential. A brand’s first-party data can without a doubt provide a highly valuable comprehension of its audiences bespoke to the brand’s products and services. Through implementing this self-reliance strategy, brands acquire a more microscopic view of their target audience.
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Furthermore, if this detailed level of audience intelligence is merged with data science, brands can ultimately plan their marketing campaigns and inbound strategies more effectively. The caveat here is brands will need to have the appetite, skillset and bandwidth to perfect their performance and create meta-strategies for data analytics and optimisation.
Achieving our end goal: the perfect shot at the perfect customer
To enhance our ability to achieve digital marketing goals, we also need to introduce the notion of machines and their contribution towards our objectives. Although artificial intelligence (AI) has hyper-organised modern consumerism in the marketing world, user demands and behaviours have become far more complicated to decode. With AI technologies having revolutionised digital marketing in the modern world, brands are scavenging for a merge that tracks our complex and individualistic preferences as humans.
Our duty as digital marketers is therefore to become more data-literate and embrace the technology that helps facilitate brands requirements. The lack of data literacy in creative marketers is a common cause of friction in the digital marketing field. Marketers tend to focus solely on detail-packed creative endeavours, while dismissing the hefty contribution of data science to teams traditionally associated with being the guardians of an organisation’s data. That is why we must add analytical efforts to our creative aspirations. To grow our businesses’ sustainably in a virtual world, we need to merge the skillsets of both marketers and data scientists to reach golden standards in precision marketing; which, essentially, is getting the perfect shot at the perfect customer.
The brainpower behind digital marketing success
This brings us to the marketing quest of the century, set towards increasing important business key performance indicators such as return on advertising spend and customer engagement. Ultimate brand success results from the fusion of creative marketing, data analysis and data science. The difference between a data analyst’s and a scientist’s job is that a data analyst reviews an organisation’s historical data, whereas a data scientist anticipates an organisation’s future. Briefly explained, a data analyst delivers accurate assessments of what works for a brand and what needs developing by using graph methods, data visualisation tools and analytics dashboards.
They dig into your past and aim to make sense of it. A data scientist, on the other hand, designs experiments and predictive models based on available data to test probable outcomes and set smart objectives. Data scientists are expected to have equal expertise in the fields of mathematics and computer programming.
Of course, marketers don’t need to know exactly what goes on under the data science black box – that’s the job of those who speak machine. However, a mutual appreciation between marketers and data scientists is key to customer engagement, considering that data scientists decode complex customer behaviours and marketers funnel them to meet their brand goals. It takes advanced statistical algorithms and machine learning tools to get this done. It may also take a significant amount of time, resources and thorough planning to turn this venture into successful digital marketing.
To spark motivation in this area and make this happen requires a start. The start could be as simple as sitting with the data scientist and explaining to them what the marketing or business goals are. Through open communication, this will build a crossover between the brand’s performance history, interpreted through data analysis, and the future objectives pursued by brainpower fused with data science.
And there you have it: the breakthrough to an elevated digital journey is on its way.