digital marketing data science

Data is the biggest currency in the 4.0 era and all businesses, big or small, are starting to realise this. It has been estimated that by 2023, big data will be worth US$77 billion. Furthermore, according to a Harvard Business Review study, in the past ten years, mainstream companies have steadily invested in big data and AI initiatives in efforts to become more data-driven with 91.9 per cent of firms reporting an acceleration in the pace of investment in these projects, and 62 per cent of firms reporting data and AI investments of greater than US$50 million.

Over 50 per cent of enterprises today are utilising big data and for good reason. When applied properly, it’s been shown to reduce business costs by 10 per cent, while increasing revenue by eight per cent. 

However, when it comes to leveraging data for better decision making, it has always been seemingly privy to either large companies or specialised high-tech startups. In this race, startups and SMEs that are not necessarily “high-tech” in nature and lack the expertise or infrastructure to analyse high volumes of data tend to get left behind. 

To address this gap, startups are starting to use applied data science to drive business decisions. This allows them to generate data from their digital marketing activities and benefit from data-led decision processes to optimise their success despite being comparatively “low-tech” in nature. 

A scientific approach to digital marketing

So what exactly does an applied data science approach to digital marketing look like? Before we dive deep into that, it is important to first understand that running a startup in a digital ecosystem is akin to a new kind of applied science via digital marketing.

This means there is scope to develop hypotheses, set up experiments, analyse data, derive insights and accordingly implement new measures for the company’s growth.

Also Read: Axiata-owned ADA rakes in US$60M from Softbank to develop AI-driven digital marketing solutions

Following a trial-and-error logic, startups can design and run experiments to generate exactly the data they need for their decision making. For instance, common experiments in digital environments are A/B tests. This allows the comparison of two different settings in the same online environment and helps find patterns in their activity set-ups to optimise success. 

Nearly all landing page and website builders out there these days offer the ability to conduct A/B tests, which allow marketers to experiment with different versions of their website or landing pages (or emails, blogs and so on).

These A/B tests are conducted side-by-side in real-time, with different versions of the content being shown to different visitors, while the data is being collected, stored and organised all the while.

For example, let’s take a simple hypothesis suggesting that red font colour works better for CTAs as compared to blue. Simple A/B test set-up to compare conversion rates by changing the font colour of the CTA, two versions can be created- one with a blue CTA button, and another with a button that’s red.

After showing both versions to visitors, collecting enough data and analysing the numbers, it can be very easily determined that which font colour works better for the CTA, and if the initial hypothesis was right or wrong. Finally, once the insights have been derived from the experiments, the final step is to apply these insights to your marketing strategy. In this case, such an application would involve changing the colour of the CTA button on the landing page.

It should be noted that this is not a one-off scenario. Data is constantly evolving and in flux, and thus, startups should keep a consistent eye on their data to stay on top of changing trends as they happen. As digital marketing is essential for value creation in digital ecosystems, these activities can be an important part of a company’s business model, beyond just a marketing channel.

Next-gen approaches lead to next-gen results

As brands begin to take a scientific approach to their digital marketing campaigns, they’re garnering incredibly useful data insights. 

Look at one study conducted by a German startup that sells online video lectures. The team set up an experiment that looked at how a promotional online video must be conceptualised and designed in order to produce conversions. They looked at video length, scenic presentation and the application of computer graphics to the video, and produced eight videos that played around with these elements.

Also Read: 3 AI-driven digital marketing strategies your startup needs right now

Counterintuitively, the experiment’s results indicated that reduced scenic presentation — in other words, the presenter speaking in front of a white wall — performed far better than the versions with rich scenic styles. And it gets more complex from there, with different combinations of elements producing different results.

For example, it was found that the videos with rich scenery performed better when they were shown without graphics, while reduced scenic versions performed better with said graphics. 

These kinds of insights would have been far too costly and time-consuming to have garnered before today’s technology was available, and are invaluable to businesses today. They allow for a level of customisation and personalisation never before seen. 

Investor support is key to the future of data science

While startups across the region and beyond are recognising the value in data-driven decision making, the application of data science to digital marketing is not that commonly supported by traditional financing agencies.

For more startups and SMEs to be able to leverage data for better decision making, investors need to step up and look a bit deeper. It is true that with the rise of fintech, financing companies have come a long way since the old days, but the drive has been geared, in fact somewhat limited, towards automating manual processes instead of improving the underwriting approach.

Investors need to look beyond tangible assets and understand as well as appreciate the value of technology-driven innovation. Some key players in the region are already starting to realise the shift and stepping up. One such example is Singapore-based Jenfi.

With a keen focus on assisting digitally-enabled businesses, Jenfi supports e-commerce ventures and high growth startups by funding their marketing, inventory, and growth campaigns. The startup uses tangible metrics to measure a business’ productivity of growth and can provide additional capital when businesses are at an inflexion point and primed to take off.

With digital ecosystems increasingly becoming mainstream, all stakeholders- founders, innovators and investors need to come together and closely look at things that matter- aspects that drive business. With innovative financing solutions like Jenfi’s, startups will have the support and resources to develop and implement a scientific approach towards data, and leverage those insights for a better, brighter future.

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