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How data science is revolutionising e-commerce

by Kristine Lasam

Recognising that data is the future is one thing, making sense of it is another. Harnessing it to create memorable customer experiences is a whole new challenge.

Companies the world over are now exploring methods to sell across platforms that were initially vertical-focused. So when you’re shopping for bibs and pacifiers, a pop-up suggests the new baby car seat from Mother Care for you to consider. Beyond traditional segmentation by demographics like job titles, the data is being taught that new fathers make purchase decisions too i.e. behavior targeting.

What’s reshaping e-commerce?

Until recently, the data analyst has been the shop owner; the one that interacts with clients gets the pulse of the market and translates this in orders. But he faced two big challenges: his knowledge was typically honed with years of professional experience, but it was hardly an asset for the shop.

The knowledge was difficult to transfer within the organisation and this limited the pace of growth. The second challenge was that validating the initial assumptions would take some time: He would discover only after weeks or months if his original intuition was correct.

Fast forward to today, where technology allows an unparalleled growth for companies, especially in the now super-competitive e-commerce market.

Data science evolved from the need for optimization and, like natural selection, only the fittest survive. And, nowadays, the fastest to conquer new markets as they become available is the one that will predate the competition.

What is the real aim of data science, and can it be automated?

The focus is on predictive analysis, inferring future trends from existing data. Science now drives product strategy, it tries to answer the questions of what we should sell, when and at what price. Tools like Google Analytics, once just reserved for big brands, are now available to everyone.

Data helps in making assumptions and validating them nearly in real time. The interesting thing is that the wide availability of data tools has given everyone – big and small – the chance to compete in the market.

An e-commerce company today has the tools to launch a remarketing campaign, either alone or with the help of a digital agency. Tracking pixels can now be attached to a wide number of actions inside an e-commerce website.

A marketer uses all this additional information to reach back to clients that abandoned the conversion funnel, clients that typically warrant higher conversion rates. Reaching a specific demographic, targeting a specific gender, age, interest or nowadays even geographical locations is now a possibility for every e-commerce startup. There is not even the need to build marketing lists: all of this can be traded.

It won’t be long before we will be able to customise the shopping experience for every visitor by querying his social profile, or online navigation history.

How can executives hope to execute on this at the level of data giants?

While most of the data is in the hands of effective monopolies such as Google or Facebook, they rendered it available to small firms, and marketing is helping to lead this revolution. But we are looking at the beginning of the next stage of evolution in e-commerce: Personalisation.

By tapping in the wealth of information available for each user, a website can use the interests of each user in order to create a customised experience.

Data science helped the evolution of e-commerce, but now it is just a building block for artificial intelligence which is now able to personalise the whole e-commerce experience. Technology is a race, and so far the winners have been the ones that leveraged data science.