While our television sets may tell us stories of dystopian futures dominated by sentient machines, artificial intelligence isn’t just a work of a science-fiction; it’s our reality. Today, AI, and by extension machine learning, is revolutionising business, and having a profound impact on the e-commerce sphere, providing a stepping stone to improved e-commerce results. Here's how.
Why Machine Learning?
Within the past decade, machine learning has amassed widespread interest throughout the e-commerce sector.
Providing forward-thinking retailers with an ability to interpret real-time behavioural data and automate site-search merchandising, machine learning algorithms have revolutionised on-site product search.
Today’s shoppers are reliant on site-search to find the information and products they want. After all, visitors cannot buy what they cannot find, and, according to Wired, those who receive null-results – where the proposed result is absent – are 3x more likely to look elsewhere.
However, when they use site-search powered by machine learning, customers are not only able to find exactly what they’re looking for, they’re also met with more targeted, relevant, and individually tailored products – improving the customer experience and encouraging larger consumer spend.
Thanks to this trend, personalisation is quickly becoming one of the most important factors in modern-day e-commerce.
Machine Learning and Personalisation
A recent report from global technology leader, Infosys, uncovered that 59% of consumers who experienced personalisation say it significantly influenced what they purchased. Meanwhile a paper from market researcher Econsultancy found that 93% of companies see an uplift in conversion rates from personalisation.
By utilising machine learning, not only are e-commerce businesses able to increase on-site conversions, they can also prioritise the products that bring in the most revenue or generate incremental sales, killing two birds with one stone.
And the benefits of a personalised shopping experience don’t stop there.
According to research by Smart Focus, 50% of consumers would be more likely to use a retailer again if they were presented with personalised offers and information. So, not only is it possible to increase conversions on a one-time
The Value of Machine Learning
Machine learning enables e-commerce retailers to significantly improve their customer personalisation, enhance the shopper experience, and, by extension, increase consumer sales and their bottom line.
It does this by tapping into specific facets of an individual’s buying habits – colours, styles, budget etc – so its able to prioritise products that matter most to the shopper – thus increasing conversions and improving revenue.
While it’s true that a basic level of personalisation can exist without machine learning algorithms working tirelessly in the background, often the processes involved are resource-intensive and can quickly become costly to execute.
Tweaking and redirecting search results or adding related products at the individual product level is time-consuming, but with automated processes via machine learning algorithms, valuable staff time is freed up, allowing employees to concentrate on core responsibilities.
Machine Learning Algorithms
While the threat of world-wide destruction via super-intelligent robots is the stuff of fiction, the current uses of machine learning are anything but make-believe.
The technology continues to cement itself as one of the most ground-breaking developments of the 21st century – enhancing personalisation and helping e-commerce organisations better understand shopper preferences and consumer behaviour.
Retailers yet to realise the value of this technology, specifically regarding its personalisation benefits, are now at a high risk of being the wrong side of the technology curve. If this sounds like your organisation, you can compare a host of leading vendors and what they offer in our latest e-commerce site-search platform cheat sheet – download it for free now.