By combining AI with massive data, the future of e-commerce will see a smarter, more self-intelligent shopping ecosystem that can make optimal decisions on its own

Southeast Asia is set to be the next frontier in e-commerce growth in the Asia Pacific region. According to PwC’s Total Retail 2016 – Southeast Asia & Singapore Highlights report, almost 60 percent of Singaporean shoppers have made purchases online every month. Indonesia, on the other hand, sees at least 24 million of its population shopping online and its e-commerce market has generated US$5.6 billion in 2016. Besides the growing affluence of consumers in Southeast Asia, shopping online has become a common practice for the region’s mobile- and social media-savvy population.

With the vast amounts of data being created with e-commerce activities, companies, merchants and distributors are leveraging big data and artificial intelligence (AI) solutions to help them better utilise the data precisely target the right audience.

Today, the advent of AI and predictive intelligence technologies allows brands to accurately analyse and improve customer journeys – developing an ultra-personalised buying process and optimise processes on the digital channels. Time-consuming marketing activities such as dissemination of e-newsletters to announce new product launches are automated, hence allowing marketers to spend time on delivering higher-value services. Online purchases are made easier, more efficient, more engaging, and more adjusted to personal needs at every stage of the decision-making process.

1. Product Searching – Algorithms for Image Recognition

Have you ever seen something that you wanted to buy, but had no idea where to find it?

With AI-based image recognition, users can snap a photo with their smartphones and easily retrieve information about the product or its exact match – the product’s specification, which online store carries it, and how much it costs.

Google, Microsoft, Facebook and Yahoo are leaders in the field of making systems that perceive objects better than humans. Google’s Cloud Vision API, for example, makes it possible for developers to identify objects in an image, recognise words or text, and even guess the emotion of a person in the picture.

AI-based image recognition can be extremely useful for the region’s e-commerce industry. Marketplaces, aggregator websites (like price comparison engines) and online retailers that need to moderate millions of pictures can do so automatically and in real-time.

It also opens new avenues for customer experience. Many brands are increasingly recognising the importance of customer experience and it can determine a company’s success or failure – 63 percent of Southeast Asian business leaders listed improving customer experience as their business priority, according to a 2016 Forrester report. With AI-based image recognition, companies can analyse beyond mentions and see what types of experiences their customers are having with their brands. Deep understanding of that content is an incredibly valuable step towards true personalisation.

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2. Buying Decision – Making Highly-Accurate Recommendations

Let’s return to the topic of customer journey. Say you saw something you wanted to buy on a website, added the item to your shopping cart and almost made a purchase. However, something interrupted you, or you had doubts, insufficient funds, etc. This happens a lot to every shopper.

Personalised advertising banners can create impulse purchases, be it reminding you of the product, or showing similar products. This is, of course, already a well-known tactic among modern marketers.

An exciting prospect is deep learning – an innovative branch of AI that solves problems by imitating the work of the human brain – which has the potential to take typical retargeting campaigns to new heights. Deep learning algorithms are used to craft features that recognise the attitude, intention and the overall state of every user visiting a website. Based on that knowledge, brands can then prepare highly-targeted product recommendations to their customers. This precision can make advertising activities up to 41percent more efficient than with the typical machine learning approach, according to a RTB House study.

The real power of deep learning from the e-commerce point of view is that AI can use a massive amount of data and learn and act like humans – without specific instructions or rules such as potential sales peaks or guessing scenarios to how people will react. Online retailers can leave full decisiveness to algorithms which learn from practice and intuit from experience how to play optimally, and much faster than any human could ever do

3. Delivery – Algorithms That Predict Your Decision-Making

Think iTunes, for instance. Based on your existing library, the music player can wisely filter your tags to what you would most likely be interested in. With artificial intelligence, iTunes can go further to decide which songs should be added to your library, even making a purchase on your behalf.

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This is similar to what Amazon plans to do with what it calls “anticipatory shipping”, a distribution system that will deliver products to consumers before they place an order. Items could be sent to nearby distribution centres before an order is even placed – meaning the package is already at the shipment hub or on a truck, waiting to be dispatched when a someone orders it. This works even better with everyday products, like tea.

If algorithms can anticipate supply and demand, you won’t need to worry about running out of your favourite tea. Analytics and logistics can also be taken to the next level, allowing companies to react quickly (and automatically) based on their customers’ needs and in turn, expanding its base of loyal customers.

Imagining the E-Commerce of Tomorrow

E-commerce is data-driven by nature. Marketers, merchants and distributors have already seen the tip of the AI iceberg with personal assistants, chatbots, automated merchandising and retargeter systems. In the region’s e-commerce industry, however, we have not seen a widespread deployment of AI – at least not to the extent of utilising neural networks on a typical basis.

By combining AI with massive data, the future of e-commerce will see a smarter, more self-intelligent shopping ecosystem that can make optimal decisions on its own. This is something that we could only have imagined a decade ago, but is definitively possible today.

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