The adoption of AI technologies across so many industries is hard to ignore, and it looks like we’re barely scratching the surface of what’s possible. E-commerce is experiencing a period of rapid change that may have been accelerated by the coronavirus pandemic, and many of the most innovative solutions will be built on emerging AI and machine learning technologies. Let’s take a look at some of the more interesting transformations in the world of e-commerce that we’ve seen in recent years, and explore how AI has been the driving force behind them.
There is an increasing emphasis on the personalization of customer experiences in e-commerce. This was already true even before AI started to influence the market, but it’s even more valid today. Shoppers expect that the product recommendations will be adapted to their own shopping history, with relevant search suggestions and recommendations from the store. This can be tricky to get right, especially with a more diverse inventory that covers a variety of products.
With the help of modern AI solutions, new processes can be automated, and patterns can be inferred that were not that obvious before. This can allow stores to more effectively target their customers – both new and returning ones – with relevant content that can drive up engagement.
Technologies like visual search are making it possible for customers to search for products based on visual similarities alone, and automated metadata tagging helps companies manage huge product inventories, by scanning and labeling product images automatically.
This concept can be taken one step further with the idea of virtual shopping assistants providing information to customers as they are navigating the store. The idea was already being explored in some capacity in the past, but expanded AI capabilities are enabling significant progress in this area.
It doesn’t matter if someone is just browsing around, or looking for something specific with a lot of information available on it. Both cases can be addressed with modern AI systems, and they can provide suggestions that even experienced customer service staff would sometimes not think of.
Navigating an online store can sometimes be a bit confusing, and identifying design issues without huge amounts of user testing is not as easy as it seems, even for experienced UI/UX designers. AI is proving to be extremely helpful in helping designers to identify patterns more effectively and to help their users navigate around their sites with ease. There are huge potential efficiency improvements and cost savings for companies that can reduce the amount of manual labor required for user testing.
Smart homes were seen as a product of science fiction not too long ago, but these technologies are rapidly being adopted by many of the world’s largest tech companies. We’re seeing solutions in this market really taking off in certain areas, and it’s only a matter of time before this technology becomes more accessible and tightly integrated into our lives.
What does that mean for e-commerce? A lot. Our homes are generally the center of our lives as consumers, and the ability to intelligently recommend products and services that fit our lifestyle has never been greater.
Smart fridges can use computer vision to automatically track food reserves and alert homeowners when supplies are running out. Not only that, but they can automatically order restocks when necessary. The same idea can be extended to the whole home. Devices can perform their own diagnostics with AI-driven tools and determine when parts are about to fail, prompting the owner to order them in advance.
The field of logistics has already seen significant improvements thanks to the introduction of AI solutions, and this has a direct effect on the people, facilities, products and prices offered by e-commerce businesses. Stores are able to predict their stock needs more accurately and waste less time and inventory space. These improvements have implications for nodes up and down the supply chain. For example, a warehouse can anticipate changes coming from other storage facilities, and local workers can integrate that information into their daily schedule more effectively.
It’s not unreasonable to envision a future in which production and supply lines operate on very thin margins, because they are working with information that’s much more precise than anything they’ve had access to in the past.
AI can also be very useful in general inventory management. Inventory supplies can be tracked and monitored with computer vision. Warehouses can be organized more efficiently, decreasing the time needed to procure certain items. This planning can be adapted to factors like items typically ordered together and other details that can impact how things should be stored relative to one another.
And with more advanced prediction capabilities for inventory capacities and stock, less space will be needed to handle the same workloads that we have right now. This should lead to the creation of attractive scaling opportunities in the sector, allowing companies to more quickly expand.
Good AI e-commerce platform integration is key to the success of these solutions, given the current state of inventory management software as a whole. That’s why the field has received a lot of attention from specialists exploring the opportunity for integration on a native level wherever it makes sense.
The link between AI and customer service is a well-known one already. And it’s a field that will likely see even more development in the coming years. AI-based chatbots can now perform some impressively complex tasks, and can guide users through their whole shopping experience from start to finish. Even if the AI reaches a problem it can’t solve on its own, to transfer the conversation to a human specialist whose job is also helped by AI services such as search and resource recommendations.
This doesn’t just apply to real-time conversations either. AI can be used to intelligently generate FAQs and similar sections, analyzing months or even years of conversations in seconds and identifying common patterns. Taking the concept one step further, sites can adapt their content dynamically to match the needs of customers as they interact with an e-commerce solution.
Counterfeits are still a major issue in the world of e-commerce. It’s a problem that affects major retailers just as much as small stores, and various brands have been hit by it over the last few years. The ease of use that most of these platforms provide, combined with the relatively low barrier of entry, have created the opportunity for the perfect storm. But with AI on the horizon, that problem is likely going to go away to a large extent soon enough.
There is a lot of active work in this field, and there are already some promising results. There are still some obstacles to overcome that aren’t inherently tied to AI technology and its limitations. For example, sellers would often put up legitimate-looking pictures and product descriptions for their counterfeits.
But they also rely on careful wording to avoid legal repercussions most of the time. And that’s where AI has proven to be incredibly useful. Modern text classification models can identify those specific nuances and tell a legitimate product description apart from a fake one. What’s more, the algorithm can take many other factors into consideration. Even small details, like the username of the seller fitting certain patterns, can all come together to create a system that works with a shocking level of accuracy.
Some of the popular AI solutions for e-commerce are also starting to target fake reviews, which are another big issue on the market. It’s a great use of AI in e-commerce, as most of the offending reviews tend to follow certain very specific patterns. It may be hard for human operators to tell those reviews apart from legitimate ones, but an AI trained on the right data and configured in the right way can be a very powerful tool for dealing with this problem.
That’s actually a major driver for the popularity of artificial intelligence in e-commerce. As it stands, merchants are taking serious losses from fake reviews in some cases. The introduction of advanced AI solutions for e-commerce has been a blessing for them, allowing them to address a long-standing issue with relatively little resources. Compared to before, the current situation looks much brighter for those trying to survive on the market.
Last but definitely not least, we have another issue which has been prevalent in the world of e-commerce for a while. Security is something that can trouble both small stores and large ones alike, and it can be notoriously difficult to get right without significant investment in security personnel.
Security teams can augment their capabilities, by combining their judgment and knowledge with the accuracy, speed and scalability of advanced AI solutions. Security camera footage, for example, can be processed and analyzed by computer vision algorithms much more quickly than a person could ever accomplish on their own. Repeat offenders can be identified, and security infractions can be prevented with scale and accuracy that was never possible before.
In general, AI is helping e-commerce businesses that are trying to target their existing customer base in new ways. This is possible thanks to diverse data streams and multi-modal inference systems, which allow stores to identify patterns in user behavior, so that new insights can be made about customer needs and expectations.
In the long term, this will likely have a significant impact on customer retention and satisfaction. Companies have started to realize that they can benefit a lot from targeting customers in unexpected ways, and if this continues, we might see some major breakthroughs in the field.
AI in e-commerce has been very useful in helping humans explore these opportunities and evaluate their problems from a new perspective. AI can help augment human experience and intuition, and help us think differently about old problems.