E-Commerce and AI Working Together in a Post COVID19 World

Kris Nickell -
Illustration: © IoT For All

COVID-19 has drastically changed the world’s shopping habits. For instance, grocery stores accelerated to curbside pick-up and Texas temporarily legalized alcohol delivery to boost restaurant sales. E-commerce companies with efficient processes have seen a boost in sales during this time. 

However, e-commerce setups inspired by a pandemic, are unlikely to be methodical or focused on the granular levels of the customer experience. Companies that needed to shift their focus to e-commerce had to find ways to increase customer value in new, creative ways. 

Turning to Tech

The latter is why a growing number of companies have turned to tech to help them find success in the new normal that we are experiencing. With this new normal comes the merging of Artificial Intelligence and Machine Learning into e-commerce platforms, offering a significantly more personalized experience for consumers. To put it simply: there’s nothing artificial about the growth that exists for companies who correctly leverage AI/ML technology. 

For example, Gucci created a new ‘artificial store’ for online shoppers. Gucci’s stores are complete with cameras and TV-style lighting to impress their customers. In the past, only a physical store could properly convey the elements of GucciDigital experiences. Those times have changed. 

By launching Gucci Live, the company was able to convey elements of luxury that are associated with the brand. Additionally, the company is hiring online advisors–a sure sign that their technological adaptation is paying off. Although Gucci hasn’t implemented a completely seamless and uninterrupted experience yet, they have adjusted quite well. When Marco Bizzari, Gucci President and CEO, was asked about this future-forward project, he discussed his desire to create “a human touch powered by technology” and it would seem he has succeeded in doing just that. 

Utilizing AI in a Changed World

Chatbots are an increasingly common way to scale the ‘personalized shopping assistant’ experience. Using NLP and analysis, marketers can create a system that automatically identifies the underlying message of most chats/texts. If potential customers ask a question about e-commerce products, AI can be used to identify the keywords then send an automatic script that addresses the question. 

Another way to use AI is through image recognition classifiers which are used to identify products within images and video, in real-time. Today’s consumer has a short attention span. As such, consumers expect much more from brands and experiences than they have in the past.

Thanks to AI, the process is direct–identify the product in a particular image or video frame, search the catalog, and serve up relevant products based on the computer vision results. AI as it pertains to computer vision can have massive returns for companies who spend a portion of their marketing budget on content and have an especially large number of offered products.

Machine learning algorithms have reached a point where they can even predict a specific individual’s behavior with greater accuracy than that person’s own spouse. It’s not only possible but commonplace for brands to now tailor different messages to different factions of their target market. The use of deep learning in e-commerce marketing has led to optimized ad creation and significantly higher ROI.

For example, Netflix plays different trailers to different viewers based on their viewing history. If you enjoyed 3 movies in a row that feature Robin Wright, it’s easy for Netflix’s data science team to understand that you appreciate strong female leads. Once Netflix’s algorithm understands this about your viewing preferences, it will highlight specific trailers that feature female leads more frequently than the male leads. 

This work is important as Netflix’s recommendation engine is responsible for a whopping 80% of content discovery on the platform.

Another example is image classifier tools like Clarifai. The company is making custom neural network training simple for the masses. The software allows users to build their own models and teach an AI system on how to identify just about anything they could desire. For example, your team could train a model to identify Instagram pictures that include more than five people. If you sell KN-95 masks or hand sanitizer, you could use this information to directly target these people who don’t appear to be socially distant. 

Crossroads of AI and e-Commerce

IoT devices like Alexa and Google Home play an increasingly important role in the crossroads of artificial intelligence and e-Commerce. While not new, you can order products directly from these devices using nothing more than your voice.

Today, machines aren’t the only ones that care about learning. More and more growth-focused marketing departments are awakening to the idea that AI will revolutionize their traditional practices. Technology-forward practices like content commerce and shoppable video will act as the sandpaper that reduces friction in the online shopping experience. You don’t need to be a luxury brand to care about increasing your online conversion rates. 

Kris Nickell - Senior Vice President, AiBUY

Guest Writer
Guest Writer
Guest writers are IoT experts and enthusiasts interested in sharing their insights with the IoT industry through IoT For All.
Guest writers are IoT experts and enthusiasts interested in sharing their insights with the IoT industry through IoT For All.