E-commerce is growing at an incredible rate because of its affordability and product selection compared to brick-and-mortar stores. This rapid growth is motivating investments in more sophisticated tech to improve the online experience for e-retailers and consumers alike.
At the core of this is deep learning. If you’re unfamiliar with deep learning, it’s a subset of machine learning within artificial intelligence that’s capable of unsupervised data acqusition and analysis. It attempts to mimic the workings of the human brain in processing large amounts of information and creating patterns to govern decision making.
Here’s how deep learning investments are changing e-commerce.
How Deep Learning Investments Are Benefiting Consumers in E-commerce
Artificial intelligence is more prevalent than people realize. Take watching Netflix for example: its “recommended shows” are based on artificial intelligence algorithms.
In e-commerce, deep learning can aid online consumers with customized ads suggesting products they’re likely to buy, in addition to products they may not have considered, but would enjoy.
Instead of buying the same products over and over again, deep learning essentially thinks for the consumer to suggest new products aligned with their interests. Amazon’s “Customers who bought this item also bought” feature is another good example.
Deep learning is so effective because it learns the same way people do, only at hyperspeed. It reviews each person’s patterns individually while also using data from millions of others to deliver fast insights.
And, of course, new players are emerging to capitalize on the technology. India-based Staqu is developing an image-to-image matching system. The goal is to simplify image search, tag generation and real-time recommendations. This will offer customers the most relevant array of advice and products suited to their interests.
If you’re well past the stage of shopping around for e-commerce website themes, you might already have an idea of how deep learning technology could improve your own store. Maybe it’s through chatbot customer assistance, recommending additional products after a customer has added to their cart or improving on their general shopping experience based on their past site interactions.
How Deep Learning Investments Are Benefiting E-Commerce Brands
Today’s e-consumers want a personalized experience. They want their product, packaging and advertising to match their likes and objectives. Deep learning is music to e-retailers’ ears in this regard because of what many customers are willing to provide in return for this personalization.
According to a study by Adlucent, 44 percent of respondents were willing to provide their name, address or email address in order to get more personalized advertising. Seventy-one percent of respondents prefer online ads tailored to their interests and shopping habits. This study also found people were almost twice as likely to click-through an ad featuring an unknown brand, if the ad was tailored to their preferences. E-retailers can take advantage of this to collect more customer information as a means of building a relationship and customizing their customers’ shopping experiences even further.
ViSenze is an AI startup developing tools for intelligent visual recognition, visual search, matching and recommendation functions for e-commerce and contextual advertising applications. This type of deep learning can help e-commerce owners by allowing other machines and software to “see” products through visual recognition, allowing the addition of product tags, show similar product recommendations, aid personal consumer discovery and allowing consumers to search for products by image or screenshot. This can boost the effectiveness of marketing and search efforts for e-commerce outlets.
Reflektion, another AI startup, provides a predictive analytics platform and easily deployable solutions for retailers and brands to boost page views, conversions and revenue on a cloud subscription basis. This type of technology is great news for e-commerce retailers, especially relatively new stores looking to capitalize on AI without investing considerable money into developing their own processes.
Deep learning offers so much potential because it singles out individual users among a large online audience. While deep learning is still developing, its enormous potential in the e-commerce marketplace cannot be ignored. As more e-retailers affordably implement this technology into their stores—and overall online experience—sales and customer satisfaction will drastically improve.
These are just few ways e-commerce will be affected by AI technology. How else are deep learning investments changing e-commerce? Stay tuned; a lot is happening behind the scenes, but only time will tell which types of technology stick around.
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