Your e-commerce store is doing well. But it could be doing better, with help from a deep learning program. Deep learning will not only help your site administrators, but improve the shopping experience for customers, which, in turn, leads to more profits.
What is Deep Learning?
Deep Learning is a subset of AI. The concept started in the 1950s, when scientists tried to mimic brain power. The computers that “do deep learning” use artificial neural networks (ANN) made up of thousands of neurons. (A mammal’s brain has billions of neurons.) These neurons work in layers, with the “deep” of deep learning referring to the many layers needed to perform these functions. Each layer can add and compute new information.
AI can read a row of numbers, but deep learning programs can take millions of examples and learn that the handwritten zero that looks like a six is a zero. Deep learning is what we call the machine figuring on its own how to solve a presented problem.
E-Commerce and Deep Learning
E-commerce has been around since the early days of the Internet, with the first online shopping system debuting in 1981. By 1999, global e-commerce reached $150 billion in sales, and of course, it’s continued to rise thanks to more secure credit transactions and mobile devices. E-commerce is expected to account for 17 percent of all retail sales by 2022.
While e-commerce is popular among consumers and retailers alike, online stores face many challenges, including:
● Acquiring inventory
● Tracking stock
● Product price changes and knowing how much people will pay
● Customer feedback and reviews
● Anticipating what people want
● Attracting customers and generating traffic
● Converting shoppers into buyers
● Managing technology and updates
● Finding return customers
● Shipping nationally or globally and controlling those costs
● Juggling multiple software programs and making sure they work together
● Making sure customers can search for what they want and find it
Deep learning and other AI programs can help with most aspects of e-commerce. Yet not many retailers have implemented it (other than the large corporations). However, some AI users say implementing such programs can increase revenues between 5 and 20 percent. Here are just a few of the ways you might rely on AI to improve an e-commerce site:
Product Suggestions – Most consumers are familiar with AI telling us what we want. We’ve come to rely on suggestions as part of the shopping experience. According to a recent study, such recommendations drive 24 percent of orders and 26 percent of revenue. Recommendations also lead to longer shopping times, bigger shopping carts and repeat visits.
Merchandising – Sorting and keeping track of your inventory and pairing similar items in your store doesn’t mean staying glued to spreadsheets. Deep learning programs will quickly figure out what goes where and track your products, alerting you to shortages and other issues and helping you categorize items.
Search – Deep learning thrives on search, figuring out what customers mean and finding the answers, predicting what customers want to see, even if that’s not exactly what they typed in. A search tool that produces desired results will make a vast difference in a customer’s experience.
Shipping – Leave the cost and time estimation to computers. Deep learning programs can sort this out for you and give customers accurate information, making them more satisfied with the overall process and saving you money, if shipping is included in your product prices.
Fraud Detection – Banks have been using AI programs for years to alert consumers about potential fraud. Deep learning programs look for anomalies, among other indicators. Your site can assure customers of their safety.
Abandoned Cart Recovery – More than 76 percent of carts are abandoned. Set up a program to send emails to customers who disappear. In studies, customers tend to click these recovery emails about 31 percent of the time, with 28 percent leading to a sale. People leave their carts for many reasons; a reminder might help them pick up where they left off and offer other ideas.
Account Management – Set up your store to alert people about password problems or figure out that they have more than one account set up with you.
Supply/Demand – Deep learning can analyze trends online and with your customers, measure sentiment, and track supplies to not only alert you when inventory is low, but predict what items will be bestsellers and when.
Pricing – Dynamic pricing is becoming more common in areas other than airline tickets. Consumers can easily compare multiple online stores. Deep learning can take a variety of factors — demand, competitors’ prices, time of day, and that type of customer — to set the price. Even if your prices are set, a deep learning program can help you determine if supply and demand dictate a higher or lower rate.
Resource Allocation – If you’re a larger e-commerce store, you might have more than one distribution site. Use deep learning to adjust inventory locations based on where things are going to be needed.
Marketing/Remarketing – AI has many places in marketing. Just one example: Use personalized product recommendations to retarget your customers or their look-alikes. Re-targeting ads show previous visitors the things they browsed while they visit other websites — even across multiple devices.
Chatbots – Install an AI chatbot to help your customers with questions. With deep learning, the program will soon figure out answers to most queries, saving your customer service team for complicated problems.
Deep learning will continue to aid e-commerce sites in ways we haven’t yet considered. If you want to add AI to your online store, talk to us about getting started.