Fully online shopping experiences have traditionally limited the consumer to the same grid of products that all users see in the same application. Top sellers and product prices are the same across multiple user screens. Fortunately for the shopper, there is a change taking place. AI ecommerce applications give the user an assortment of prices, products, and suggestions, based on their individual history on the application, including, but not limited to, browsing and purchasing habits.
Retailers spent years collecting shopper data. At first, they used it in small ways, like sending promotional emails. Then AI changed everything. Now retailers can use that data to predict what customers want in advance. Artificial intelligence has introduced the feature of a smart search bar. It has complicated order fulfillment by introducing chatbots and personalized the online shopping experience based on the collected user data, such as differentiating the school supply shopping page from the sneaker supply page.
The ecommerce applications that adopt these features are the applications that will gain users over competitors using outdated platforms.
Why Ecommerce Apps Need an Upgrade
Ecommerce apps that are not personalized show the same home page to a 16-year-old who is buying Nike airmax and a parent who is buying school supplies. Integrating AI for an ecommerce app development company involves more than simply piecing AI components together. Cart modules now need to fully connect with search, recommendations, pricing, checkout, and support.
Where AI Actually Shows Up in Ecommerce Apps
Smarter Product Search:
Commerce search has moved away from matching keywords to understanding the shopper’s intent. If you want to find a jacket that is warm and good for a rainy hike, old search functionality would return items with “warm” in the title. New smart search would return exactly that.
Custom Suggestions:
eCommerce app development services are only beginning to match what was first established by Netflix. AI models have the capability to predict products a shopper will buy. It helps drive conversion by recommending a personalized list of products. When done properly, this should increase the average cart value and improve the shopping experience.
Dynamic Pricing:
For decades, airlines have implemented dynamic pricing. Now, eCommerce apps use similar techniques by keeping track of inventory, competitor prices, and demand.
AI Chat Support:
If there is a case where a customer has a question regarding the sizing of the product, they wait for an agent to assist them the next day. AI chat support allows instant responses. AI chat support is also able to check and assist customers with return issues. It will transfer to a human agent for assistance if the question is too complex.
Visual Try-On and AR:
Apps that sell furniture allow customers to see how a virtual couch looks in their own living rooms. These help to minimize the rates of return after making the decision to ship a product.
Fraud Detection:
This is more important, as an even greater number of issues with spotting fraud have been compounded by the old rules that were used.
The Honest Trade-Off
The maintenance costs of AI in comparison to standard applications are noticeable. Ongoing data and machine training make an AI recommendation system much harder to set up. The personalization may not even be worth the cost for smaller stores with low site engagement. For stores with a few thousand monthly visitors, a full personalization AI system may not be worth the cost in the long term.
Final Take
Many ecommerce businesses can no longer afford to watch the competition when it comes to AI and ecommerce. Much like how easy returns and free shipping became a baseline expectation for ecommerce, AI will become the bare minimum expectation. The competition is not going to see AI development as a bonus, as they have with shipping and returns.
You do not need to implement a full system all at once to keep up with the competition. AI recommendation and support systems may ease the pain the most for your users and may be worth implementing first. Attempting a full system implementation is a sure way to exhaust your resources without improving your business.
Keeping AI as a primary focus in developing integrations, as opposed to viewing it as a tool to simply spike PR, helps build real customer loyalty rather than just one-time purchases. Customers appreciate when apps become more than another retail app. Soon, using the same AI as your rivals will be normal, and differentiating yourself will be imperative.
Should Every eCommerce App Be Using AI?
No. Smaller ecommerce sites with fewer customers and a lower volume of business are unlikely to have sufficient traffic for ecommerce personalization. This will become more relevant once there are sufficient customers with a wider variety of products.
How Long Does It Take To Integrate AI Into An eCommerce App?
It depends on the feature. AI Search can be integrated in a few weeks, while a fully developed and integrated AI personalization and recommendation engine might take several months in order to have sufficient data and an adequate QA period.
Is AI eCommerce Just For The Big Players?
No. Thanks to cloud computing, AI has become a part of ecommerce in a highly modular fashion, making it considerably easier and more affordable for the middle players of the market. Furthermore, developing ecommerce apps has become much easier thanks to the extensive availability of development services.
Author Bio
Kanika Sabharwal is a content writer with a knack for crafting pieces that inform, inspire, and engage readers. Her writing has appeared on well-known platforms like Medium, and she currently writes for Calgary App Developer.
