Smart E-commerce is on the rise, the world in now in the era of super retail. The implementation of AI technology in the E-commerce retail industry can be seen anywhere.
According to a research conducted by the Common Wealth Magazine, after looking into 1000 Taiwanese businesses, they discovered that most of the AI resolutions adopted by the retail industry, logistic services and the service industry are mainly designed to improve “external” services. Common examples of “external” services would be the service efficiency and recommendation systems.
Ｍany types of AI technology can be found on the market. However, choosing the right type for your business is the key to a successful digital transformation.
Know Your Consumers Inside Out With the Adoption of AI In the E-commerce & Retail Industry
Machine learning can help retailers know their customer. The data collected from customers’ favorite websites, apps and social media can help businesses understand consumers’ preferences and patterns to further offer a personalized experience. Picture the online clothing shop you always visit, if the website is able to offer suggestions according to your specifications, the weather or for your next date, wouldn’t this elevate your overall brand loyalty?
Predict Consumer’s Behavior and Plan Your Game Early With the Help of AI
According to an article about AI Supply Chain, PChome analyzed their sales data in the past and concluded the popular items from all areas. They used this information to prepare for the event, making sure the fluency of their operation. PChome paired up with 14 logistics companies and set up additional pick up stations to cope with the 8 times more than average orders. We can tell from this example that the accuracy of AI data empowerment can be of great help in the preparation game for the E-commerce industry. It increases the operating efficiency in both offline and online channels and saves more time and budget for businesses.
Simplify Your Logistics System and Develop Your Supply Chain
AI technology serves a great influence in the supply and development planning process. Take Sweden clothing brand H&M for example, the brand is often criticized due to the waste of resources and environmental harm resulted from fast fashion. H&M was pushed to transform into a sustainable clothing brand and they seeked the implementation of AI technology in their production.
With the accurate prediction of AI, the company was able to foresee the potential items that might attract customers. They then design their product less in quantity but much in variety, offering customers a wider range of choice. This smart movement created a win-win game. Which helped the company build a sustainable business that automatically restocks, manages inventory and controls the time spent in logistics.
The Substantial Results of AI Implementation in Taiwanese E-commerce Industry
Ping Shuo Ting, Chief of Digital Information Technology from Carrefour Taiwan stated his opinion about Digital Transformation in the C-Suite AI Forum held by Business Next and CloudMile last year. He stated, “Carrefour has been eagerly promoting digital transformation. One of our top goals in this movement is to drive the sales growth of all distribution channels through the application of AI, ML, and other novel technologies. What can these technology do? For example, the grouping, categorization, cross-platform sales, and so on through AI technology. This can transform offline consumption behavior online, bringing more members and create a new consumption mode.
Great minds think alike! Online shopping platform momoshop utilizes AI technology to help form strategies for warehouse management and logistics distribution. Cutting down the labor costs in the shipping process and transshipment stage to successfully optimize shipping efficiency.
Build a Personalized Shopping Experience With AI Recommendation System
The AI Recommendation system allows consumers to upload the items they wish to purchase, they can easily find highly related products. At the same time, the system would be able to stay ahead of the game and generate the extended items which the consumers might also be interested in. For example, when searching for “beers”, the system can analyze the consumers’ behavioral data and recommend other products like “beer bubble maker” and “bottle openers.