In the 21st century, the retail business has changed, its dynamics are now very different from the past 10 to 20 years. Retailers are facing many challenges to keep up with the modern needs of digital commerce.
Retailer do not want their shoppers to go empty-handed and they also do not want to show an empty page if the shopper is looking for a specific product. Furthermore, every individual has their own interests and unique choices. If we go on with the strategy to devise the same online system for all types of customers, it would not be a good idea. The best is to go for a solution tailored to the needs of different customers. Customers should get a live shopping experience through their e-commerce journey.
Salesforce Commerce Cloud has embedded an AI-based mechanism called Commerce Cloud Einstein to cater to the retailers’ needs of targeting customers on an individual basis. Commerce Cloud Einstein’s AI algorithm gets the data feed from B2C commerce and gets trained from customers data, their browse history, purchased items, etc.
Commerce Cloud Einstein mainly works on the below-mentioned areas to generate customer based shopping experiences.
This feature utilizes machine learning to generate recommendations based on the individual experience. The primary target is to provide the appropriate product at the right time. This recommendation leads to more sales as the customer will be getting the products based on their shopping experience and interests.
Predictive sort allows the retailers to automatically sort the order of the products displayed on the category or search pages. The product that is more relevant to the individual customer will be displayed on top. With this the shopper does not need to scroll or browse through multiple pages, they get the desired product on that very page. On mobile devices, it will be very helpful as the screen is small.
Einstein provides a shopping cart dashboard to analyze purchased items by multiple customers. Merchants can select items and learn what other products shoppers are buying along with the selected product. This helps in creating product based sales and bundle purchase categories. It generates data sources from the B2C Commerce; browse and purchase history.
There are situations when a customer searched and landed on the page without any results. This happens may be due to incorrect spelling or there is no item matching the searched criteria. A search dictionary takes all the site searches and terms used by the customers to search the items and then it generates the recommended synonyms to be added. As a result, if customer has used the term that does not matched any search the customer will not ends up with an empty page. The search dictionary will provide the results from the synonyms list and the customer will most likely to have the product they are looking for.
Search recommendation is targeted to provide user-specific search recommendations to the customers. It applies the algorithm to the searched data of B2C commerce to identify which resulted products are relevant to each shopper. As some customers will be getting different search recommendations on press the letter ‘S’ while others will be getting other search recommendation.
With Commerce Cloud Einstein AI-based commerce is now much more comfortable then we can imagine.