Artificial intelligence is doing wonders in the fields of technology, health sciences, and raising living standards. Similarly, it has not left behind in the field of online reputation. To better get in touch with the customers, AI is playing a great role in dealing with customer experience. Here are two areas of customer experience which AI helps to transform.
1.Escalate the insights with Natural Language Processing
Nowadays, customers can interact with brands in several ways. They have several mediums with which they can talk to the brand. Social media is the biggest. Along with that, email, web chats, direct feedback on the stores. When such interactions take place, brands get enormous data. This data helps them in their research processes. Insights generated can be used to scale the business. In short, companies have several ways to get in touch with their customers and get useful information.
The question arises here, what is the role of AI in this scenario? Well, NLP (Natural language processing ) combines the AI and derive the useful results from customer data. It will draw your graphs and get you clear stats. Moreover, they can be further used to scale the business. It will align the processes of knowing what your customers like and dislike. It will help the brands to make effective decisions that earn them profit. Also, the best strategic plans and one to one customer experience.
2.AI helps to boost the Personal Recommendation
When we buy something online then we always look out for the feedback. Sometimes, the brand recommends such things which are of no good use. Usually, brands use 2 types of recommendation approaches.
The one is totally based upon the customers. Where they consider the customer’s opinions and devise their products according to the customer’s need and recommend them. The second one revolves around the product. When the company makes the product irrespective of its consumers taste but still their customers show some interest. However, products made on consumer preferences are of utmost importance.
Whichever approach is adopted, you may face 2 challenges in the recommendation process.
When it gets scalable
When you have enormous data, then it would be difficult to handle and balance the accuracy of predictions and recommendations with performance.
Hurdles in initial steps
You may face difficulties in the start when you introduce a person to the system. You won’t have enough information about the customer. So, it would be difficult to recommend.
By now, you may have a clear idea about how the AI is transforming the customer experience by integrating the machines interaction into customers preferences. Companies are getting indulged into AI techniques to get a competitive advantage.