Toby Lam from Payment Asia: Merchants are good at selling commodities and services to customers but they are not so good at data mining.
Reference Link: Press Here
Data is a treasure trove for businesses providing that it is analyzed properly. One could say that every merchant should set up a special analysis department dedicated to data analytics but in practice we don’t see it happening too often. The reasons are cost and business model. Merchants are good at selling commodities and services to customers but they are not so good at data mining. Therefore, they need a third party to take care of their collected and stored data. Payments Asia is one of those solutions that help merchants analyse their data.
Payment Asia provides merchants with solutions for payment processing and it also helps them deal with digital marketing, website, and mobile application development. The company has a number of successful cases for merchants in generating traffic to their websites in order to increase sales and conversion rates. It is important for merchants to understand their customers and their purchasing behaviour.
Based on customer payment data, our dedicated team performs advanced data analytics for merchants. For example, the team performs customer segmentation for merchants based on consumer, business, and volume. This information provides powerful insights into consumer purchasing trends, which influences marketing activities and product designs.
AI assistants / bots
More than 4.1 billion people use messaging apps. Merchants have a new business opportunity due to conversational chatbots. They are integrated into different kinds of messaging platforms such as Facebook, WhatsApp, WeChat and Skype.
A number of studies also showed that (i) 65% of the customers prefer using a messaging app when contacting a business, (ii) 50% customers prefer making a purchase through a messaging app and (iii) more than 50% of the customers prefer a business to be open in 24×7.
In the financial industry in particular, handling that large amount of the customers’ inquiries from different sources is a challenge. The data collected from the customer services department is not fully analyzed to provide the necessary insights for the business owner. For this reason, the owner cannot further improve the quality of services / products. To drive the customer engagement, especially in the financial industry, our data science team is developing an AI-enabled customer service chatbot for multiple channels providing the best advice / answer to the customers’ inquiries in 24×7.
Another practicality of data analytics is for the trader in forex or any other market, where it is crucial to be aware of the mood in those markets. The trader has to consider both his own and the others’ opinion. Currently, our data science team is developing an Artificial Intelligence (AI) sentiment monitoring engine to analyse financial news, stock news, and social media in real time. We adopted the state-of-the-art Natural Language Processing (NLP) and Deep Learning to train the model for getting the sentiment score. The current system is scalable to handle tremendous amount of data. It would generate sentiment indicators and extracts trending keywords which are useful information for financial analysis. The extracted information is valuable for the traders to evaluate the market.