Using Machine Learning to better understand your customer
by Piyush Rakhecha in General
The popular buzzwords these days without a doubt are “machine learning” and “automation”. However, discussing innovative technology and actually utilizing it to drive your business and reach new clients are two distinct aspects. As a rule, it comes down to personalization and having the information to create solid client experiences.
What really is Machine Learning (ML)? It is primarily a part of artificial intelligence that permits computer models to perceive designs in existing information so that it can predict what to do or what will occur later on. Quite similar to how people retain data and use it to detail their perceptions or forecasts, ML can do it without any bias, processing and rapidly consuming substantially higher information than any human brain can actually figure out. Before focusing on how machine learning will help companies understand customers, we must understand what factors will a customer consider before purchasing a service or product.
Factors showing customer involvement:
The sales cycle of every business involves customers at multiple levels. While making decisions on what to purchase, customers take into account a few important aspects that organizations need to keep in mind such as:
- Perceiving needs: Need is one of the foremost aspects for a customer to make a decision regarding a particular purchase. Thus, every company needs to distinguish their clients purchasing needs and goals.
- Finding solutions: Once companies are able to pinpoint what need drives the client’s purchasing decision, they can effectively identify and provide compelling solutions.
- Dynamic decision making: Companies offering client centric solutions empower the client to make the right decision.
Methods of utilizing ML in business:
- Decoding consumer behavior: With ML, critical data insights from customer behavior and actions can be derived. This helps to identify customer preferences and choices in real time. Different pattern analysis techniques are used with machine learning to understand what customers purchase and when they purchase it.
- Predictive analysis: With data of consumer behavior and understanding the customer preference, predictive analysis can help an organization to estimate their sales and accordingly set a future target. This also allows the companies to save on resources used on a particular service.
- Chatbots and virtual assistants: Instead of general responses, machine learning enables chatbot and virtual assistants to learn when they should use specific responses, when to gather information from users and when to pass on the conversation to a human agent. This helps provide round the clock service and retain good customer relationships.
Every process and product in a business has different requirements. This makes it a tedious task to design a unified smart automation solution which will interact with customers. And it is even more challenging if your business runs on old architecture. Nuage is here to help you solve your concerns and develop a smart and dynamic architecture for your business. This will allow you to easily adapt to new changes and also implement machine learning based systems seamlessly.
To know more how we can help you contact our experts at, info@nuagebiz.tech