In today’s data-oriented environment, using predictive customer service is essential for excellent customer satisfaction and customer care. While there is an overwhelming amount of data out there, most organizations only use a small percentage of their data. However, with the right analytics and AI technology in place, companies are able to take more advantage of their resources. With the help of analytics and AI-powered predictive customer service tools, companies can understand their clients better. Predictive customer service allows organizations to understand what customers are interested in. This enables them to predict their future spending habits, offer personalized ads, and recommendations.
Understanding your customer needs
Perhaps the most obvious but also the most important aspect of predictive customer service technologies is the way that it allows companies to know and predict when a customer or client is looking to purchase, as well as the products that they are likely interested in. Using AI and predictive analytics to better understand your customers can not only help you increase sales, but it can also help you in your branding efforts. By being able to communicate tailored suggestions to your customers, you can make sure that they only receive promotions and offers that are relevant to them. When it comes to contact centers, this means that with the help of omnichannel solutions, your agents will already know the type of client they are talking to along with their specific needs.
Fine-tuning your company resources
Predictive customer service technologies can also help you adjust your own business model. With optimization technologies, you can analyze your customer interactions to help you optimize your pricing models. Additionally, you can anticipate higher or lower volumes of calls, letting you adjust your staffing policies accordingly. When running a contact center operation, this means that with the help of predictive customer service technologies, you will be able to calculate the number of agents needed during various inbound or outbound campaigns.
Rethinking your service model
Analytics can also help you rethink your company’s service model. With enough data, predictive customer service technologies can help you understand your customers’ life cycle stages and help you increase sales depending on these patterns. For example, insurance companies often use analytics to understand the major life events of their clients, such as a new house purchase or getting a driver’s license. Such technologies enable you to market especially relevant services or products to your customers.
Targeted customer communications can be beneficial for both the client and the company’s side. As a customer or client, predictive customer service technologies allow you to receive communications that are relevant to you, letting you avoid the burden of being spammed with irrelevant offers. On the client-side, it can help you gain insights that would otherwise be impossible. By using a data-driven approach, you can understand your customer needs, fine-tune your company resources, and rethink your service model in order to be able to provide excellent customer service through all lifecycle stages of your customers.