By: Tony Colombo on September 1, 2021
4 min read
The exciting promise of data analytics within a contact center lies in personalized customer experiences. Contact centers have evolved in the last decade and rapid technology advancements have drastically changed how a contact center functions today. In the past, traditional contact centers used static call scripts and a “one strategy fits all” approach, whereas today's modern contact centers are leveraging advanced functionality with AI-powered technology and tools to improve customer interaction.
Before deciding on your new technology, it is helpful to understand how that particular technology can benefit your business. If you are questioning why to use data analytics and tools to improve customer experience (CX) for your business, the answer is simple: to ultimately increase customer lifetime value. Unless you have a good data-driven customer view, you can't serve the customer faster and give smarter responses to resolve customer issues.
Data analytics tools can help you understand the customer preferences, sentiments, make the best decisions, improve customer satisfaction, retention rate, likelihood to buy more from your business, etc. To extract useful signals from data, companies must learn how to identify and make use of them.
The following are a few common tools & metrics used by contact centers to gain real-time insight:
Calls can be monitored in real-time with speech analytics.
Analytics for text-based customer interactions, including SMS, emails, social media, etc.
Analyzing customer interactions with automated services, such as chatbots or web forms.
Agent productivity can be tracked with the help of desktop analytics.
Measuring successful and seamless cross-channel transitions.
Measuring the satisfaction rate of the customers across all interactions through satisfaction analytics.
With a data-driven approach, contact centers can instantly gain real insight into what is working well and what is not. Data lets you take immediate actions with a lasting impact to improve call handle times, customer relationship management, workforce optimization, and much more.
We are sharing some of the best approaches for data-driven contact centers to improve customer experience.
1. Intelligent call routing
Call routing is a system that assigns calls to the right agent. AI is utilized to determine the best available agent while considering the reason for the call as well as the lifetime value and call complexity. Traditional call systems assign calls based on skills and likelihood to respond to a promotion.
In terms of complex technical issues and unresolved issues, this is where data comes into play. Organizations can use caller data, caller input, and historical customer data in conjunction with CRMs and corporate databases to route these calls to the best possible resources while reducing unnecessary transfers, and offer repeating information.
2. Leverage the context of the conversation
Context is vital for the call center because it enables the agents to deliver a personalized conversation with the customer. Context also helps the customers by making the process easier as they don't need to re-explain their problem or question.
With data, agents can get a comprehensive understanding of their customers by visualizing historical data of how the customer has already interacted with the business. Conversational AI is a great way to engage the customers and help you stand out in an extremely crowded marketplace. Comparatively, chatbots are more cost-effective than agents, but they will become irrelevant to customers if left unoptimized. Assistive technologies are now leveraging conversational context to answer questions more effectively.
3. PERSONALIZATION AND CUSTOMER PROFILING
In contact centers, there is no one-size-fits-all approach to customer experience. Every customer wants a personalized experience, and brands need to ensure they deliver on that promise.
As data is gathered from a variety of channels, it is essential to leverage that information to build a stronger profile of the customer. By offering personalized customer experience using predictive analysis, businesses can empower the customers to build trust in self-service, which gives them a personal touch. Consequently, this increases customer loyalty, reduces unnecessary calls, boosts agent confidence, and more importantly sales.
4. ENHANCING FIRST CONTACT RESOLUTION
First contact resolution (FCR) is one of the most critical metrics in contact centers. It is vital to consider the revolving ratio of the customer's first contact . If the first call satisfaction level is lower, it significantly reduces the FCR percentage and the customers have to rely on a callback. Agents can use data analytics to understand the underlying causes of FCR churn. Using smarter data-driven tools like Genesys Cloud CX, contact centers can reduce repeat calls, thereby increasing customer satisfaction.
5. grow customer lifetime value
The customer preferences keep changing and they are hard to analyze without proper tools. Customer profiling can help agents to understand customer preferences to a deeper extent with the data derived from their previous calls and chatbot conversations. Data analytics can help organizations understand their customers, understand what they expect, and predict their needs.
conclusion
In competitive industries, contact centers must upgrade into full-fledged data-driven software solutions. With consistent advancements around big data analytics, AI, and machine learning, it becomes essential for companies to select smart technology solutions to keep up with their customer expectations and stay ahead of the competition.
Data-driven contact centers with real-time dashboards can adjust their strategies more quickly and accomplish their business goals faster. A data driven approach enables agents to communicate with the customer in meaningful ways, and deliver a more personalized experience thus increasing conversion and customer lifetime value.
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