9 Ways In Which Call Centers Improve User Loyalty With The Brand

Technology continues to improve the business landscape and organizations need to innovate to stay ahead of the competition. As artificial intelligence (AI) and other technological tools become more common, users are aware of the change, so it is more important than ever that call centers adapt quickly to meet the needs of users.

Why Do Companies Strive To Take Advantage Of Call Center Data To Improve User Participation?

According to experts, 85% of contact center leaders say that data and analysis are important to inform sales and marketing departments. When it comes to data sources, 39% admitted trusting only:

• Income figures.
• The data of social networks.
• Sales figures.
• Team feedback.

These data are important, as is the information that can be extracted from conversations with users. Together, all this could be used to drive organizational change, increase profits and improve the user experience in a call center.

How Can Companies Take Advantage Of The Data Of The Users Gathered In The Call Center?

The analytics of the data extracted from the contact center have access to the Voice of the Client (VoC) without filtering, so that you can know exactly what the users want, how they want it, and what is more important, what is not.

9 Ways In Which Call Centers Improve User Loyalty With The Brand

1) Help Contact Center Leaders Increase On The First Call Resolution (FCR)

The happier users are, the more likely they are to remain loyal to an organization, which is why many companies rate user retention as a top priority.

The first call resolution is the number one metric of the call center, since studies have shown that user satisfaction is reduced by 15% each time you have to call back to solve your problem. Analyzes allow administrators not only to track the volume of repeated calls, but also to root causes so they can quickly improve their FCR and keep users happy.

2) Ensure That Call Center Supervisors Perform Quality Management

Machine learning can be used to generate predictive assessments for 100% of interactions, which allows supervisors to focus their attention on the right calls and use that quality knowledge to provide training to the agents who need it most.

3) Identify The Agents That Obtain High Evaluations From The Users

Machine learning can also be used to identify agents who constantly offer quality experiences to users. This helps supervisors discover tactics they can use to train other agents, as well as the ability to recognize the best agents for their work.

4) Help Call Center Leaders Improve Proactive Reach

By using machine learning in generating user loyalty scores for each interaction with them, regardless of whether they have completed a survey, supervisors can see 100% of who the user users are, the detractors and the liabilities, and guide them with the appropriate efforts.

5) They Allow The Organization To Detect Users With Risk Of Wear And Respond In Time

When a user feels frustrated, he often uses words that can be classified by an analysis solution as a negative feeling. The call center data can be used to identify those users and take measures to retain them.

Understanding how a user feels about your organization can be a challenge, but it is a way to get critical information about the contact center, the products and the company. This is because the analyses of feelings, new technologies that are part of the analysis of the call center, which can help understand what callers, say and how they feel. The analysis of the call center can be used to identify the user’s trust and allow the organization to respond quickly.

6) Find And Address The Interactions Of The Call Center That Lead To A Negative User Experience

Contact center leaders can segment calls with negative feeling scores by agent, team or group and then proactively monitor interactions with negative scores within a specific team or group. They can use this segmentation of feelings to identify optimal opportunities for agent training, decide how to handle emerging problems, and predict the feeling of future interactions.

7) Identify Opportunities To Improve The Commitment Of The User Outside The Call Center

With users interacting with organizations through more channels than ever, it is increasingly difficult to keep track of all the factors that affect their experience. Advanced reports can be used to break down those groups of data by combining call center data with automatic call distribution (ACD), interactive voice recognition (IVR), quality monitoring, workforce management, CRM, human resources, own software applications and even social networks.

8) Allow Contact Center Leaders To Conduct Quality Monitoring On Several Channels

When adding and analyzing data from multiple channels using sophisticated visual tools; supervisors can evaluate agents from many different internal and external perspectives; improve agent training in near real time; combine supervisors’ quality scores with comments from users and the agent; and highlight the best interactions and the most outstanding agents.

9) Facilitate The Organization To Obtain A More Complete View Of The Agent’s Performance

The race to innovate is underway, and it is clear that to improve the perception of users about the call center, organizations must find ways to better use the data that are at hand, and will have to take advantage of the analysis to do so. .

At its core, the analysis automates tasks that would otherwise dominate the time of an agent, supervisor or organization, while offering significant insights that can be used to improve the user experience.