The complete guide to data analytics for a customer service manager
Every customer service manager strives to deliver the best possible customer experience. But what defines outstanding service?
In short, it is making sure the customer is happy. However, in reality, the process is multifaceted; the client needs to be completely satisfied with the product or service, interactions with staff, installation, and user experience, to name but a few components of the sales cycle. To deliver the highest quality customer service and nurture positive client relationships, sales teams need to have a positive attitude, a detailed knowledge of the company’s product, proactive problem-solving skills, and excellent people skills. Furthermore, consumers increasingly expect instant response, so reps need to be extremely efficient.
However, as companies scale up, it becomes more challenging to manage customer relationships in detail. When hundreds of customers become thousands, it becomes impossible to get feedback from every individual. Instead, companies have to turn to data; by recognizing trends and patterns in customer behavior, the customer service manager can maintain high standards. Given how important customer satisfaction is to success, it is essential to understand how analytics impact customer experience. This especially the case as technological advancements are significantly enhancing capabilities. For instance, machine learning is transforming the way corporations handle big data.
The key to improved customer service is big data. This approach creates added value for consumers, whilst fostering long-term relationships. However, the main challenge analysts face is getting lost in data; data can tell multiple stories, depending on interpretation. Therefore, it is essential that companies approach analytics with clear goals and laser focus. Furthermore, they also need to make sure in-house data sources are integrated with external data captured across multiple channels. In this article, we outline the three key categories of analysis and how customer service managers can use these strategies to improve customer experience.
The 3 key types of customer analytics
1. Descriptive analytics, or “what happened?”
Descriptive analytics are the most basic type of analytics. In essence, they summarize raw data in order to describe events. These analytics are relevant to customer service KPIs such as CSAT, total conversions, and resolutions to name but a few. The customer service manager can get the most out of descriptive customer analytics by identifying trends like sales increases or demand troughs. These insights inform strategies for regular business events and operational optimization. From here, these analytics are useful for departmental budgeting.
2. Predictive analytics, or “what might happen?”
Predictive analytics are the most useful insights for a customer service manager. These analytics do more than illustrate trends; they anticipate what is going to happen next. Furthermore, thanks to advancements in machine learning, these analytics are increasingly accurate. They are also incredibly invaluable when it comes to enhancing customer experience, as they enable sales teams to forecast customer behavior – which can give companies a significant competitive advantage.
3. Prescriptive analytics, or “what should be done?”
Prescriptive analytics are a relatively new approach, representing a progression of predictive analytics. These AI-powered systems generate advice on how to act on potential outcomes. In essence, they make predictions whilst making recommendations on how to go forward. In a service context, this allows the customer service manager to optimize customer experiences.
The steps a customer service manager needs to implement to effectively leverage analytics
Now we’ve covered the key categories of analytics, we’ll explain how these strategies can be implemented to enhance customer service. Below are four key strategies the customer service manager can implement to leverage analytics to maximum effect.
1. Differentiate the customer experience
To provide exceptional service, sales teams need to understand what motivates their customers. Therefore, it is essential to conduct rigorous market analysis. This will enable the business to uncover new ways to differentiate customers and create a more personalized experience. This is particularly the case if a business is operating in a crowded market of competing against an industry leader. In this instance, the customer service manager needs to ask what it is about the service they offer that provides a unique experience.
2. Deliver personalized service
Although the notion of big data may seem impersonal, it is, in fact, a vital tool for providing personalized customer service. Rather than creating a standard sequence of best practices, businesses can identify specific customer preferences and deliver on these desires. By gaining a more comprehensive view of the customer, companies can nurture more meaningful customer relationships. As Forbes report in a recent article, over 85% of marketers found that personalization brought greater engagement and higher revenue.
3. Develop a singular view of the customer
When creating a customer service strategy, it is essential that businesses develop a singular view of the customer. Customers will interact with businesses across numerous touchpoints, therefore, it is essential that all departments benefit from a consistent stream of information. By combining data into a single repository, businesses can ensure each department has a unified view of the customer. This will mitigate the possibility of friction when moving between multiple touchpoints.
4. Deliver consistently exceptional service
Consistency is crucial to excellent service and customer loyalty. Businesses that successfully leverage data to deliver consistency will see the benefits; for example, Nordstrom is deploying data within their department stores. In store, digital devices will display what customers have purchased before and generate personalized recommendations, delivering what is effectively a personal shopping experience. Bricks-and-mortar businesses must find a way to deliver consistent experiences across physical and digital spaces; if companies can leverage insights to deliver personalized service, they are ideally placed to deliver exceptional service time and time again.
Big data – the key to excellent customer service
In summary, big data analytics make a huge difference in the standard of customer service, no matter the industry. By capitalizing on the opportunities big data offer, businesses can significantly improve customer experiences and streamline operations. In order to remain ahead of developments in customer service, it is essential that the customer service manager develops a big data strategy. By emphasizing personalization, democratizing information, and driving consistency, the sales team can drive conversion rates and encourage return custom. Through big data, businesses can ensure that their customer experience maximizes satisfaction and drives customer loyalty.