Business analytics: how to leverage your data for growth

Business Analytics serves to transform data into knowledge. When analyzed methodologically, management can make better decisions. The data also provides a picture of the reality of a company over an estimated period. Thus, a clear picture of its capabilities to achieve growth targets is generated.
In this sense, like any data analysis process, the objective is to present real results of business behavior. This is achieved through tools such as data management, visualization and mining, as well as predictive modelling, forecasting simulation and optimization. So how is this process done and what is its importance?
 

Data reliability for business analytics

In order to perform a valid information analysis, primarily structured data is required. That is, data defined for searching. But when faced with Big Data, you need to develop a digital environment to be efficient.
Every process in the company, including production, administration and customer service, is an important source of information. If digitized, it will be reliable and will reach the analysis center disaggregated, sorted and in real time. For example, capturing the different interactions (voice, email, chat) from a contact center will not only deliver valid information. It will transform the user experience by actively listening to the data.
 

The importance of business analytics

A recurrent problem in business management is the stagnation of decisions. As a result, the company's growth is halted and important management indicators, in terms of efficiency, productivity and profitability, are reduced. 
In this scenario, reliable information helps to optimize and streamline business processes. Thus, estimates and grey areas in the process are eliminated. Therefore, analytics enables:

• Shape and evaluate the company's future decisions.
• Review the performance of individual departments.
• Establish communication policies.
   

How to improve customer service through business analytics?

Now, the question is to ground the data in customer service. Consolidating and organizing data is only useful when it has a purpose. To do this, some concrete actions need to be taken.
 

1. Define the most important KPIs

Trying to solve all problems at the same time is not useful. Therefore, it is important to identify key indicators such as:

• First Call Resolution (FCR): first contact resolution rate. It often reflects the performance of customer service agents and the difficulties they may face, despite their goodwill.
• Net Promoter Score (NPS): focuses on measuring higher long-term satisfaction, especially in terms of loyalty. Unlike CSAT, it is predictive of consumer behavior and is often linked to measures of company growth.
• Customer Effort Score (CES): measures the level of effort made by the customer. In other words, it measures customer satisfaction in relation to their shopping journey. 
• Waiting time: one of the main KPIs, as it gives an overview of the overall quality of customer service. On the telephone, for example, there are two types of waiting times, before an agent is called and before the problem is resolved.
   

2. Set short and long-term goals

After determining the critical KPIs, their relationship to the customer service process should be assessed. In this way, short and long-term targets will be set. To do this, it is necessary to align business processes with their objectives.
 

3. Recognizing key trends

An overview of the customer service process makes it easier to make the right decisions. In this sense, business analytics can identify recurring patterns and trends, both good and bad. For example, it is possible to apply software in the contact center to recognize trends in conversations.
 

4. Knowing potential customers

Likewise, a good use of business analytics allows for a better profiling of customers. Comments, interaction with the brand, demographic data, among others, offer a clear picture of the audience. One of the preferred channels to get to know them is live chat.
 

5. Charting the customer journey

Visualizing the customer journey allows you to see what inhibits or motivates the customer. It also helps to define how to adapt customer service to the big picture and to detect current problems. It also helps to increase the Brand Experience, which undoubtedly strengthens the brand's relationship with its customers. In this way, every moment of contact and interaction is exploited.

In this era of artificial intelligence, machine learning, digitization and interconnectivity, customer retention is more complicated. Applying business analytics with technology tools to obtain customer data is a smart decision.