3 Ways to Use Data Analysis in Customer Service
Understand how to use data analysis in customer service in 3 ways and learn tips to improve the customer experience with Big Data.
Data is information that has value. Therefore, when doing the data analysis in customer service, companies find valuable information that is used to differentiate themselves from the competition and offer something unique to their customers.
Big Data tools help treat, analyze, and extract information from a very large database. After all, without logical organization, data sets are like shuffled cards.
The organization of the available information is what makes the difference when it comes to filtering and finding data to validate an action or identify a trend.
To obtain consistent results, the service team needs to know what they are looking for and thus direct the focus of the analysis, avoiding distractions during the work.
Do you want to learn how to use data analysis in service? Read on and also learn how to improve the customer experience with Big Data Analytics.
Have a good read!
How to use data analysis in service?
Data analysis in customer service can be used to assess the past, present, and future of a company's strategy.
Um McKinsey consultancy study highlights that data-driven organizations are 23 times more likely to acquire customers, 6 times more likely to retain customers, and 19 times more likely to be more profitable.
In addition to collecting data on various aspects of the business, knowing how to use them strategically is what will set your company in the direction of better results.
To create a data-driven, i.e., data-driven culture, data analysis in customer service can be used in three ways. Check it out!
1. Descriptive analysis
A descriptive analysis it is the first step in the study of collected data. The manager separates the service indicators, organizes and uses it to make a diagnosis of the moment.
The KPIs selected and evaluated are those that show the performance and quality of the service, such as:
- Customer Satisfaction Score (CSAT);
- average waiting time;
- average service time;
- First Contact Resolution (FCR);
- call abandonment rate;
- Net Promoter Score (NPS);
- Customer Effort Score (CES);
- among others.
This analysis shows whether the relationship with the client is positive, how the indicators varied within the analyzed period, and which aspects need improvement.
Thus, the manager can make optimizations in the operational service processes and list investments in tools and services that contribute to the evolution of metrics.
2. Predictive analytics
As for the approach predictive, data analysis in customer service focuses on what can happen. The objective is to be one step ahead, anticipating scenarios and trends that may affect the market.
Studies of this type focus on customer behavior to identify needs that are still emerging. Today's machine learning (machine learning) tools perform increasingly accurate analyses thanks to the evolution of technology.
This allows the company to improve the experience offered to customers according to their expectations, which generates a strong competitive advantage in the face of the competition.
3. Prescriptive analysis
A prescriptive analysis it is an evolution of predictive analysis. Through systems that use artificial intelligence, managers can obtain direct insights about what to do according to the results of the evaluated scenario.
This is the most futuristic type of data analysis in customer service among the possibilities of use presented and the one that will require the most investments in Big Data analysis tools.
In return, service managers optimize customer experiences through effective actions that truly strengthen the relationship.
How to improve customer experience using Big Data Analytics?
For 65% of those interviewed in a Econsultancy and Adobe research, improving data analysis is a very important factor in providing a better customer experience.
If data has value, companies need to take advantage of internal and external databases, using Big Data Analytics resources to increase the level of service offered.
To help you out, here are tips on how to improve the customer experience with Big Data Analytics.
Learn the difference between your company's experience
With the support of data analysis tools, managers understand both motivations and what causes bottlenecks for clients.
This helps to refine the target audience profile and personalize the experience so that it meets the needs sought. In this way, it is clear what makes the company's experience unique and, also, what can be explored to increase customer loyalty.
Focus on personalized service
Big Data Analytics software is very useful for offering personalized customer service. This is because these resources direct the creation of standard good practices, but also identify specific customer needs.
Thus, the company knows better the conquered consumers and invests in relationships with each one in a different way, offering the desired solutions and creating more meaningful relationships.
Share data internally
The customer view and profile are not only useful for the Service and Marketing areas. All sectors need to know the type of person that the company prospects and seeks to strengthen relationships.
Gather customer data, reports, and analysis in a common place for every company to access. The proposal is that the teams know and know how to relate to the customer profile, contributing to creating a frictionless experience at the different points of contact.
Have consistent service processes
Data analysis in customer service helps companies to offer a consistent service and increase the loyalty rate.
With the insights obtained, the customer experience is designed so that, regardless of the channel, they have access to the same resources and resolve their requests with agility.
This planning helps the customer to receive exceptional service, whenever they activate the company's channels.
Does your company offer quality service?
Now that you know how to use data analysis in customer service, bring the team together to evaluate the service considering the data that the company has available.
To help you, Get a free diagnosis of your CX operation. With the insights, your business can improve the level of service experience and correct the necessary points in the journey.
Talk to our experts to learn more about Cloud Humans and learn how we can help you achieve your business objectives.