Data Analytics for Customer Service and Customer Experience
- November 28, 2023
Data analysis refers to the process of analysing data sets to extract meaning and information. So what is the importance of data analysis in customer service and customer experience process. Let’s examine it together.
Importance of Data Analysis
Data analysis systems are used to optimise the performance of companies. It enables businesses to make the right decisions and take steps to move the company forward with its analyses.
The company also uses data analytics to analyse customer trends, make the right decisions, and design better products with customer satisfaction in mind.
Data Analytics for Customer Service and Customer Experience
The company’s data analysis evaluation plays a major role in determining the services to be offered to the customer and in creating a positive customer experience. Data analysis ensures that customers’ requirements and expectations are met.
In order not to lose customers to competitors, to meet customer expectations and to determine the service to be offered, the use of data analysis should be adopted.
Customer Satisfaction Analysis
We can summarise the steps you need to follow for customer satisfaction analysis as follows;
- Firstly, it is determined what it is that the customer will benefit from the company and its purpose.
- Then data about the customer is collected.
- Erroneous data is cleaned to obtain more accurate results and to avoid negative feedback from the customer.
- After these processes, the service is provided according to the customer’s data analysis.
Methods of Measuring Customer Satisfaction
- Customer Satisfaction Score (CSAT): The CSAT is a type of customer satisfaction survey. The more positive responses you receive, the more positive the customer satisfaction will be.
- Net Supporter Score: The percentage score of supporters is calculated by subtracting the score of those who received a negative response.
- Customer Effort Score: A metric where customers rate the question from 1 to 5.
- Direct Feedback and Customer Satisfaction: It is the method in which customer satisfaction is analysed directly through a questionnaire.
- In-App Customer Surveys: It is the survey method offered to the customer while the customer is using the service. It brings immediate response and high engagement.
- Post-Service Customer Surveys: Questionnaires directed to the customer immediately after the service. This is done via email or live support.
- Customer Surveys by E-Mail: It is a survey method that provides in-depth responses from customers with low customer participation, but also from customers who participate.
Data Analytics to Improve Customer Satisfaction
The use of data analyses; reaches customers directly and collects their evaluations of the company. With data analysis measurement methods, customer satisfaction is evaluated with questions and questionnaires directed to the customer. The collected data can be analysed and steps can be taken to ensure satisfaction.
Customer Retention Analysis
In data analysis, you can use customer trends and historical comparisons in your system. Thanks to these analyses, you can enable your company to make better decisions and increase efficiency.
Customers willingly give you their data when they buy services from you. Companies should use this data wisely. Marketing efforts should be personalized to the customer. The company should not only collect data, but analyze it. Use the knowledge gained to attract customer interest and increase customer loyalty and satisfaction.
Methods to Measure Customer Retention Rate
- Understand customer expectations,
- Use CSAT,
- Conduct CSAT surveys,
- Read customer reviews,
- Evaluate customer survey data,
- Personalize your data for your customers,
- Design pricing in such a way that your existing customers will want to repeat business with you,
- Implement cross-selling and up-selling strategies,
- Reward your repeat customers, thus increasing existing demand.
Data Analytics to Improve Customer Retention
When you understand your customers, learn who they are and what they need, you can establish a real dialogue with them. Having a continuous customer group is the secret of a successful business. You cannot have loyal customers without satisfied customers.
In order to have satisfied customers, it is necessary to really know the customer. It costs seven times more to acquire new customers than it does to retain existing customers. Companies need support from data analysis software to recognise and retain their customers and to determine the customer’s goals.
The service to be provided by analysing the data obtained from the existing customer will improve the customer retention rate.
The Future of Data Analytics
Data analytics is a constantly evolving field and will remain important in the future.
AI plays a big role in the future of data analysis. Artificial intelligence technologies have great potential for collecting and analysing data. These technologies, which minimise the need for manpower, allow these data to be analysed from digital platforms for the desired purposes.
Data analytics will continue to have a major impact across many industries and will become even more complex with evolving technologies. Therefore, data analysis skills and technical knowledge will be even more important in the future.
You can contact us for a 14-day free trial of Grispi, which offers detailed reporting fields to help you increase customer satisfaction.
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