AI’s ability to handle large amounts of complex data makes it ideal for today’s businesses. According to the State of Data and Analytics Report, in the next 12 months, more than two-thirds (68%) of data professionals are expecting a large increase in data – around 20% across a variety of sources, including first-party data, third-party data, and device data. Meanwhile, companies are expected to churn out about 22% more data on average in the coming year. As data volumes explode, the need for effective management grows, too.
What are the benefits of tracking customer service analytics?
Customer service analytics offer many advantages to businesses that want to retain their customers and also save on costs. These include:
Our research shows that 94% of customers say a good service experience makes them more likely to make another purchase. Analytics help you understand customer expectations and experiences, so your business can then tailor services to meet those expectations effectively.
Identifying pain points: By analyzing customer feedback and complaints, your business can identify recurring issues and address them proactively, leading to improved customer satisfaction.
Operational efficiency: We found that 69% of service agents say it’s difficult to balance speed and quality. Analyzing customer service data allows your company to optimize their processes, allocate resources efficiently, and enhance overall operational effectiveness.
Product and service improvement: Insights from analytics can guide product and service development, ensuring they align with customer needs and preferences. After all, 73% of customers expect you america phone number list to understand their needs and expectations.
Customer retention and loyalty: Understanding customer behavior and preferences allows your business to design strategies that foster customer loyalty and improve retention rates.
What to measure for customer service analytics
While customer service analytics is the broad category, at a more granular level you need to decide which data you want to measure. This is where your KPIs come in. Here are some important ones to consider and how to use them:
1. Customer Satisfaction (CSAT)
To find CSAT, conduct post-interaction surveys and ask your customers to rate their satisfaction on a scale (e.g., 1-5). The average score indicates overall satisfaction.
2. Net Promoter Score (NPS)
After a customer interaction, ask, “How likely are you to recommend our company to a friend or colleague?” Have customers answer on a scale of 0-10. Categorize respondents into Promoters (9-10), Passives (7-8), and Detractors (0-6). Calculate the NPS by subtracting the percentage of Detractors from the percentage of Promoters.
3. Customer Effort Score (CES)
After an interaction, ask your customers, “How easy was it for you to get the help you wanted today?” The scale is usually 1-7, with higher scores indicating a seamless experience. Fun fact: our research found that CES was one of the fastest growing service KPIs between 2020 and 2022. It’s that important.
4. Average Response Time (ART)
Calculate the average time taken to respond to a customer query from the initial contact. Lower ART indicates efficient service.
5. Average Handle Time (AHT)
This metric is the average duration taken to handle a customer interaction comprehensively. AHT is a bit tricky, because you don’t want agents rushing off calls or chats before the problem is solved. The goal is to optimize processes to reduce AHT without compromising quality.