But with Salesforce’s powerful analytics tool, Service Intelligence for Service Cloud, you can make sense of all your data quickly and get the trusted insights you need to make better business decisions.
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What types of customer service analytics are there?
First, let’s get an understanding of the different types of customer service analytics you may want to use. Some categories are:
Descriptive Analytics: This involves analyzing historical data to understand past customer interactions and patterns, providing insights into what has happened.
Diagnostic Analytics: This category focuses on identifying the america phone number list reasons behind specific customer service outcomes, helping your business understand why certain events occurred.
Predictive Analytics: This uses AI, data, statistical algorithms, and machine learning to identify the likelihood of future outcomes based on historical data, enabling proactive measures.
Prescriptive Analytics: With AI, this type of analytics suggests actions to optimize outcomes based on the insights from predictive analytics, guiding decision-making in real time.
All of these types of analytics can be helpful for your service operations. You might use omni-channel analytics, a form of descriptive analytics, to understand what happened on a recent Tuesday. Then use diagnostic analytics to understand the reasons. Perhaps you’ll see that wait times were too high on voice, because agents don’t have adequate training on that channel. Maybe the average handle time was long, due to one extremely lengthy call. You might then review the call transcript to see if agents need more training on that issue.
Predictive analytics help you forecast the staffing capacity you’ll need during anything from a regular Tuesday to an upcoming holiday season, based on past patterns. You can also use predictive analytics to determine the category or severity of a case as it is logged.
Predictive analytics – in combination with prescriptive analytics – lets your agents make better decisions. For example, you can provide agents with insights — right in the flow of their work — that help them better serve your customers. Analytics helps you optimize service operations.
AI and customer service analytics
The power behind many analytics is AI, which crunches the data and offers up useful facts and suggestions in real time. AI algorithms can analyze vast amounts of customer data rapidly, providing valuable information on customer behavior, preferences, and trends.
In order for AI to do its job, your customer data – from purchases to web engagements to customer service cases – must be connected and unified. AI then takes this clean, reliable data to the next level by serving up intelligent predictions and recommendations to help your team improve the service you provide. AI can analyze your customer messages, for instance, grab the details it needs, and create in-depth responses to questions, speeding up response times and improving customer satisfaction.