Next in our Expert Analytics series, we’re moving on from NPS to Amazon Connect Post-Call Customer Satisfaction (CSAT) surveys, for a deeper look at how customers really feel about your business and how we at CloudInteract visualise the results.

For finer-grained non-NPS type reporting, CSAT Surveys are an extremely powerful way to receive real feedback and insights from your customers on the quality of service received. Visual representation turns a static number into a fascinating barometer of changing customer sentiment and brand perception over time, enabling you to continually improve the customer experience.

By configuring your questions to be scored on a numeric range using any scale between 1 and 10 (0-9 response), it’s possible to measure CSAT scores given to curated questions to help assess Agent experience, knowledge, attitude and overall level of service provided to your customers.

Our Surveys dashboard below presents the overall CSAT score (across all answered questions) as a high-level stat, trending over time, and included as a comparison data point against individually scored questions, Agents and Queues.

This makes it easy for an Agent Supervisor to understand:

1. The current level of CSAT, and whether that score is degrading or performing better over time

2. Individual Agent performance

3. If there are lower CSAT scores associated with particular queues, as potential problem areas requiring further investigation

Agent Supervisors can focus in on potential issues simply by selecting a particular queue, to filter all question scores and agents associated with it. Similarly, by using date range filters it’s possible to target specific points in time to help diagnose problem areas, providing insight to correlations and causations.

What If Customers Don’t Answer Every Question?

As with NPS, there will be customers who choose not to answer CSAT questions. Of those who do, the numbers often drop as they progress through the survey. So in quantifying CSAT scores, it’s important to contextualise by looking at percentages.

Let’s consider this example; in a 4-question CSAT Survey, an average score of 9 for the 4th question ‘How likely are you to recommend AnyCompany.com to a friend?’ certainly sounds impressive. But, when data shows that only 16% of customers offered the survey started it, and only 22% of those reached and answered question 4 – it suddenly becomes less meaningful.

So, let’s say that the percentage of customers staying in the survey and reaching question 4 increased noticeably in Jan 23 – a month in which the first 2 questions had been reworded. Shorter listening time led to greater engagement, and resulted in 43% of customers completing question 4, the end of the survey. Thus the average score of 8.7, whilst lower than 9, was more statistically valid and a truer reflection of how customers felt about recommending the company to friends.

Capturing and visualising CSAT data is therefore invaluable not only for tracking service levels, but also the effects of any changes made to contact flows, operational procedures, staffing or technology.

Troubleshooting with CSAT

Looking at it from a different perspective, we could start from the top level - AnyCompany.com’s overall average survey score of 6.8. Putting aside percentage of customers moving through the survey, we could ask ourselves; is there a question that frequently destroys the overall average?

- If the question is about the Agent’s handling of the call, in terms of attitude and knowledge, that could indicate a need for additional training

- If the question is about the time spent queuing, there may be an issue with workforce management

- If the question is about smooth progression through the IVR, the prompts may need to be reviewed and rewritten to improve signposting

CloudInteract’s Data Analytics Specialist Rush Nour makes it his mission to surface complicated data in a way that is visually stunning, makes immediate sense, and yet can be filtered and drilled into for deeper insight and further analysis. As powerful tools for monitoring Agent and service performance and keeping track of brand perception and operational issues, Rush’s BI dashboards are available 24/7 and can be easily shared and collaborated upon.

So here’s a recap of why understanding CSAT data is so important. It can:

- Create better customer experiences

- Prompt ideas for product and service improvement

- Identify and resolve common process bottlenecks

- Help find brand advocates

Join us next time for Agent Evaluations – from trending metrics to contacts evaluated per queue/dept/Agent, we’ll delve into how we can learn even more about servicing our customers better.

Or, if you can’t wait until then – contact us now to find out more.

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