CloudInteract offers a wide range of both near real-time (NRT) reporting and historic reporting including Lex bots for voice/text etc and Contact Lens analytics to help you make data driven decisions and understand patterns and trends over time, curated in Power BI, Tableau or QuickSight.

In the first of our Business Intelligence blogs within the Expert series, our resident expert Rush Nour looks at how to utilise the wealth of NPS data captured by Amazon Connect, and transform it into tangible business value.

Let’s take a look….

NPS – More than just a number

Net Promoter Score, or NPS, is a standard measurement of customer satisfaction, often captured at the end of a call or chat between a customer and a customer service agent. This is important for the agent’s progression, their manager’s targets, and ultimately the business itself. After all, a happy customer is a loyal customer.

A critical measure in tracking customer loyalty, contact centres commonly task their employees with meeting a target NPS on a monthly basis, ensuring customers receive a high level of service. But there’s a lot more to it than one big number.

Data nuances = significant insights

Focusing on the headline number provides assurance to the business, but it doesn’t explain how the score came to be given. Amazon Connect amasses a wealth of data during every call; the challenge is turning this into meaningful information. Dashboards must be interactive and intuitive; they must serve as quick-glance aids to info, as well as deep-dive analysis tools. They must also be appealing and accessible to everyone.  

Power BI offers the opportunity for client to harness the data into stunning visuals – let’s look at what an example below, achieved from the raw data.

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NPS and how to explore it

From this single dashboard, we can see real-time and historical NPS, and apply filters for deeper analysis:

• NPS scores over time; for a particular time period, a certain queue or group of queues, for a particular agent
• Correlation between NPS and number of holds  - if callers are frequently put on hold, there may be knowledge gaps that require Agent training
• Average queue duration
• Correlation between NPS and time in queue - if longer queues mean lower scores, is there adequate resource in place?

The overview looks positive, but what happens if you isolate a period of time, or look at a particular queue?

Persistently low scores within a certain queue are concerning, raising a number of questions;

• Is the score driven by specific Agents?
• Are these Agents established in their role?
• Have they been successfully onboarded?
• Is more training required for that skill set /knowledge base?
• Has the contact flow recently changed?
• Were there any connectivity issues over the selected period of time?
• Does the contact flow relate to a new productor service that’s unfamiliar to customers calling in?
• Is the queue sufficiently staffed to handle the level of calls?

Straight away, by simply scratching the surface, a seemingly decent NPS can reveal multiple areas for improvement.

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Of course, not every caller chooses to rate their experience; this tends to smooth the polarised values into amid-range score that offers little insight to the customer’s thoughts and feelings. This is why our Data Analytics Specialist, Rush Nour, spends so much time visualising the data we do have, in order to understand the data we don’t.

Join us next time as we explore Surveys presented to customers post-call, including metrics on Surveys Offered, Started and Completed; Surveys and Results trending over time, and Question results by Agent and Queue.

Still to come: Supervisor Evaluations; from trending metrics to contacts evaluated per queue/dept/Agent, we’ll delve into how we can learn even more about servicing customers better.

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