CX Index prides itself in delivering hyper-intuitive and engaging dashboards, so regardless of role, any person in your organization can easily track CX performance.
Each agent, for example, has access to their own dashboard and there are different dashboard views for different tiers of stakeholders (agent, team leader, manager, etc). At the agent level, you can customize what agents can see and they are empowered to review all feedback that relates to them.
In addition, Case Management and a host of other tools can be enabled or disabled with the click of a mouse.
In the Summary View you can filter by:
Filtering allows you to control which data sets populate the graphs on the Summary View page
The Request Date is the date on which a user receives a request for feedback from CX Index.
The Submit Date is the date on which a user completes the CX Index feedback form.
The Request Date is the date that the system requests feedback from the customer. The Request Date applies to all feedback.
The Submit Date is different. Only completed records have a Submit Date. This is the date when the customer submitted the feedback.
These dates can be useful in filtering analysis of the feedback.
Measuring the time lag between the Request Date and the Submit Date can provide insights.
Was the feedback
Understanding these insights allows for fine-tuning of the process for getting customer feedback.
Filter by a customisable set of types of feedback. This allows you to drill into the most feedback type you’re most interested in.
By 'completed records' we mean a customer completing a request for feedback (known as a 'record'). So a 'completed record' is a request for feedback completed by a customer.
The stages for a record's completion is:
Filter by the Agent’s performance you want to review.
Not all feedback is created equal.
The call conditions for a first-time call are not the same conditions as for a caller on their fifth call.
So, we can say that the conditions of some calls are more favourable compared to other calls.
We display this difference by using weather symbols to describe the different conditions.
This provides a simplified depiction of the current or predicted call conditions. It is a barometer – or forecast – of the expected call condition. It also describes the condition at the time of the call.
CX Index sets up the call conditions for you. It is on our product roadmap to allow Admins to customise conditions in the future. Get in touch with your Account Manager if you are interested in this feature.
Conditions range from very easy (clear and sunny) to nearly impossible (thunderstorm).
Net Promoter Score (NPS) a metric to measure customer loyalty and satisfaction. It gauges the likelihood your customers will recommend your business to a friend.
It is calculated based on feedback to one question.
"How likely is it that you would recommend our company/product/service to a friend or colleague?"
Subtract the percentage of your Detractors from the percentage of your Promoters.
It differs from CSAT (customer satisfaction) or CES (customer effort) metrics. This is because it measures a customer’s sentiment about a brand. CSAT and CES focus on a customer's attitude towards a specific interaction.
For a more detailed NPS breakdown, see this article we wrote on NPS 101: Promoters.
CSAT stands for Customer Satisfaction Score. It measures the satisfaction levels of your customer.
CSAT tends to comes into play in relation to a specific customer experience. I.e. asking how a customer how they felt a specific interaction went.
E.g. say you run a survey of 1000 people. 900 of the people surveyed give 'Satisfied' as their response.
You'd have a CSAT of 90%.
We render this in the graph here to a figure out of 10, for the sake of simplicity. It also makes it easier to compare against e.g. NPS.
Track your NPS, Sentiment, Service Quality, Requests Fulfilled, Ease of Interaction, and Response Rates.
Your comment score represents the average of all your customers’ comments. The comment score scores out of 10. The comment score displays:
Use this data to identify operational business trends from the comments submitted:
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