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Performance & Experience Metrics to Examine

Posted on 10.02.2016

Big data, machine learning and artificial intelligence are helping brands redefine the customer experience in many unexpected ways.

While there is often a great deal of information circulating within enterprises and organizations, it remains difficult for those responsible to determine the right blend of metrics as there are so many to consider.

Sixty-four percent of respondents rated their own company as "good" or "very good" at collecting and sharing customer experience (CX) metrics (Temkin Group, The State of CX Metrics, 2015), but only 22 percent gave themselves high marks when it comes to making trade-offs between CX (experience) and financial (revenue) metrics.

The solution for many has been to create better decision-making frameworks, one that measures the quality of the experiences and the current levels of loyalty. Doing so makes it possible to identify the unique drivers that shape customers' experiences, and model different scenarios in order to predict the impact on customer experience. By using a decision-making framework of this nature it's easier to produce positive results (e.g., revenue). Consider the following when analyzing performance in the age of experience today.


Measuring in a range of how pleased or displeased customers are provides an opportunity to influence the likelihood and frequency of purchase. Seek out insights through relationship and transactional surveys to get a sense of what consumers value. The most practical application could be first response time - how long it takes for the user to receive contact in the form of email, phone or chat. Timeliness and speed have a direct correlation with satisfaction. 


Measure customers' ability to satisfy their intent, be it questions about product features or its actual purchase, to see which areas need improvement and attention. Keeping track of whether or not a proposed solution was helpful is very important for future issue resolutions. If a representative was not able to assist a customer now, how could they assist someone with the same problem later on?

Reach & Revenue Growth

Monitor what customers like and the channels they prefer. This provides an opportunity to optimize those that are consistently driving the most revenue growth, and on a more granular level, optimize participation based on time of day, or day of week, where customers have been known to be most/more active. 

Measuring the wrong thing can lead in the wrong direction. Everyone wants to improve and optimize the customer experience, but if you're spending time looking at the wrong metrics, it's slowing you down, while the competitors move ahead.

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