2 ways to measure customer experience performance

Is your customer experience making you money? Is it costing you money? Do you know?
Exceeding expectations or solving customer problems: What’s more important?

Let’s say you set out to improve your company’s customer experience to drive better organization performance (kudos to you). What will be more important in attaining that goal: exceeding customer expectations, or solving customers’ problems?
6 customer experience statistics - and the performance implications for your business

Measuring customer experience: 6 metrics for the sixth step

Measuring customer experience: 7 metrics for the fifth step

If you're just joining us in the Measuring the Customer Experience series, you can play catch up by taking a look at the metrics I've shared so far.
Today, we're covering the metrics you should check to see how you're doing at the fifth step common to every customer experience: proving your promise as your customers are using your product or service to solve their need.
Measuring customer experience: 5 metrics for the fourth step

Measuring customer experience: 5 metrics for the third step

As a reminder, every customer experience starts with a person, who's got a need they would trade something of value to have solved. Their experience is something they pass through - it's what happens and how they feel as they realize they realize a need, learn about options to solve it, buy, solve the need and even evolve to another need over time. This week we look at the metrics you can use to see how the third step of your customer experience is impacting your business performance.
Measuring customer experience: 4 metrics for the second step

Measuring customer experience: 5 metrics for the first step

Stat of the week: What does success look like?

We've covered some provocative stats pulled from the Aveus study Finding the Performance Payoff in Customer Experience. I shared that whether (or not) an organization has a well-understood definition of customer experience is such a strong indicator of performance that we used it as the primary distinction in the findings. For fun and for clear reference, I called these groups “Haves” – those that have a definition that everyone in their organization understands – and “Have Nots” - those that, well, you get it.
