You might have heard Qualtrics discussing X-data (experience data) and O-data (operational data), and wondered, should we care? The answer is yes, and here’s why.
Let’s start with a basic premise that no individual experience exists in a vacuum. People form their opinions about any experience based on a collection of different factors. The more we can understand those factors, the better we can extrapolate the insights about a single personal experience to form a deeper understanding about other people’s experiences.
Now to my discussion of Xs and Os, starting with customer experience (CX)…
Let’s say that your company has this data:
- X-Data: NPS responses
- O-Data: Customer product ownership and support history.
With X-data, you can calculate an NPS for the customers who responded. You can also dig into their feedback, and hopefully understand what’s causing promoters and what’s causing detractors.
That’s extremely valuable, but it only tells you what’s going on with the people who happened to respond to the survey.
By combining O-data with your X-data you can examine (especially through predictive analytics) what types of products and service interactions lead to promoters and detractors, and use this data to calculate the NPS for large portions of your customer base–—even for customers who never responded to a survey.
It could be that ownership of a certain version of a product tied together with a specific type of customer service problem is highly likely to create detractors. You can identify all the customers with that profile and take proactive measures to correct the issues — even though they may never have complained.
Result: More loyal customers and more targeted use of your resources.
This works across all areas, even with employee experience (EX). Let’s assume you have this data:
- X-Data: Employee satisfaction study
- O-Data: Employee tenure, promotion history, most recent performance rating
With X-data, you can determine how employees feel about their next steps at the company. You can also dig into their feedback, and hopefully understand what’s causing higher vs. lower levels of career satisfaction.
By combining O-data with your X-data you can examine what influence tenure, promotion history, and performance may have on satisfaction, and use this data to identify segments of employees to invite to participate in a high-potential development program.
Result: More high-performing workforce because you’re investing in the right employees.
Hopefully you can see how the combination of X- and O-data can increase your CX and EX insights. The same dynamic also holds true for brand experience (BX) and product experience (PX). By combining and analyzing the different types of data, you can use feedback from a few people to build an understanding of many, many more. This allows you to better prioritize investments, while making more targeted and impactful changes.
The bottom line: X- and O-data together provides an analytics goldmine.