Turn CX Data Into Actionable Insights
Measuring Customer Experience (CX) via customer sentiment and Net Promotor Score is great, but these indicators do not provide insights on actions you can take to improve results. Front line workers and their managers need CX insights that shed light on items that can have a meaningful impact on customers. Without the ability to identify actionable insights, the data is of limited value.
The Signals platform is designed to allow front line management to quickly gain insights to large data pools. In our blog post Data Analytics on Chat Sessions, we found that online chat data not only told the CX story, but it shed light on specific actions the company can take for improvement. These included:
- Adding functions/capabilities in the product
- Updating FAQs on the website
- Improving the user interface
- Improving error messaging, and error handling
- Correcting employee interactions with your client base
- Implementing a go-forward data analytics plan to uncover issues in near real time
(Read the blog for the details of our case study.)
Turn your CX data into actionable insights by following the five steps below:
Let the Data Tell the Story
Stories are what resonate with people. Stories are remembered long after the statistics are forgotten. Signals analyzes all of your data (not just a sample), and uses machine learning to construct the story from the unstructured text feedback from customers. The analysts do not need to create a taxonomy in advance of the study. Remove the inherent bias from defined taxonomies, and let augmented intelligence present the findings.
People are Key
The simple goal of a CX analytics effort is to leverage information to better business processes. To do so, information needs to be placed in front of human analysts. Signals focuses on providing everyone with augmented intelligence, combined structured data, semi-structured data, and unstructured textual data. In simple terms, Signals’ algorithms read and analyze data and determine the “who”, “what”, “when” and “where”. A human then uses this intelligence to determine the “why” and decides on the appropriate course of action. This is particularly helpful when reading the emotion in the comments.
Comparative Analysis Speed Insights
One of the key elements in CX analytics is enabling users to dive into multiple aspects of their datasets, in a combined fashion of structured and unstructured data. Analysts need to have the ability to focus on structured “pivot points”, with custom dimensions to analyze and specific visual outcomes. Placing data results side-by-side can quickly show differences in the CX feedback.
Collaboration Speeds Insights
Analysis in a vacuum can lead to sub-optimal results, which is why we built collaborative analytics into the Signals platform. Collaboration on CX analytics opens communication, enables identification of insights, and enables creation of action plans helps align business strategies. This keeps everyone on the same page. This enables companies to extend the analysis to a greater portion of the enterprise so timely, and useful, insights can be added by other team members. Simply put, business teams can make better CX improvement decisions by working collaboratively, rather than working independently and linearly.
The best way to track CX data is to schedule analysis jobs on a recurring basis. This allows for easy side-by-side comparison of changes. It is not time consuming to perform, and can help front line managers identify changes in CX quickly so actions can be taken. The brain processes visuals 60,000x faster than text (source: Jenn Manalo, Sr. Product Specialist, 3M Corp). That is why Signals provides a powerful interactive visualization interface. Displaying current versus previous results side-by-side on the screen can help your business be more responsive to changes in the marketplace.
Follow these five steps and go beyond the sentiment and NPS scores, and use CX data to identify actionable insights.
The Signals platform has pre-built data connectors to many CX sites, including the app stores, major ecommerce sites, social media sites, and review sites. You can also upload your own Excel or csv file. Many times Open Data sources provide data in these file formats. The Consumer Financial Protection Bureau is one example, and we wrote a post using their data here: What Can Public Consumer Complaints Tell Us?
If you would like to try CX analytics for yourself, sign up for a free trial account on the Signals platform. If you have questions, reach us on chat, or email us on email@example.com. We would love to help you on your next CX analytics project.