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  • Yue Ning

Step-by-step guide on effective customer feedback analysis

Updated: Jul 24, 2019

We can often find valuable insights in customer feedback. They help us build better products and offer better services.

In previous blog posts, we discussed the 3 key questions to answer to better understand open-ended customer feedback. And with an example, we saw the importance of having quantitative answers to all of the key questions.

However, analyzing customer feedback is not a straightforward process. In this blog post, we will cover what are the steps we need to go through and what are the tools that can help us completing each of them.

Step #1: collect feedback from all channels

Customer feedback data is very valuable but hard to collect. And we would like to leverage all we have. Write down the places you would potentially receive customer feedback, either on a review site, or social media, or within your product. Make an effort to collect them to a centralized place for analysis.

Collecting feedback manually could be a very time consuming process. If you are looking for services that help you with this, they are normally in the reputation management and social listening category.

Step #2: analyze for aspect and opinions

To have a holistic understanding, here we would like to bring some standardization to these unstructured feedback and turn them into structured data. To achieve this, we go through each of the feedback, and answer two questions: what are the customers talking about? And how do they feel about them?

The picture above is an example of an analyzed review for a VR headset. Contexts related to aspects we care about are in bold font. The corresponding sentiment is represented by the color of the context.

Products serving this functionality are usually in the feedback analytics and text analytics category.

Step #3: visualize for insights

Our brains are not designed to make sense of large amounts of data, but they are really good at pictures and charts. Here is where statistics and visualization can help. With the structured data produced from the step above, we can visualize it and get valuable insights.

Above chart is the key-driver analysis visualization of a VR headset product, we see that controller performance and video quality are most important to customer satisfaction. It offers product owners an idea on where to prioritize for next iteration.

There are many data visualization tools that can help you with this step. You can visualize basic charts with Excel or draw complex graphs with powerful tools such as Tableau.

Step #4: benchmark and compare

The visualizations offer us a qualitative view of how our products and services perform on each aspect. It would be more helpful to see a comparison - between different offerings in your product line, between your stores of different locations, or even between your product and a competitor product.

Above is the comparison between two VR headsets: the stand-alone battery-powered version vs the premium desktop-tethered version. We can see customers care about different aspects for the different versions. Video quality is more important for the stand-alone version, while game performance and pricing is more important for the premium version.

Most of the tools in step #3 should also help you cover the visualization needs in this step.

Try with your customer feedback

Technology improvements have turned above steps from a manual process that takes tens of hours to a self-service workflow that takes minutes. Interested in what the workflow can get out of your open-ended customer feedback? Take a look at our website or contact to try us for free.

We will later posts more blogs covering the detailed approaches and tips on each of the steps mentioned above. If you are interested in receiving updates, please subscribe here.