What is Customer Feedback?

Customer feedback is the information we use to evaluate customer satisfaction, an important metric for any business. Insight from analyzing customer feedback data enables us to detect flaws and opportunities in the customer experience, and if we act on these insights, we create opportunity for growth.

Examples of customer feedback

    • The customer contacts you directly, for example via calls, emails, chat messages or support tickets.
    • Customers mention your products, services, or brand indirectly in other conversations, both as a central topic or in passing. This happens often in online forums, social media, and on review sites, for example.
    • You gather feedback directly by yourself by conducting market research, surveys, interviews and questionnaires.

Analyzing Customer Feedback

In all of the above cases, you end up with an often vast and ever-growing stream of text or speech data. Keeping on top of what is being said in that stream is a challenge for any business!

Customer Feedback

Processing and analyzing customer feedback is absolutely vital for understanding the key aspects of driving satisfaction levels in your business:

    • What are customers satisfied with?
    • Where do they demand improvement?

Customer satisfaction drives repeat business, online presence and your share of the market. Harnessing this is undeniably important for yielding maximum profitability.

Traditional Analysis

The traditional way of analyzing customer feedback involves constraining the data to numerical scores. This usually means running a survey where customers respond on a scale from 1 to 5. This kind of data is easy to analyse, but is a pretty drastic compression of customer opinion!

Interpreting and graphing quantitative scores is simple, but involves a big loss of information. Customers are usually much happier if they are freely able to express opinions through writing, and will get you more insight.

AI-Driven Analysis at Scale

While a small number of texts is easy to process manually, on a large scale processing must be done using text analytics. However, such a solution must be sophisticated and scale well to large amounts of data.

This is where Explorer comes in, using state of the art Natural Language Understanding to process qualitative data in a quantitative way, in essence converting text data to statistics.

Explorer analyzes thousands of texts in seconds and automatically presents the topics discussed, customer sentiment, important drivers, and more.

The insights from our tool allow world-leading Customer Experience and Customer Relations managers to gain vital knowledge about what is powering satisfaction in key aspects of their business.

Learn more about the features of Explorer here.

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