Customer feedback analysis has long been a staple for brands looking for insight into their performance. In the past, simple surveys would ask customers to fill out questionnaires, usually gauging satisfaction by either positive, negative, or neutral. Others ask customers to rate certain KPIs on a scale of one to five.
However, there are a few problems with this.
First, it’s far too simple. A customer’s relationship with a brand is far too nuanced to be reduced to a simple questionnaire. However, a more in-depth survey would take time. Customers either aren’t inclined to do a long survey or brands don’t have the resources to perform them.
Secondly, there are so many sources for customer feedback now. Between social media, review sites, forums, and comment sections, there is a mountain of unstructured data for brands to mine that could provide deeper insight than a simple questionnaire. But, again, we run up against the issue of resources.
How can brands modernize their customer feedback analysis?
AI is a game-changer because it can analyze massive amounts of data quickly. However, in the past, it has struggled with the complexities of human communication. So much of the way we communicate goes beyond just language. You have to take into consideration context, tone, sarcasm, and more.
This is called sentiment analysis.
In recent years, researchers have been using neural networks to teach AI to understand communication beyond the literal level. Learning algorithms began learning how to understand logically fuzzy grammatical structures like sentence fragments. Even before the pandemic, sentiment analysis was approaching 90 per cent accuracy.
Customer Feedback Analysis
The application of sentiment analysis for brands is potentially huge. Instead of assigning employees to try and sort through the overwhelming amounts of feedback on the internet, you can just get an algorithm to do that. Now you can spend more time actioning that feedback instead of accumulating it and crunching it yourself.
The data is better too. Because AI can work at such a large scale, you don’t have to worry about corralling customer feedback analysis into simplistic surveys. Algorithms can analyze feedback based on the way customers actually talk, giving you much more sophisticated insights.
Isn’t it ironic that using a computer to perform customer feedback analysis gives you a more authentic depiction of your customers?
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Of course, technology is only as good as the people using it. Marketsupport has the expertise to know the best tech solutions for your needs. Whether it’s customer feedback analysis or eCommerce CMS, our knowledgeable professionals are ready to help.
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