Video: Analyze Customer Feedback With NLP to Get Actionable Insights
Published on — Written by Wonderflow
Most companies have more sources of customer feedback than they realize. Customer surveys and reviews aside, call logs, support tickets, and brand mentions on social media all are customer feedback, rich with insights.
Many of the world’s most successful enterprises have automated the entire process of gathering and analyzing their customer feedback using AI-driven Natural Language Processing (NLP) tools. It gives them an edge over the competition and allows them to extract actionable insights.
If you haven’t automated analyzing customer feedback yet, you’ll want to start doing this, ASAP. Going through customer feedback allows you to understand your target audience on a deeper, more intimate level. It enables you to improve upon your product/service to win over more customers.
In this guide, we walk you through all you need to know about analyzing customer feedback with NLP, including:
- Why it’s important to review customer feedback
- The difference between data and actionable insights
- How to transform your data into insights
- Analyzing customer feedback using NLP
- A step-by-step guide to collecting and analyzing customer feedback
Do you prefer text over video? Find our full blog post here.
Let’s discuss how to analyze your data to come up with these insights.
If you’re looking at quantitative data, this is fairly straightforward. Say that you’re using the Customer Effort Score (CES) to benchmark your customer satisfaction levels, for instance. Because the CES is recorded on a numeric scale (from one to seven), it’s easy for you to track changes in your score, and come up with insights based on any fluctuations.
But with quantitative data, on the other hand, things aren’t as simple. Say you send out a survey, and within that survey, you have a free-text question asking your customers: What do you think CompanyName can improve upon? Obviously, the data that you collect can’t be textured translated into numeric results which are easier to analyze.
Now, if you intend to manually collate and read all the responses, then analyze the content to come up with insights, this will take a lot of time and effort. Here, a workaround is to use Natural Language Processing (NLP) and machine learning (ML) to do the heavy-lifting. These tools analyze qualitative data, and churn out insights that are derived from your customer feedback.
Take Wonderflow. Our tool utilizes NLP to mimic the human ability to comprehend texts. Once you feed your data into the tool, the tool will work to understand the data, and conduct sentiment analysis to gauge whether your customers are satisfied, neutral, or dissatisfied with your product and service.
At the same time, Wonderflow also generates automatic insights based on your customer feedback. You can receive the insights in your inbox in real-time, and these are also made available in Wonderflow’s reports, where the tool shares recommendations on how you can implement your learnings into your product life cycle.
Recently, Wonderflow was selected by independent research firm Aragon Research as one of the companies making an impact in document analytics. Check out the report here.Interested in more? Visit and subscribe to Riccardo Osti’s Youtube channel for many more videos.
Wonderflow empowers businesses with quick and impactful decision-making because it helps automate and deliver in-depth consumer and competitor insights. All within one place, results are simplified for professionals across any high-UGC organization, and department to access, understand, and share easily. Compared to hiring more analysts, Wonderflow’s AI eliminates the need for human-led setup and analysis, resulting in thousands of structured and unstructured reviews analyzed within a matter of weeks and with up to 50% or more accurate data. The system sources relevant private and public consumer feedback from over 200 channels, including emails, forums, call center logs, chat rooms, social media, and e-commerce. What’s most unique is that its AI is the first ever to help recommend personalized business actions and predict the impact of those actions on key outcomes. Wonderflow is leveraged by high-grade customers like Philips, DHL, Beko, Lavazza, Colgate-Palmolive, GSK, Delonghi, and more.
Other articles you might like:
Business · Dec 12, 2018
Review of the week: Polar watch Vantage V
You’ve probably heard the term sentiment analysis before but never really took much notice of how important it can be for your company. Wonderflow offers many tools that help brands discover the “why” behind customer feedback (ex. Why do customer dislike X feature?). This is because the language people are using can be mined to discover their true emotions and the intent in their sentences. With this information, you can gain a real understanding of…
Press · Apr 22, 2020
Wonderflow supports companies with free employee feedback analysis tool WonderWork
Wonderflow supports companies with free employee feedback analysis tool WonderWork WonderWork extracts actionable insights from employee feedback using artificial intelligence, aiming to help companies support new ways of working, as well as monitor and improve employee well-being. Amsterdam (NL) and Trento (IT), April 23, 2020 – Wonderflow, a leader in artificial…
Business · Mar 02, 2020
Video: What is the biggest limit of data science teams in an enterprise?
If we think about innovation today, the first thing that comes to our mind is probably related to information technology, complex software, and hardware. If we think about the word “innovation” inside a company, we are therefore pushed to think about the IT department, and we sometimes believe that all the new good…