Improving NPS with Text Analytics – Learn from the Pros

Net Promoter Score

Improving NPS with Text Analytics – Learn from the Pros

Nov 24, 2023

6 mins read

Manisha Khandelwal

Contents

When there is a big decision to be taken, for example, buying a new phone or looking for rentals, who do you ask first? 

– Your family and friends.

This is because I trust and value our friends and family above others. And believe it or not more than 70% of customers trust their friends and family when it comes to product recommendations. 

This is why businesses need to pay attention to their NPS score. This score tells you how likely your customers are to recommend you to their friends and acquaintances. 

Your NPS score helps you gauge your customer loyalty and satisfaction with your product, service, and overall business success. A higher NPS score is associated with increased customer retention and long-term profitability, whereas a low score requires immediate action.

But being aware of your NPS score is not enough to improve NPS performance, right? Along with launching NPS surveys and calculating your NPS scores, you also need to take action to improve it. And by improving your NPS score you ultimately boost your customer retention and drive positive business outcomes. 

But how to achieve this? Let’s find out.

Challenge with NPS 

The first step to improving the NPS score is to analyze the data the right way. 

But what I’ve noticed with many businesses is that they don’t know how to! 

The main stumbling block? They get overwhelmed by the number of responses because they do not have any efficient tool to process such a huge number of data.

The image shows a meme on crying.

So what to do?

The Fix -Text Analytics Software

This is a GIF that shows how using the text analytics software user is creating new tags to train the tool to automate feedback tagging. 

Here’s what I do – 

Let’s say I receive about 350 comments every week which equals about 1500-2000 comments in one month. That’s a lot, right? So, what I do is, use SurveySensum’s Text Analytics Software to efficiently manage and analyze the NPS program.

All I had to do was:

  • Train the system. Read a few comments, and figure out some categories. For example, for a SAAS company ‘Product Design’ can be one. 
  • Then add some keywords related to it.  
  • In tag analysis, you will see how the platform can tag every comment automatically.
  • And give you a detailed report of top trends and sentiments in just a few minutes

Piece of cake!

Launch Your First NPS Survey – Sign Up Here For Free!

 

But the challenge is how can you improve NPS with Text Analytics Software. 

Let’s talk about it with the help of a case study of a media giant that I recently helped in boosting the NPS score.

Case Study: Media Company’s NPS Journey

The Challenge

A prominent media company was on a mission to boost its NPS score and close the feedback loop in real-time. 

So, what did they do?

They collaborated with SurveySensum to enhance their website user experience and improve NPS on their website.

They had a million users which means they received about 10,000+ responses, per month, on their website. Now, the challenge for them was to prioritize this 10k+ feedback, analyze it, and take action based on its urgency. 

The Solution – Step-By-Step Process

They were sending an NPS survey to its users after they had spent an average article read time of 45 seconds. They also set up a survey repetition interval of 30 days. 

Here is a glimpse of the NPS survey:

The image shows an NPS survey sent by the client to their users asking them about their likelihood to recommend them to a friend.

Now, their issue here was, that they were not able to prioritize and analyze such a huge number of survey data. 

1. They Analyzed Thousands of Qualitative Feedback with Text Analytics

STEP 1: They trained the ‘SurveySensum’s Text Analytics’ machine on 100-200 comments creating 7-8 categories those comments might fall in.

STEP 2: Now, every time a keyword or similar words to that keyword appear they should fall into a particular category. This saved them around 40-50 hours of manual analysis which they were spending in a month to read these comments. 

Once the training was finished they ran a text analysis and the results came like below.

The image shows the categorization of feedback in the Text Analytics Software.

2. Identifying Drivers of Dissatisfaction

Now, that the tool was trained, it quickly identified the emerging trends and customer complaints which was – ‘Sign-in/Password’ category comprised 10% of comments, with a corresponding NPS score of -67.1.

People were frustrated about why they had to constantly log in. 

The image shows how with the help of automated tagging in the Text Analytics Software, a major issue with sign-in/password was identified.

Recognizing the frustration related to constant logins, they proactively implemented targeted interventions. This recognition prompted them to take focused actions aimed at alleviating the identified source of discontent among the readers and ultimately improving the NPS score.

The image shows negative feedback related to the sign-in/password issues.

3. Close the Feedback Loop With Text Analytics

With the identification of the prime complaint among customers, it was time to resolve these issues, hence closing the feedback loop. This was done in two steps:

1. Proactive Interventions and Targeted Actions

Once the signup issue was highlighted to the product and support team, They promptly set up email notifications for their support team. These notifications were triggered whenever a subscriber mentioned login problems. 

Here’s how it was planned;

  • STEP 1: The NPS survey was integrated with the client’s email address in the survey-builder.
  • STEP 2: Then the conditions for login issues and other similar keywords were set up. 

The image shows the email integration in SurveySensum’s survey-building platform.

The image shows the setting up of new alerts when a negative review is given by readers.

Close the Feedback Loop With Text Analytics – Request a Demo

 

2. Implementing Email Notifications

Email notifications were set up and forwarded to the Support team. This allowed them to respond to the readers in time, close the feedback loop in real-time, and identify all possible root causes for login issues. 

Here is an email notification when a reader leaves negative feedback. 

The image shows how an email notification was received by the client when a reader left negative feedback on the sign-in/password issue.

The image shows an email received by the client when a reader left a negative comment about their sign-in/password issue.

4. Results and NPS Score Improvement

After running this activity for a month, they figured out the client’s major concerns, fixed them in another month and 2 months later 90% of the issues were resolved. This resulted in an 11-point increase in NPS scores within 3 months. 

This case study exemplifies how leveraging technology and data-driven insights can transform user experience and drive positive business outcomes.

What’s Next?

In an ongoing commitment to enhance its user experience and address potential reader concerns, the media company has now set up new notifications. For example, now they send email alerts when readers leave negative reviews about subscription cancellations and other issues.

 

 

Manisha Khandelwal

Senior Content Marketer at SurveySensum

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