Using AI For Verbatim Analysis


Using AI for verbatim analysis Using AI for verbatim
Table of Contents

Do you benefit from using AI for verbatim analysis?

Most of the valuable insights come from qualitative or textual data. The feedback customers share in their own words fuels the eureka-moment to innovate your business strategy. 

However, the challenge is that text feedback is difficult to analyze. Most data analysis software is engineered to analyze numeric or quantitative data. 

So, how can you make sense of verbatim responses?

Artificial Intelligence such as Sentiment Analytics can help you solve the problem. 

The feedback, reviews, or comments customers leave for your brand have some underlying emotions. Using AI for verbatim analysis, you can extract keywords that resonate with customer experience, identify emotions and cognitive responses across all touchpoints and thus create a Customer-Focused framework.  

  • After a positive experience, 85% of customers purchase more from a brand. 
  • A negative experience results in 70% of customers purchasing less. 
  • After a positive experience, shoppers are likely to spend 140% more with your brand. 

Having insight into customers’ emotions towards your brand can be a game-changer and help you make better CX decisions to boost loyalty and drive revenue.

Become an intelligent enterprise with AI.

How does Sentiment Analytics work?

Using AI for verbatim analysis Using AI for verbatim
  • Sentiment Analytics reads through customer feedback and detects emotions based on the language used. The AI uses NLP and machine learning algorithms to split customers’ emotions into positive, neutral, or negative. 
    • Combined with CSAT, NPS®, or CES surveys, AI can capture verbatims and emotions to obtain profound insights shaping your short-term and long-term strategies to retain customers. 
    • It can analyze a large volume of feedback in real-time to recognize which customer needs more attention and who is satisfied. 
    • You can utilize AI to predict whether customers are satisfied or have complaints. 

    Regardless of your target customers, you can win over your customers’ hearts using sentiment analytics.

    [Related: Read about How Sentiment Analytics can be conducted? in detail]

    Benefits of using AI for feedback analysis: 

    Customers remember how you make them feel: 

    To offer customers positive memories, you need to determine the root cause of their concerns. 

    Use AI to understand what is causing the issue. Sentiment Analytics can help you track recurring themes and keywords from customer feedback that can highlight what troubles your customers the most. 

    Segment these customers and follow up with them to further understand their concerns. Generate insights to take decisive actions, offer outstanding experiences, and mend your customer relationship. 

    Discover what’s missing:

    Customers can tell you themselves what they want and where you fail to deliver. Often, the touchpoints brands expect to impact CX are not the ones customers truly care about. 

    AI can show what customers want from your business, where they need help, and what you miss out on. Using sentiment analytics, you can detect the pain points and use them as an opportunity for improvement. 

    Be it an aspect of product or customer journey, uncover the urgent issues and factors critical to customers to prioritize them.

Using AI for verbatim analysis Using AI for verbatim

Happy! Sad! Annoyed! Content!

Discover customer emotions around your brand.

Capture customers’ perception of Brand: 

Brand reputation is critical in acquiring new customers – 95% of shoppers read customer reviews before buying. 

With sentiment analytics, you can capture how customers feel in real-time. Tracking positive and negative mentions of your brand, you can identify what is influencing their attitude towards your brand. 

Capturing customer sentiment in real-time is the key to improving brand reputation.
Customers’ emotions are likely to dissipate over time, and they may move to other brands. Capture customer reviews and direct them to the relevant team so they can proactively resolve the issue. 

Brands that reply at least 25% of the time to customer reviews are likely to earn 35% more revenue.

[Related read: Significance of sentiment analysis]

Increase ROI with innovative strategies: 

You can gather intelligent insights by analyzing customer feedback to innovate marketing strategies that appeal to your target audience. 

Brands can design personalized campaigns by segmenting their customer base using NPS® & qualitative feedback. It can help you recognize whether the “satisfied” customers are delighted. Often the customers who give high scores for satisfaction are at the risk of deflecting. The insights you gather by analyzing customer feedback can alert you to the risk of loss in such scenarios. 

You can design personalized campaigns and services that deliver better value to the customers. 

Escorts Group fuels digital transformation & drives lead conversion with Voxco Intelligence. 

Read the full story. 

Eliminate what harms CX: 

The ultimate benefit of using AI for verbatim analysis is to prevent a crisis by prioritizing actions that deliver exceptional customer experience. 

You can analyze customer emotions to discover the factors causing dissatisfaction among customers. Sentiment analysis of survey responses can help you understand what is frustrating the customers or what delights them. 

Be it a certain marketing campaign or payment process; you can take decisive action and intervene at the right time.

Wrapping Up; 

Every customer response or feedback is a goldmine to accelerate business growth. Brands can now leverage AI to monitor every aspect of customer experience in real-time and provide effective resolution promptly. 

Happy – Neutral – Sad, always stay in tune with your customers’ feelings about your brand.

Ready to try AI?

How about you connect with our team for a free consultation.

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The Likert scale is a 5- or 7-point scale used to assess a respondent’s level of agreement with a statement or the intensity of their reaction to something.

The scale grows symmetrically, with the median number (e.g., a ‘3’ on a 5-point scale) representing a point of neutrality, the lowest number (always a ‘1’) representing an extreme opinion, and the highest number (e.g., a ‘5’ on a 5-point scale) representing the opposing extreme position.

Likert-type question examples:

  • How strongly do you agree with the following statement: [company’s] payment method is easy and straightforward?

1 – Strongly disagree

2 – Somewhat disagree

3 – Neither agree nor disagree

4 – Somewhat agree

5 – Strongly agree

  • How satisfied were you with your customer service experience?

1 – Very dissatisfied

2 – Somewhat dissatisfied

3 – Slightly dissatisfied

4 – Neither satisfied nor dissatisfied

5 – Slightly satisfied

6 – Somewhat satisfied

7 – Very satisfied

When should we utilize Likert scale questions?

Because the responses are provided in a set sequence, Likert-type questions are also known as ordinal questions. Likert scale questions, like other multiple-choice questions, are useful when we already know what our clients are thinking. For example, if our open-ended questions reveal a complaint about a recent modification to your ordering procedure, we may utilize a Likert scale question to evaluate how the average user felt about the change.


Rating scale questions have responses that correspond to a number scale (such as rating customer support on a scale of 1-5, or likelihood to recommend a product from 0 to 10).

Rating questions include the following:

  • On a scale of 0 to 10, how likely are you to suggest us to a friend or colleague?
  • On a scale of 1 to 5, how would you rank our customer service?

When should we utilize rating questions?

A rating question is the way to go whenever we want to offer a numerical value to our survey and/or examine and compare patterns.

A common rating question is used to calculate Net Promoter Score® (NPS®): the question asks consumers to assess their probability of suggesting items or services to their friends or colleagues, and the findings allow us to look at the results historically to see if we’re improving or worsening. Customer satisfaction surveys and product reviews (such as Amazon’s five-star product ratings) also employ rating questions.


These are easy questions that demand a simple ‘yes’ or ‘no’ response.

Yes/No questions include the following:

  • Was this article beneficial? (Yes/No)
  • Were you able to locate what you were searching for today? (Yes/No)

When should we use ‘yes’ or ‘no’ questions?

  • Using ‘yes’ and ‘no’ questions, we can easily categorize our replies. Assume we’re seeking to figure out what hurdles or objections are preventing individuals from trying our product. We may put a poll on our price page, ask folks if anything is holding them back, and then follow up with the part that said ‘NO’ by asking them to clarify.
  • These inquiries are also excellent for getting our foot in the door. When we ask a ‘yes’ or ‘no’ question, the response takes relatively little effort. When a person commits to answering the first question, they are more likely to answer the subsequent ones.


The words and phrases used in a question are crucial in conveying the meaning and aim of the question to the respondent and ensuring that all respondents read the question in the same manner. Even little language adjustments can have a significant impact on the responses individuals offer.

A large amount of study has been conducted to assess the impact of different ways of asking questions and how to minimize disparities in how respondents understand what is being asked. The challenges surrounding question phrasing are extensive and cannot be completely addressed in this small space, but here are a few key points to consider:

To begin, it is critical to ask clear and detailed questions that each respondent will be able to answer. If a question is open-ended, responders should be aware that they can react on their own terms and what sort of response they should offer (an issue or problem, a month, number of days, etc.). Closed-ended questions should allow for all acceptable replies (i.e., the list of alternatives should be exhaustive), and the response categories should not overlap (i.e., response options should be mutually exclusive).

It’s also a good idea to limit yourself to one question at a time. Questions that ask respondents to evaluate more than one concept (known as double-barreled questions) – such as “How much confidence do you have in President Obama to handle domestic and foreign policy?” – are difficult for respondents to answer and frequently result in difficult-to-interpret responses. It would be more effective in this case to ask two separate questions, one about domestic policy and one about foreign policy.

Net Promoter®, NPS®, NPS Prism®, and the NPS-related emoticons are registered trademarks of Bain & Company, Inc., Satmetrix Systems, Inc., and Fred Reichheld. Net Promoter Score℠ and Net Promoter System℠ are service marks of Bain & Company, Inc., Satmetrix Systems, Inc., and Fred Reichheld.

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