Optimise your customer satisfaction surveys with emotional analysis: AI methods and tools

Published on October 16, 2024  - Updated on October 16, 2024

Optimise your customer satisfaction surveys with emotional analysis: AI methods and tools

Customer satisfaction: a strategic lever with emotional analysis

Customer satisfaction is now a key indicator of business performance. Customer satisfaction surveys play a fundamental role not only in assessing customer experience, but also in guiding companies in improving their products and services. However, the quality of the information gathered depends directly on the structure of the surveys and the relevance of the questions asked. Optimising these categories is therefore essential if we are to obtain usable and accurate data.

Another aspect that is often overlooked is emotional analysis. In addition to traditional indicators such as the Net Promoter Score ( NPS), companies can now understand not only what their customers think, but also what they feel, thanks to innovative tools such as Q°emotion. This platform uses semantic artificial intelligence to analyse the primary emotions expressed in customer feedback, providing additional depth to data interpretation. In this article, find out how to structure your satisfaction surveys effectively to maximise their impact.

I. The importance of categories in satisfaction surveys

Categories structure responses, making the results easier to use. Research by McKinsey shows that 70% of companies that focus on customer satisfaction indicators achieve better financial performance than their competitors (Survicate: Effortless Survey Software). By effectively structuring categories, companies can :

• Segment returns to better analyse responses.
  
• Focus respondents' attention on specific aspects of the experience.
  
• Identify actionable insights for each dimension of the service or product.
  

Poorly defined categories can lead to a scattering of responses and prevent problems or strengths from being clearly identified. Optimising your categories therefore means improving the relevance of responses and encouraging informed decision-making. What's more, Q°emotion offers a solution that allows you to go one step further by analysing the emotional dimension of verbal responses left by customers.

II. Identify the survey objectives to structure the categories

Defining the objectives of your survey is essential to guarantee actionable results. A Harvard Business Review study revealed that companies that align their surveys with strategic objectives are 30% more likely to improve customer satisfaction (XM Institute). Here are a few best practices:

• Clarify the KPIs you want to measure (e.g. NPS, CSAT).
  
• Define priorities: do you want to evaluate a specific product, the quality of customer service, or the overall perception of the brand?
  

These elements will enable you to structure categories tailored to your objectives, thereby increasing the relevance of the information gathered.

III. Create exhaustive but precise categories

It's crucial to strike a balance between comprehensiveness and simplicity. Categories that are too broad run the risk of lacking precision, while categories that are too specific can overload the survey and tire respondents. To structure your categories properly :

• If a category such as ‘service satisfaction’ is too vague, divide it into more detailed sub-categories such as ‘responsiveness’, ‘agent competence’ or ‘ease of contact’.
  
• Keep the categories actionable: Each category should lead to concrete decisions.
  

The idea is to enable each response to provide clear, actionable information. Incorporating an emotional component via tools such as Q°emotion can go even further, by identifying which categories arouse positive or negative emotions.

IV. Combine qualitative and quantitative approaches

A good satisfaction survey is not just about numbers. While quantitative data is essential to get an overall picture, qualitative data is essential to understand the ‘why’ behind the figures.

• Quantitative: Evaluation scores such as the Net Promoter Score (NPS), the Customer Satisfaction Score (CSAT ) or the Customer Effort Score (CES) can be used to measure performance on specific criteria.
  
• Qualitative: Open-ended questions can be used to explore in more detail the reasons behind the ratings given.
  

Example: If a category dedicated to customer service satisfaction shows a low score, a complementary open-ended question such as ‘What frustrated you the most during your last interaction with our customer service department? will provide precise indications of what's going wrong.

To find out more about the difference and complementarities between qualitative and quantitative approaches to satisfaction surveys, read this dedicated article on the subject on Q°emotion.

V. Adapting categories to different customer segments

Not all customers have the same experience, which is why it is so important to tailor surveys to customer segments. Segmenting your customers allows you to ask more relevant questions.

• New customers: Questions will focus more on onboarding, ease of use and clarity of information.
  
• Regular customers: They will be more likely to evaluate aspects such as the quality of customer service or brand loyalty.
  

By adapting the categories according to customer segments, we can better understand the specific expectations of each group.

VI. Regularly analyse and adjust your categories

Finally, it is crucial to re-evaluate your survey categories on a regular basis. What is relevant today will not necessarily be so tomorrow. Customer expectations change, as do offers and markets.

• Analyse the results: Observe which categories generate constructive feedback and which do not. If a category remains unchanged over several surveys, it may be time to reformulate or replace it.
  
• Listen to customers: Adding categories based on direct customer feedback is an excellent way of improving the relevance of surveys. Suggestions made by customers themselves can reveal needs or concerns that you hadn't anticipated.
  

FAQ : Satisfaction surveys and Emotional Analysis

How can we optimise customer satisfaction surveys? Optimisation involves structuring the categories properly, defining clear objectives and adding an emotional dimension to better understand how customers feel.

What is emotional analysis in satisfaction surveys? Emotional analysis involves using artificial intelligence tools, such as Q°emotion, to interpret the emotions expressed by customers in their open-ended responses.

How can surveys be adapted to different customer segments? Customer segmentation allows us to ask more relevant questions that are adapted to each type of customer, such as new customers or regular customers.

Conclusion

Optimising the categories of your satisfaction surveys is crucial to obtaining accurate, actionable information. By aligning categories with your objectives, adopting a mixed quantitative and qualitative approach, and adapting questions to different customer segments, you can maximise the effectiveness of your surveys. Companies that adopt these practices generally see an increase in loyalty and financial performance, reinforcing the importance of customer experience as a strategic lever.

If you'd like to see some real-life examples of how we've worked, take a look at our Floa Bank case study to find out how our solutions have improved customer satisfaction and engagement through emotional analysis and optimised surveys.