Customer experience managers are constantly striving to understand their customers better. What are their thoughts, desires, and pain points? Do they genuinely appreciate your products and services, or are they simply being courteous when completing your feedback forms?
These are the questions that drive continuous improvement.
Fortunately, technology provides avenues to gain clear answers to some of these questions! Instead of merely speculating about customer sentiment or relying on limited survey responses, you can now leverage powerful methods to measure customer sentiment data, offering tangible value to your business and enhancing your bottom line.
Today, we'll explore what customer sentiment is, why it's essential, and how to measure it effectively to maximize the utility of the data you gather using solutions such as betterfeedback.ai.
What is Customer Sentiment?
Customer sentiment is the metric organizations employ to gauge how their customers feel about their brand, products, and services. It represents a way to quantify somewhat intangible aspects, such as customer satisfaction, brand perception, and customer loyalty.
Analyzing customer sentiment is crucial for your brand's long-term success. If you aim to understand how your customers perceive your brand, the language they use to describe your product, and their willingness to recommend your brand, you need to measure and analyze customer sentiment.
The resulting data provides critical insights into product strengths and areas for improvement, current customer engagement and satisfaction levels, and even forecasts for future customer loyalty, particularly when coupled with the powerful analytics available from betterfeedback.ai.
How Can You Measure Customer Sentiment?
Customer sentiment analysis can be complex. You're attempting to assign numerical values to people's feelings, which can seem like an imperfect fit. However, understanding these sentiments is so vital for brand reputation and revenue that you must make the effort.
Some conventional scoring methods used to address this challenge include the Customer Satisfaction Score (CSAT) and Net Promoter Score (NPS). However, these are not the only means of gauging customer sentiment.
Here are some common methods that companies use to track customer sentiment, with the addition of how betterfeedback.ai can enhance these processes:
- Customer Sentiment Surveys: This classic approach involves directly asking customers about their experiences with your product or service. Surveys pose various types of questions to gather insights into their experiences. It's a straightforward method built on the idea that direct inquiry yields answers.
- Social Media Monitoring: By tracking how customers discuss your brand online, you can gain valuable insights. Utilizing social listening features available in most social media management tools, you can track mentions, hashtags, and overall sentiment across different social channels. Some tools even provide scores based on positive, negative, or neutral language used in mentions of your brand.
- Direct Feedback: Soliciting direct feedback can be invaluable. Open-ended customer feedback forms, comment sections, email feedback, and one-on-one interactions offer avenues for customers to share detailed thoughts in their own words. While analyzing this unstructured data requires more manual review, it can provide unique insights into the customer experience.
- Sentiment Analysis Software: For advanced analysis, sentiment analysis software harnesses artificial intelligence (AI) and machine learning to extract insights from various feedback sources. This software identifies trends across channels and platforms and offers actionable recommendations.
Understanding How to Analyze Customer Sentiment Scores
After measuring customer sentiment, what's next? Like all forms of data collection, you'll need to analyze the raw information for practical insights.
Here are some guidelines for analyzing customer sentiment scores or feedback:
Dos
- Segment data: Segment customer feedback by demographics or behavior to discover unique insights and tailor actions accordingly.
- Contextualize: Consider external factors that might influence data patterns, such as holidays or events.
- Look at the Big Picture: Combine quantitative and qualitative data to identify trends and gain a holistic view of customer sentiment.
- Take Action: Once you identify areas for improvement, take action to address them and demonstrate your commitment to customer satisfaction.
Don'ts
- Overgeneralize: Avoid making assumptions based on limited data without considering segmentation.
- Rely on Automation: Automated "how did we do?" surveys lack nuance and may not always yield the most accurate results.
- Act on Limited Data: Ensure that actions are based on a reasonable sample size to accurately reflect customer sentiment.
- Delay Responding: Respond promptly to feedback, especially negative feedback, to demonstrate your responsiveness and commitment to resolving issues.
Why does this matter? A positive CSAT, NPS, or CES score can indicate a customer's likelihood to return and make future purchases. In fact, increasing customer retention rates by just 5% can boost profits by 25% to 95%.
Mastering the measurement, scoring, and analysis of customer sentiment is key to enhancing customer loyalty and improving your long-term financial performance.
Examples
Let's examine some practical examples of measuring customer sentiment in different contexts.
Retail
A customer success team in a retail company may analyze customer sentiment scores to identify the most successful customer service areas within a specific store. They could use a custom survey to gather data on customer experiences.
The results from this survey are valuable for the retail location. If, for example, many respondents highlight "Friendly and helpful staff," the store manager might consider training staff from other locations in the chain using the successful team as a model.
Software as a Service (SaaS)
A SaaS company may survey customers to determine their preferred features on their platform. This type of feedback helps customer service and customer experience teams determine which features are most popular, especially after introducing a new capability.
The data can then help determine areas that require improvement, features that are underutilized, and potential opportunities to innovate, using betterfeedback.ai to identify the most impactful changes.
Personal Finance
Banks may survey their customers to gauge their satisfaction with updates to their mobile applications. These surveys might include questions about ease of use, practicality, and suggestions for future enhancements.
The answers to these questions help customer experience teams understand what their customers find valuable within the application. Identifying underused AI-driven features could lead to their sunset, thereby optimizing budget allocation and concentrating resources on areas that offer the greatest customer value.
Find Out How Your Customers Really Feel
Customer sentiment analysis is an essential part of your customer experience strategy. As automation creates more distance between us and end users, understanding customer needs becomes increasingly vital. Utilizing advanced tools and customer sentiment analysis, such as betterfeedback.ai, is the best way to do that.