Keeping customers happy is even more critical during bear markets. 

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99% of the time, it's cheaper to keep an existing customer than to attract a new one. Moreover, satisfied customers spend more, are more loyal, and are more likely to promote your brand. Who wouldn't want that?

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Customer service is a crucial touch point with your community. Getting it right can make the difference between losing a customer to a competitor or keeping them and growing their brand loyalty to your organization.

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Customer Satisfaction Scoring, often shortened to CSAT, is one of the key metrics web3 organizations can use to understand how satisfied their customers are after interacting with customer support moderators/agents. 

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This article will provide a brief overview of CSAT, why it's important, how to interpret it, how it's calculated, and how to improve it. 

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LFG. 

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Why is Customer Satisfaction Scoring (CSAT) important?

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It may seem obvious but keeping your community happy is critical to help your community grow organically over the long run. Despite this, we have seen countless examples of web3 communities where customer service is fragmented and disorganized. It results in a poor customer experience, and the damage done is often impossible to quantify  due to a lack of data. 

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Customer support is one of the most important and frequent 'touch points' your organization will have with the community. Asking your customers to rate how happy they are with the experience they received is a crucial first step in understanding how and where you can improve. 

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How do you calculate a Customer Satisfaction Score (CSAT)?

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Using Mava, you can automatically ask your community for feedback at the end of a conversation, whether they are talking to your team via Discord, Telegram, or our web chat widget. Using emojis, the user will simply need to rate the conversation on a scale of 1 - 5. 

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To calculate the CSAT we then take the number of positive feedback responses (5⭐ Extremely + 4⭐ Somewhat Satisfied) and divide it by the total number of feedback responses. To get a percentage score, this number is then multiplied by 100.

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CSAT = Positive Responses / Total Responses

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For example, say you gather data from 100 customers. If 80 customers rated  you 4 or 5 on the 1-5 scale, you would divide 80/100 = 0.8. You then multiply 0.8 by 100 to get a percentage score. So in this example, the company's CSAT score is 80%. Keep in mind the CSAT is not an average of all ratings. 

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How to interpret a Customer Satisfaction Score (CSAT)?

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You should measure and track CSAT scores at an individual agent level and an overall organization level.

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So what is considered a good benchmark CSAT score to aim for? A CSAT of 80% or higher is excellent. Below this, you should try to improve. Likewise, it's worth comparing agent scores vs. the overall organization score to identify moderators who might need extra training or support. 

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We all know it's hard to get customers to leave feedback. As a benchmark, it's considered good if 25% or more of your customers leave feedback at the end of a customer support conversation. 

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Mava can help increase the number of customers leaving feedback by making it quick and straightforward for your community. If you have CSAT scoring turned on, within your Mava dashboard, your users will be asked to select one of 5 emojis after their ticket has been marked as resolved, simple as that. 

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How to improve a Customer Satisfaction Score (CSAT) within your web3 community?

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If you are not consistently getting 80% or higher CSAT scores, your team probably has some room for improvement. 

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The best place to start is by looking through previous support tickets where customers have provided negative feedback. Carefully review the entire interaction and identify what happened. Was there an opportunity to improve the experience for the customer? Did they need to speak with a support agent in the first place or would a different, self-service mechanism have been better? Is this the customer's first time trying to solve this issue or have they already tried to resolve it? If a support agent has followed all the correct procedures, but the customer left a bad rating because of a frustration with the product, 

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Sample tickets each month and try to identify areas for improvement as a team.

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Reviewing CSAT scores at a company and agent level frequently is essential. It should form a key part of a monthly review process where the team sits down and identifies weaknesses and celebrates excellent customer success stories. Your aim should be to keep improving CSAT scores over time. 

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Conclusion

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There's no denying the importance of good customer service. Happy customers are more likely to become brand advocates, be loyal, and will often spend more. Good customer support is a crucial decision-making factor for new and existing customers when deciding whether to interact with your organization or a competitor. 

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Using Mava, you can quickly gather customer feedback across multiple platforms, including Discord, Telegram and our Web Chat widget. You can then view your CSAT scores at an overall organization level and an individual support agent level. 

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A CSAT score of 80% or higher is considered great, and you should aim to have at least 25% of your customers providing feedback.

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The best way to improve your community experience is to start gathering data and getting a current benchmark CSAT score. From there, you can look to improve your customer interactions by reviewing support tickets where users left very positive and very negative feedback. Identify patterns and lessons that you can share with your team. 

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In future articles, we will look at other customer success metrics, such as net promoter score (NPS) and customer effort score (CES).

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If you have questions about CSAT scores or other customer support metrics, then feel free to reach out to the Mava team and book a demo.

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