Boost Your CSAT with Nocodo AI

Ready to supercharge your customer feedback process? With Nocodo AI, you can seamlessly collect user sentiments, translate them into actionable insights, and watch your CSAT soar. Dive into this use-case to discover how Nocodo’s streamlined approach makes it easier than ever to measure, interpret, and elevate your customer experience.

Sebastian WahnFunko Pop! figure of sebastian with glasses, beard, and brown hair, holding a mug and laptop. Wearing a Hard Rock Cafe shirt and a lanyard.

Sebastian Wahn

10 min read
Understanding your customers' satisfaction is key to business growth. In this post, we’ll show you how to easily measure Customer Satisfaction Scores (CSAT) and how Nocodo AI can automate the process, giving you real-time, actionable insights.
You’ll learn how to:
  • Quickly gather customer feedback.
  • Use Nocodo AI to evaluate and score it.
  • Gain deeper insights to improve your customer experience.
Let’s get started on enhancing your customer satisfaction today!

What Is CSAT?

Customer Satisfaction Score (CSAT) is a powerful metric used to assess how satisfied customers are with specific experiences—be it a product purchase, customer support interaction, or even a visit to your website. Typically, a CSAT survey asks customers, "How satisfied were you with your experience?" on a scale (e.g., 1-5, where 5 indicates "very satisfied"). The higher the score, the more positive feedback you’re receiving.

Why Should You Care About CSAT?

  • Indicator of Success: A high CSAT score signals that you’re meeting or exceeding customer expectations. A low score? Time to dig deeper and solve potential issues.
  • Customer-Centric Insights: CSAT surveys offer a simple, quick snapshot of your customers' experiences, ensuring teams (from product development to customer support) stay focused on the experience they deliver.
  • Customer Loyalty: A satisfying experience increases the likelihood of repeat customers and organic recommendations. CSAT helps identify key areas where customers feel delighted, leading to better retention.
  • Quick Feedback Loop: CSAT surveys are concise, making them easy for customers to complete. You can act on this immediate feedback to continuously improve.
  • Supports Growth: Improving customer satisfaction can directly boost referrals and, ultimately, revenue. CSAT is a measurable, actionable metric that ties back to your business's bottom line.

How to Measure CSAT

Measuring CSAT is easy:
  1. Ask the Right Question: Keep it simple—"How satisfied were you with [service/experience]?"
  2. Use a Rating Scale: It could be 1-3, 1-5, or 1-10.
  3. Calculate Your Score: On a 1-5 scale, your CSAT score is typically the percentage of respondents who select a 4 or 5. For example, if 75 out of 100 users rate 4 or 5, your CSAT score is 75%.

Maximizing CSAT Impact

  • Ask Clear, Concise Questions: Your customers' time is valuable. Keep your questions simple.
  • Short Surveys: Don’t overwhelm customers. Stick to what’s essential.
  • Follow Up: Use low scores as an opportunity to reach out, understand, and improve.
  • Track Trends: Monitor CSAT scores over time to see if your changes positively affect satisfaction levels.

Common Misconceptions

  • CSAT Isn’t Just Extra Overhead: It’s often the first sign of a hidden issue that could escalate if left unaddressed.
  • One Survey Won’t Tell You Everything: CSAT is just a snapshot. Combine it with other metrics (like NPS) for a fuller picture.

How Nocodo AI Elevates CSAT Evaluation

Nocodo AI offers a seamless, automated solution for gathering, analyzing, and scoring CSAT feedback. Rather than manually assessing each response, Nocodo AI leverages powerful AI tools to provide a quick, consistent, and scalable solution to evaluate customer feedback.

Setting Up CSAT Evaluation with Nocodo AI

Here’s a simple example of how Nocodo AI can automate your CSAT evaluation process:
  1. API Input Node: Receive customer feedback via an API call.
Text Input Node: Set up clear instructions for the AI to evaluate the customer feedback. Example instruction: 
    
Drop the placeholder {input-0} where the customer's feedback is inserted.
  1. Large Language Model (LLM) Node: The AI evaluates the sentiment and assigns a CSAT score based on the feedback.
  2. Output Node: Display the CSAT score along with any relevant department assignment.
Screenshot of a workflow interface showing nodes labeled "Input," "Test," "Large Language," and "Output" connected by lines.
Example project setup to evaluate a CSAT score
Once you’ve set up the project, the feedback system will be accessible via a URL. Here’s how it works:
POST Request Example: 
    
{ "input-0": "The product is very good." }
Response: 
    
{ "data": "Score: 5" }

Example Feedback & Results

  • Positive Feedback: Input: "I was really impressed by how quick and straightforward the checkout process was." Output:
  • Negative Feedback: Input: "The delivery was delayed, and I couldn’t track my package. Disappointing experience." Output:
  • Mixed Feedback: Input: "Customer service was polite, but I didn’t get a clear solution to my question." Output:

Taking CSAT to the Next Level

To enhance your CSAT system, you can modify the AI's evaluation to provide more actionable insights. Instead of just a score, you can identify which department (e.g., Product Development, Billing, Customer Support, or Shipping) is associated with the feedback.

Updated Instructions for AI Evaluation: 

    
You help evaluate customer feedback and provide a score based on the customer's 
sentiment of the product. 

Please base your evaluation on the CSAT method (1 to 5 points).

If possible, assign the feedback to the relevant department 
(Product Development, Billing, Customer Support, Shipping).

If no department is clear, use "UNSPECIFIED."

Example Output:

  • Customer Support Feedback: Input: "Customer service was polite, but I didn’t get a clear solution to my question." Output:
  • Unspecified Feedback: Input: "The product is decent." Output:

Why Use Nocodo AI for CSAT?

Nocodo AI makes gathering and analyzing CSAT feedback more efficient, reliable, and actionable. With our customizable nodes, you can scale the process, enhance the feedback collection, and directly link it to relevant business areas. The flexibility to adjust the project based on your unique needs means you’re always equipped to improve the customer experience and refine your processes.

How Can Nocodo AI Help You Gather a CSAT Score From Your Users?

By now, you’ve seen how measuring your Customer Satisfaction Score (CSAT) can give you valuable insights into how customers feel about your business. But what’s the easiest way to start collecting this feedback and transforming it into a clear score?
Let’s say you’d like to gather user comments through a simple text form and then translate that feedback into a satisfaction rating on a scale of 1 to 5. From there, you can quickly gauge how effectively your business is meeting customer needs.
This is where Nocodo AI comes in. With Nocodo AI, you can set up a new project that includes an input form for collecting user feedback plus an AI component to evaluate and score each submission. Here’s a step-by-step guide on getting started:
  1. Add an API Input node to your project. This node will receive the user feedback.
  2. Add a Text Input node to your project. In this node, you instruct the AI on what to do with the input, including the user's feedback.
    The LLM instruction can look like the following: 
        
    You help evaluate customer feedback and provide a score based on the customer's sentiment of the product.

Please base your evaluation on the CSAT method on a scale from 1 to 5 points.

Please reduce your generated output to the form of:
Score: [CSAT_SCORE]

where [CSAT_SCORE] is your evaluation.

Please only fill out the CSAT number and do not add any context to the response.

Following is the customer's feedback:
```
{input-0}
```
    Drop the placeholder {input-0} at the correct spot so the customer's feedback is embedded in the LLM's instructions.
  3. Add a Large Language Model (LLM) node to your project. This node will evaluate the instructions and respond. The LLM will do the heavy lifting by evaluating the user input and assigning it a CSAT score.
  4. Add an output node to your project. This node will provide you with the LLMs output.
  5. Connect nodes of steps 1 to 4 in a sequence beginning with the API Input node's output connected to the Text Input, the Text Input’s output connected to the LLM, and the LLM's output connected to the Output Node.
After saving the project, it is accessible under the API Input nodes URL.
Requesting the URL via POST and the body: 
    
{
    "input-0": "The product is very good."
}
It will yield the following result: 
    
{
    "data": "Score: 5"
}
More examples
Positive feedback 
    
{
    "input-0": "I was really impressed by how quick and straightforward the checkout process was."
}

  
    
{
    "data": "Score: 5"
}
Negative feedback 
    
{
    "input-0": "The delivery was delayed, and I couldn’t track my package. Disappointing experience."
}

  
    
{
    "data": "Score: 1"
}
Mixed feedback 
    
{
    "input-0": "Customer service was polite, but I didn’t get a clear solution to my question."
}

  
    
{
    "data": "Score: 3"
}

Further Improvements

While a simple score is a good starting point, there are times when you need more context to truly understand what’s driving your results. Instead of just knowing that customers are satisfied or dissatisfied, it can be helpful to pinpoint which parts of your business are excelling and which ones might need extra attention. This deeper insight allows you to make more informed, targeted improvements.
The project can be adjusted so that the LLM will also provide further information.
Update the Text Input instructions to be: 
    
You help evaluate customer feedback and provide a score based on the customer's sentiment of the product. 

Please base your evaluation on the CSAT method on a scale from 1 to 5 points. 

The business providing the product has the following departments: Product Development, Billing, Customer Support, Shipping. 
If possible, add a corresponding department to the response when the customer's feedback can be mapped to the abovementioned ones.

Please reduce your generated output to the form of:
Score: [CSAT_SCORE], Department: [DEPARTMENT]

Where [CSAT_SCORE] is your evaluation and [DEPARTMENT] is the department if applicable, please use "UNSPECIFIED" as the default.

Please only fill out the CSAT number, and do not add any context to the response.

Following is the customer's feedback:
```
{input-0}
```
Following user feedback: 
    
{
    "input-0": "Customer service was polite, but I didn’t get a clear solution to my question."
}
will generate 
    
{
    "data": "Score: 3, Department: Customer Support"
}
We see that the LLM detected the department based on our updated instructions.
When no department was detected, the fallback “UNSPECIFIED” is picked up: 
    
{
    "input-0": "The product is decent."
}

  
    
{
    "data": "Score: 3, Department: UNSPECIFIED"
}

Why Choose Nocodo AI for Your CSAT Evaluation?

Nocodo AI’s flexible, node-based approach streamlines the process of collecting feedback and translating it into meaningful scores. With its powerful nodes, you can easily enhance your project to drive even better results—whether by adding more detailed feedback options or integrating additional data sources. Feel free to tinker with the outlined example project and tailor it to your specific needs, ensuring your CSAT evaluation is perfectly aligned with your business goals.

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