I think it's very important to have a feedback loop, where you're constantly thinking about what you've done and how you could be doing it better
Elon Musk

What is Customer Survey Software?

Definition: Customer survey software enables organizations to measure customer satisfaction, track brand loyalty, and conduct customer research. The data collected from a customer survey can be turned into actionable insights, helping to improve the customer experience.

Types of Customer Surveys

Many customer survey tools overcomplicate customer surveys by using inconsistent terminology. Some software will call their features "customer experience", while others will it "customer success". Regardless of the terminology there are two main types of customer surveys: customer satisfaction and customer effort. Both of these surveys will help you metrics on brand loyalty- higher score means happier customers and increased interactions.

1) Customer Satisfaction

This is the most common type of customer survey. The format can customer surveys can vary, but using a Net Promoter Score question as the basis for customer satisfaction is the industry standards. A Net Promoter Score question asks:

How likely is it that you would recommend this company to a friend or colleague?

When the results are tallied, one number ranging from -100 to 100 is displayed. This number is easy to track and benchmark over time

2) Customer Effort Score

A customer effort score questions asks respondents one simple question:

Did [Company Name] make it easy for you to __________?

This question uses 7-point rating scale from disagree to agree. This results from this question are averaged to give you a score from 1 to 7. The higher the score, the easier it is for customers to stake a certain action. This type of survey is often used after a purchase is made, after a support ticket is closed, or when an action is taken on a website.

How to Design Customer Surveys

Whether its a customer satisfaction survey or a customer effort survey, the form used to collect feedback should be short and to the point. For customer satisfaction, your survey should start with a Net Promoter Score question, followed by an input box question asking the reason for the score. A similar logic would be used for customer effort score surveys; use a customer effort score rating question, followed by a text input.

After your text input questions, you can add a few questions to collect more granular feedback. Demographic information like household income or gender are common questions and can be used to segment your results. You could also use an opinion scale to quickly get ratings for related items; such as website design and product offerings.

Avoid asking unnecessary questions like "When was your purchase?" or "What was the date of your support request?" This information should be included automatically using a query string. This information is referred to as custom data. This data reduces survey length and can be used to segment the results.

How to Collect Customer Survey Responses

There are a few different ways to collect customer feedback and each one would target different goals. A good customer survey program should be as automated as possible to ensure your organization is not missing data points.

Automated Emails

The most popular type of distribution method. When an action is taken on your website, you can send an email asking for a rating.

Embedded Surveys

Banners at the bottom of a page with a Net Promoter Score or Customer Effort Score. These are simple for customers to fill out are not intrusive.

Web Links

Simple survey links are the easiest way to collect customer feedback. The link can be placed in email receipts, on checkout pages, or even in the footer of the company website.

Best Practices

It's important to not bombard your customers with constant survey requests. If you send a survey to a customer the first time they make a purchase, don't send another one for six months to a year. If using an embedded survey, only ask a user one time for a score or rating.

Analyzing Customer Survey Results

There are three important points when analyzing customer survey data. Keeping this points in mind is crucial to developing a great feedback system.

1) Text Analysis

This is the most powerful feature of a customer survey program. The folleo-up questions for Net Promoter Score or Customer Effort Score can be categorized using text analysis and machine learning. Suppose a bunch of low ratings were due to comments related "price". A good text analysis tool will automatically tag answers that talk about price.

Not only is this useful from a statistics standpoint, but it eliminates the need to ask multiple questions inside of a customer effort survey. A lot of the times you'll see inefficient surveys ask about things like price, support knowledge, website layout, etc. Text analysis eliminated the need those questions. If a customer has an issue with a certain part of your business, or thinks poorly about a certain aspect of the business, text analysis will quantify that automatically for you.

2) Benchmarks

When you run your first customer survey use the Net Promoter Score or Customer Effort Score as the initial benchmark. Share this number with teams and management and have a goal to increase the numbers over time. Once you get your surveys up and running, analyzing monthly trends and 30 day scores will help guide decision making.

3) Segments

Customer survey scores can vary by department, geographical location, or even the service offered. Adding custom data to your data links can help you segment your results to make comparisons. For example, your Net Promoter Score might be 30 overall, but what if one store is -40 and one store is 60? Without segmenting your data, a poor performing store may never be uncovered.

Product Research

Customer survey software can also help you research products and business practices. Building products with the needed features at the right price can boost your company customer base and bottom line. A great website can boost traffic, increased conversions, and in turn more sales. To build optimal products and improve your website here are some common research tools:

  • MaxDiff - perfect to identify the most important features of a product or app.
  • Conjoint - used to find the optimal price and feature set of a new product.
  • Van Westendorp - will give you a range of acceptable prices the market will accept for a new item.

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