Gather user feedback with surveys and live chat
A high
customer satisfaction score is the lifeblood of any successful business, serving as a powerful testament to the quality of products or services offered. Beyond being a mere metric, it is a direct reflection of customer loyalty and positive brand perception. A satisfied customer is not only likely to become a repeat customer but also becomes a brand advocate, spreading positive word-of-mouth and attracting new clientele. Moreover, a strong customer satisfaction score is an invaluable tool for businesses seeking sustained growth, as it fosters trust, enhances reputation, and ultimately leads to increased revenue. In an era where consumer choices are abundant, a stellar customer satisfaction score distinguishes a business as one that not only meets but exceeds customer expectations, solidifying its position in the competitive landscape.
From the half a dozen mechanisms available to gather user feedback, surveys remain the most simple and effective to use. With the help of a survey software tool such as SurveyMonkey, Typeform, and Frill, you can add surveys in a few clicks. Here are
things the best survey tools have in common.
Any of these tools offer pre-made survey formats, but they also let you create custom surveys that fit your exact needs. Two popular survey types you can use on your site are:
• The
Customer Satisfaction Survey (CSAT) helps you understand your
customers’ level of satisfaction regarding your products and services.
• The
Net Promoter Score (NPS) helps you measure the likelihood a customer will recommend your company to a friend.
Once you have created a survey, you can either add them to your website or through an email automation campaign. In both cases, you should pick your target audience carefully. For example, if you want to survey users with abandoned carts, you should show your survey only to these people, both on your web and email.
To get the best answers out of your visitors, use a feedback request template to help you understand and retain your customers.
Alternatively, you can gather user feedback
with the help of a live chat tool. While live chat tools serve a different purpose than surveys—that is, to provide a positive customer experience—you can find the most common problems your customers have by reading through the conversations they have with your customer support representatives.
In a way, live chat tools work as an indirect survey mechanism—you can’t ask them specific questions like you can with a survey, but you can see their level of satisfaction they have
with your brand. If all your live chat conversations are negative and end up with an unresolved problem, you can imagine your overall customer satisfaction score will be low.
You can implement both surveys and live chats simultaneously to start collecting user feedback data faster.
Analyze user feedback
After you have started using surveys and live chats on your site, grab all your data from every source and centralize it in a sheet. It’s critical to categorize your data according to the frequency and importance of the issues found and segment the answers around your different customer segments. Also for the calculations, take into account the
cost per resolution in this data.
For example, you may see that your customer satisfaction score is higher among your oldest customers—e.g., those that have made their first purchase over a year ago—and lowest among your newest ones.
If the latter group is more numerous than the former, you may conclude that your customer satisfaction is low, when that’s not entirely true. It may be that your customers take some time to extract all the value from your products. To avoid such issues, segment your data accordingly.
You can use a text analysis tool to improve your data analysis and get better insights from your user feedback tools, especially your live chat transcriptions. A text analysis tool will take all your data and carry out different levels of analysis such as:
•
Topic extraction, which tags text based on its subjects and themes.
•
Entity extraction, which identifies the important nouns (including addresses, phone numbers, and email addresses) in a piece of text.
•
Keyword extraction, which highlights words based on the number of times they are mentioned.
•
Sentiment analysis, which classifies text as positive, negative, or neutral.
•
Emotion analysis, which identifies emotions based on the words used.
•
Language detection, which deters the language type used in the text.
After you have gathered all your data, start looking for patterns. Pay special attention to those topics with high frequency, as they are most likely the most important. You also want to prioritize these topics that you consider more important for your business.
For example, you may see that only a few people complain about your payment processing options. Although seemingly small in size, this problem can lead to users leaving your tool due to lacking a payment option that best fits their needs. Therefore, the financial implications of this problem increase their importance, regardless of its volume.
Finally, define solutions based on the data analyzed previously. Talk to your team about the solutions you can implement to fix the problems found in your data.