Main illustration: Leonardo Santamaria
There are many reasons an organization seeks out customer feedback. A support team will want to know if their service experience was helpful, while a product team might need help prioritizing what to build next.
Customer feedback is of obvious benefit to product managers, customer service teams, analysts, marketers, and pretty much anybody in your organization. Despite this, a recent study found a full 42% of companies don’t survey their customers or collect feedback.
What is customer feedback?
Customer feedback is input relayed from your customers about their experience and satisfaction levels regarding your product or service. Customer feedback can come in from a variety of channels (email, social media) or messenger tools such as Intercom.
Why is customer feedback so important?
Customer feedback is important for future product development, improving the customer experience and overall customer satisfaction levels. Proper analysis provides a company with a better view of what it has to change and improve on to help increase customer loyalty and reduce customer support cases.
6 rules for collecting better customer feedback
1. The type of customer giving the feedback matters
Do you pay equal attention to all the nuggets of wisdom people give you? Unlikely. Chances are the friends you’ve known the longest are the people whose opinions you’ll trust most. The stranger you just met on a bus who told you emphatically what you should do with your life? You’re probably not going to put as much weight on their views.
In a business situation, the customer’s relationship with your business influences how much weight you give their feedback. Customers who have been loyal the longest have a wealth of experience with your product that makes their opinions particularly valuable. Do you have some new customers who only started using your product six months ago but use it heavily? They’re likely to have a lot of insightful feedback. Do you have some customers who pay significantly more than others? You may want to factor that in too.
2. Whether it’s prompted or unprompted, customer feedback matters
Unprompted feedback deserves special attention. Here’s one key reason why. The customer issues that aren’t on your radar, that you’re completely unaware of, can be the most important things you need to hear. You’re more likely to hear those left-field issues via unsolicited feedback or from open-ended questions rather than, say, a short survey with multiple choice answers. There’s a reason doctors ask if there’s “anything else you want to talk about?” at the end of your appointment. It often triggers the patient to talk about their most important issue.
3. The customer’s motivations matter
Remember, people are generally motivated to provide unsolicited feedback if they have extreme experience. That’s why you see Yelp restaurant reviews clustered around the “amazing” and “appalling” end of the spectrum. People perceive they’ll gain social capital from telling others about the great restaurant they just went to or by warning others against a terrible restaurant.
But the night your dinner was really average? You’re probably not going to bother writing a review because, well, what’s the point? It’s not a very interesting story, is it? The restaurant example of customer feedback illustrates an important principle about motivations.
“Your customers are more motivated to tell you when they are very happy or unhappy about your product”
The type of distribution that results in this kind of restaurant review data is often a J curve. The “J” shape refers to data where the curve initially falls but then rises to a higher point than the start.
When it comes to customer feedback you receive about your business, you can expect there to be a similar pattern. Your customers are more motivated to tell you when they are very happy or unhappy about your product. However, this doesn’t mean that your customers only love/hate your product. You’ve probably got a large group in the middle who think your product is “fine.” These customers typically stay silent. Remember, they could also have useful feedback for you. If you’re smart, you’ll find ways to tease out their feedback.
4. Volume matters
If 80% of your customer feedback in the last month is telling you that the “improvement” you made recently to your core product has broken people’s workflow, you should listen up. The overall volume of feedback about a single issue relative to other issues matters. It will also protect you from “fre-cently” bias, where people assume things they hear frequently or recently have the greatest importance.
5. Repetition matters
User issues are often dismissed on the grounds that “Oh we’ve heard that for years.” Maybe you’re planning to finally address that issue in a big redesign next year. Or more likely this request has become so repetitive that it’s become trite, a sort of dull whine that nobody listens to anymore.
Either way, this kind of feedback is really worth listening to, especially when it relates to product quality, bugs, or difficulty achieving a core task in the product. It’s an indicator you haven’t got the basics right, and that’s something you have to address as a priority rather than ignore.
6. The stakes matter
Some feedback is worth listening to purely because of the severity of the problem the customer is experiencing. This is high stakes feedback. Perhaps you pushed a release that had a security loophole, or your product has accidentally put consumer’s privacy at risk. When reviewing customer feedback, try to build a mechanism that alerts you to this kind of very occasional but high stakes feedback so you can take action straight away.
How to collect customer feedback
There are a number of feedback tools, methods, and systems you can use to gather customer feedback and learn about their pain points. Here are three places where you can proactively (or reactively) hear what your customers are saying.
Live chat is a frictionless way for customers to communicate with you directly. You can ask specific real-time questions (prompted) or passively categorize the inbound feedback (unprompted).
Asking your customers questions regarding specific features, aspects of your platform or parts of their experience is an easy and direct way. Measure customer satisfaction with customer feedback surveys. Here’s how to do it with Intercom.
As you’ve probably noticed, people like to express their feelings on social media. While it is oftentimes not constructive, you can actually find extremely valuable feedback on Facebook, Twitter, and other places. Customer feedback on social media tends to reside on either end of the spectrum – elated or infuriated. But if trends appear, you should incorporate it into your analysis.
7 steps to analyze customer feedback
Once you’ve determined how you collect customer feedback and decided which customers’ feedback you want to pay attention to, how do you transform customer feedback into something you can act on as a company? How can you take a jumble of feedback from open-ended questions and use it to inform your product roadmap?
Follow these steps, and you’ll have a prioritized list of customer insights you can act upon with confidence. You can even use the output of your analysis to inform your product roadmap.
1. Collate your data
First, collate all the open-ended customer feedback you want to analyze, plus key metadata about each customer, into a spreadsheet. Ideally, the metadata will include attributes such as how long the person has been a customer, how much they spend, the date the feedback data was submitted, and the source of the feedback e.g. open-ended customer survey question. Of course, you can use Intercom to help gather this data. Your column headings should look something like this:
2. Determine how to categorize the feedback
A general rule that you can apply to help you make sense of customer feedback is to group it by:
- Type of feedback
- Feedback theme
- Feedback code
Let’s break these down.
Categorizing your feedback into different types is particularly helpful if you’re dealing with unclassified feedback from your customer support team or situations where customers could write anything they liked in a survey field (e.g. “Any other feedback for us?”)
Here are some categories you may find useful:
- Usability issue
- New feature request
- User education issue
- Generic positive (e.g. “I love your product!”)
- Generic negative (e.g. “I hate your product!”)
- Junk (this is useful for nonsense feedback like “jambopasta!”)
- Other (this is useful for feedback that’s hard to categorize. You can go back and recategorize it later as patterns emerge in the rest of the data)
Breaking feedback down into themes can be useful when you’re trying to make sense of a high volume of diverse feedback, so if your data set is small (roughly speaking, 50 pieces of feedback or less) then you may not need this.
The themes you come up with will be unique to the actual feedback data you’ve received and will usually relate to aspects of the product. For example, let’s say you work on a popular product like Instagram and you’ve received a bunch of customer feedback. Your themes might look like a list of specific product features, like this:
This type of categorization is particularly useful when you’re working in a situation where you’re likely to have to feed your insights back to multiple teams to take action on (i.e. if you have one team that works on Stream, another on Stories, etc).
Sometimes themes can by team-related (e.g. customer support, sales, marketing) or they could be related to unmet needs that customers are experiencing. Try coming up with some themes and see if these types of categories are useful to you and the data you’re making sense of.
The purpose of the feedback code is to distill the raw feedback the customer has given you and rephrase it in a more concise, actionable way.
Your goal is to make the feedback code descriptive enough so that someone unfamiliar with the project can understand the point the customer was making. The feedback code should also be as concise and true to the original customer feedback as possible. Your job is to distill the feedback as objectively as possible, whether you agree with it or not.
Here’s an example:
3. Get a quick overview
You want to get a feel for the data before starting to codify it. Scan through the feedback to get a sense of how diverse the responses are. As a general rule of thumb, if each customer is giving you very different feedback, you’ll likely have to analyze a higher volume of feedback in order to see patterns and make it actionable. If you scan through the first 50 pieces of feedback and they all relate to a specific issue in your product, then you’ll likely have to review less.
4. Code the feedback
Time to roll up your sleeves and focus. Find a place you won’t be disturbed and start reading through each piece of user feedback, carefully coding each row.
The exact feedback codes you create will be specific to the product that the feedback relates to but here are a few analysis codes for some fictitious new feature requests to give you a flavor:
- Assigning a task to multiple clients
- Adding complex HTML to tasks
- Adding or removing teammates from any screen
- The ability to send emoji to clients
If one piece of feedback is communicating multiple points (e.g. two different feature requests), it’s useful to capture these two separate points in separate columns.
5. Refine your coding
It’s okay to start with higher-level codes and break them down later. Pay attention to the exact language people use. Issues that sound similar upon first glance might actually be separate issues.
“As you read more feedback you realize that you need to break one popular code down into a couple of more specific codes”
For example, imagine you initially see a lot of customer feedback related to “Email issues”. However, when you read more feedback carefully, you realize that these break down into separate issues: “Email composer bug” and “Email delivery bug”, which are quite different.
Sometimes, as you read more feedback you realize that you need to break one popular code down into a couple of more specific codes. For example, “More control over visual design” could be broken down into “Ability to add fonts” and “Ability to control the alignment of images.” Remember to go back and recode the earlier rows.
6. Calculate how popular each code is
Once you’ve coded everything, the next step is to calculate the total amount of feedback per code. This will help you see which feedback is most common, and what the patterns are in your customer feedback.
One super simple way to do this is to sort the data in your “feedback type”, “feedback theme” and “feedback code” columns alphabetically, which will group similar items together. Then highlight all cells that have the same feedback code and a total count will appear in the right-hand corner of your spreadsheet. Create a summary table to record all the total counts for each feedback code.
“Which customers are complaining most about X? What’s the monthly spend of the customers demanding X new feature?”
If you have between 100-500 pieces of feedback, add a new column next to your “Feedback code” column, and enter a “1” for each row that has the same feedback code (e.g. add a 1 next to all cells that say “Ability to crop image”. Then add up how many times that code appears. Repeat for the other feedback codes.
If you have a larger data set, you can create a pivot table to do these calculations. With large data sets, it’s also valuable to dig deeper at this point and analyze the other customer attributes that you collected. Put the customer attributes (e.g. customer type, customer spend) into a spreadsheet and look for other correlations with the feedback you’ve received. For example, which customers are complaining most about X? What’s the monthly spend of the customers demanding X new feature?
7. Summarize and share
Now you’ve coded your data, you can create a summary of customer feedback data based on issue popularity and discuss it with your product team.
If you’ve got 50 pieces of feedback or less, you can summarize actionable feedback in a simple table or one-page doc. If you have a larger set of feedback, you can break the data down by the other variables we discussed earlier (“feedback type” and “feedback theme”). This will make it much easier for you to take the different buckets of feedback you’ve identified and channel them to different people in your company who can take action on the feedback.
Case study: Albacross
You can also leverage customer feedback to grow your brand. Let’s use the experience of lead generation software company Albacross as an example.
As Albacross grew and their customer base expanded, the team was interested in getting more in-depth customer feedback. Not only that, the team wanted an easy way to follow up with customers who gave feedback. But rather than sending the same rote response every time, the team wanted to personalize each response based on the score that users gave.
To encourage more customers to give meaningful feedback, Albacross started using the customer feedback platform Wootric to regularly measure net promoter score (NPS). New users receive an in-app request to rate the app 30 days after sign-up. If they respond, they then receive a follow-up survey every 90 days. Users who don’t respond are asked for feedback every 30 days.
The Albacross team uses the Wootric integration for Intercom to import the ratings data into Intercom. From there, they use Intercom to send automated follow-up messages that are customized to users’ ratings.
For users who rate the app poorly (NPS scores 0-6): Albacross shows a message that asks for additional feedback, with the goal of starting a conversation with the user and gaining a deeper understanding of the issues. To make it as easy as possible for customers to answer, Albacross keeps the message brief and only asks users for a single thing that they could improve.
For users who give the app a passive rating (NPS scores 7-8): Albacross triggers a thank you message that asks them to leave them a review on Capterra. By transferring positive momentum from their surveys to review sites, the team has been able to increase their presence on Capterra and establish credibility. “It works like a charm because if people are excited to recommend your product, they will most likely leave a positive review,” says Evgen Schastnyy, Marketing Manager at Albacross.
For the users who rate the app very high (9-10): the Albacross team sends a similar thank you email, but personalizes it to come from their CEO.
As a result of their efforts, the Albacross team doubled their NPS score from 12 to around 30. They now have over 100 reviews on Capterra, with an average rating of 4.5 out of 5. “Most of the great reviews we’ve gathered recently are thanks to the Intercom messages we’re sending to NPS promoters,” says Evgen. Their experience goes to show just how powerful customer feedback can be when you actively seek it out and engage with it.
It can be hard to know how to go about analyzing customer feedback, especially if you don’t have researchers or analysts at your company who can help. However, if you follow the advice in this post, anyone can turn a jumble of customer feedback into a clear summary. Best of all, you can then use that summary to make informed decisions in your company and, in turn, improve your products.