Over the last year, we’ve been speaking to product teams of all sizes about what it is like to build better feedback loops with customers, and the challenges behind driving more effective product discovery. In all these conversations we noticed that most successful teams tend to have a couple of things in common:
- Shorter and frequent learning cycles: Successful teams seem to understand that customer research is not a one-off exercise. They know it is an iterative process, so they invest time and resources to make it happen as often as possible.
- Collaborative process: We also noticed that these teams know that they can’t learn from customers in isolation. They put in place processes and communication channels to make sure the rest of the organization has access to the insights and can actively contribute to them.
- Diverse data sets: Successful teams understand that informed product decisions are based on a variety of data points beyond a couple of customer interviews. They use a combination of quantitative data, unsolicited customer feedback, in-depth user research, user testing experiments, behavioral data, surveys and more to get the big picture and valuable context.
All of the above sounds painfully obvious, but in practice, it takes time, patience and lots of intentional change in order to build the foundations for a better process that can help the business learn from customers faster.
Part of the work required to build these foundations is to have a deep understanding of how tools and methodologies work together. In the video below Teresa Torres from ProductTalk shares an overview on the history and evolution of product discovery and how different approaches can be used to drive more customer empathy across the product team and the business.
One of the many interesting points Teresa makes in her talk is the need for teams to have multiple data points at any given time in order to make better product decisions.
As Teresa explains,
"We don’t want to make a decision based on one A/B test, we don’t want to make a decision based on one customer interview. We want to make our product decisions based on sets of data, sets of research activities. And so in order to do that, we need to make sure that we’re continuously adding to our bank of interviews and to our bank of experiments. We have to develop effective knowledge management techniques. We have to be able to document all the experiments that we’re running. We have to be able to capture interview snapshots and archive them so that when we remember we interviewed this person who had this exact problem, we can go back and find all the interviews where this issue came up. This may sound like it’s impossible to do, but I can tell you that I work with some really big companies in the United States, in old industries like banking and insurance, and they are doing this, and they are doing it really well."
In this lesson, we are going to focus on one of those data points: Customer feedback.
It is very easy to get overwhelmed trying to make sense of customer feedback. Mostly because it tends to be a very manual process and in most cases, a siloed experience, however, in order to take full advantage of this type of data we need to understand how to transform feedback from a pain point into a powerful tool.
Braden Kowitz, User Experience Designer and Partner at Google Ventures, has said,
“When designers don’t know which problems to solve, we spin our wheels. We make products prettier when we could be solving customer’s needs and generating real value. So any company that’s serious about design should get equally serious about listening to customers.”
“Humans are remarkably bad at explaining why they did something in the past and even worse at predicting what they’ll do in the future. So skip over all that and get your customers to show you what they do today, what problems they have right now, and watch where products (including yours) are failing them. I guarantee you’ll learn a lot.”
With that, here are three principles to help you think about customer feedback in a more productive way.
Principle One: Customers Own The Problem, You Own The Solution
Your customers won’t shy away from voicing their dissatisfaction with your product. They’ll also be generous with ideas. However, it’s not the customer’s job to provide you with solutions.
That’s your job.
Use customer feedback to identify patterns in the problems they’re describing and let those patterns be the trigger for deeper research. Customer feedback should not be taken at face value.
Principle Two: Customer Feedback Needs Context
Each customer feedback channel has its own nuances. People behave differently based on who they are and the channels they use. A user on a free trial may not value or use the product in the same ways that the subscribers of your most expensive plans do. And neither of those customers will use your product in all the ways you expect them to.
A group of vocal users may not represent the majority of your customers. Some people leave negative comments in your surveys but remain loyal customers. The process of identifying patterns in your feedback includes understanding the context in which the feedback was generated: the who, where, and when.
Principle Three: Customer Feedback Is Just One Part Of The Puzzle
Your customer feedback and qualitative research are an important part of your decision-making process. But they’re not the only deciding factors. Deciding what to build next requires an understanding of the market, your unique strategy and vision, internal feedback from other teams, and ultimately, a deep understanding of customers’ problems.
The internet isn’t short of blog posts claiming you shouldn’t listen to customer feedback. What they mean is that you shouldn’t take feedback literally. Remember, customer feedback does not equal solutions. But ignoring customer feedback altogether will stop you from truly understanding your customers and identifying opportunities for innovation.
“Get closer than ever to your customers. So close that you tell them what they need well before they realize it themselves.”
– Steve Jobs, former CEO, Apple
Here we discuss different frameworks you can use to identify patterns in your customer feedback and qualitative research. In the meantime, let’s have a look at some of the most common feedback sources you can start taking advantage of.
Customer Support Systems and Live Chats
If you’re using a customer support system, you have powerful customer feedback waiting for you. This type of feedback normally comes from paid customers or active users (people who already know they have a problem and that your product solves it) and can be particularly helpful for getting the basics of the product right. Your users and paid customers will tell you what it is about the product that’s keeping them from having a great experience.
Some of the questions your customer support data can help you answer are:
- Is our pricing clear?
- Is our documentation sufficient, or does it need to be expanded?
- What do our customers complain about most? (Bugs, user experience issues, feature requests, etc.)
- Are people aware of what they can do with the product?
- Are customers using the product in the way we intended?
Regardless of whether you have a live chat function, ticketing system, or work with a call center model, your customer support system is critical to bringing you the data you need to make top-level decisions. Some of the popular software programs for ticketing systems and live chat tools include Help Scout, Zendesk, and Intercom.
You can combine your data from these sources with feedback from social media, email, surveys, and more to create a centralized hub using a tool like EnjoyHQ. In lesson three, you’ll learn all about the importance of centralizing all customer feedback to identify trends your team can act on.
Surveys come in all shapes and sizes. There are exit surveys or cancellation surveys, Net Promoter Score (NPS) surveys, product market fit evaluations, satisfaction surveys to name a few. Data from surveys will help you gather what your most engaged users or customers have to say.
Surveys are known for their low response rate. After all, when was the last time you filled in a survey for a company you didn’t care about? Rather than blindly asking everyone broad questions, surveys are effective for gathering data on very specific areas.
For example, NPS surveys focus on whether or not the respondent would recommend your product or company to somebody else. NPS surveys tend to get extreme responses on your service or product, either from people who really like your product or people who have had the worst experiences with your service. They provide an opportunity to understand what makes your customers tick.
This type of data can give you the best snippets for what customers actually value from your product and will help you design strategies to turn unhappy customers into your biggest fans. Testimonials and highlights from NPS surveys are often key for marketing materials.
Exit, or cancellation, surveys specifically help you understand why your product couldn’t help your customers. These surveys are normally triggered when a customer cancels their account and help you identify which parts of the experience need more attention. It’s not always about the product, either. Sometimes it has to do with lack of communication or failure to deliver great customer support. Conversely, you may find that a user was simply not your ideal customer.
Social Media and Reviews
Similarly to NPS surveys, social media channels and review sites can offer somewhat extreme views on your product or service. These people may be current customers, potential customers, or simply people who’ve heard the good (or bad) about your product. Either way, they feel strongly enough to share their thoughts publicly where they know they will be heard by others.
But are they being heard by you?
It’s important to complement this type of feedback with customer interviews and surveys. Public sources of feedback can be used to discover problems and build hypotheses that need to be explored much more deeply.
Reacting to vocal feedback when prioritizing your product features is not a good idea. Your product prioritizations need to be rooted in a deep understanding of your customers as a whole.
Remember, it’s not just those who talk the loudest who need all the attention. However, it is always a good idea to engage with customers on social channels and let them know you are listening to their feedback.
Internal Feedback (Email, Google Docs, Wikis)
Your team members – from sales to UX researchers to marketing – are constantly interacting with customers. Each of these teams are trying to learn from your customers in order to transform insights into product features, retention, word of mouth and, ultimately, revenue.
These teams will help you paint the full picture of who your customers are. It’s important to have a process in place for helping team members easily share those insights with you. Some teams will redirect that feedback via email or Google Docs, and some via internal chat tools like Slack.
Regardless of the channel, make sure their voices are heard and keep an open mind to their insights. Centralizing this type of data will give your teams the peace of mind that their feedback and the feedback of the customers they’ve interacted with will be heard and considered. Making this data available to the whole organization will also help all teams address issues faster, leading to better conversations, and ultimately, smarter product decisions.
In-Depth User Research and Customer Interviews
Customer interviews are where the real insights take place. The aggregation of multiple feedback sources can help you identify top-level themes and unveil multiple customer problems that are worth formulating as hypotheses. Speaking to customers and observing them in their own environments will drive a deeper understanding of the data you may already have.
“The more you engage with customers the clearer things become and the easier it is to determine what you should be doing.”
– John Russell, President, Harley Davidson
- A Practitioner’s Guide to Net Promoter Score by Andrew Chen
- Why You’re Getting Rotten NPS Data and How to Fix It by Qualaroo
- On Surveys – A comprehensive essay on surveys by Erika Hall
- Lean Customer Development: Building Products Your Customers Will Buy by Cindy Alvarez
- Validating Product Ideas: Through Lean User Research by Tomer Sharon