Customer surveys are an opportunity to learn what customers think about your brand based on facts, rather than assumptions. The customer feedback you gather from surveys is gold dust. Within them lies all the information you need to provide the products and services customers really want.
And it doesn’t stop there.
Giving customers the opportunity to provide feedback empowers them by giving them a voice, showing they truly matter to you.
Ultimately, survey feedback helps foster a customer-centric culture which in turn creates happier customers. And that’s good news because happier customers mean higher retention, more sales, and a thriving business.
Planning your customer survey
In the initial stages, conducting a customer survey can seem overwhelming. Begin by asking yourself this question:
"What am I trying to find out?"
Effectively, you will be collecting evidence to tell a story. To do this, you need a clear vision. Is there a particular problem that you are trying to address? For example, your answers to the question “What am I trying to find out?” might include:
- Why is my customer churn increasing?
- Why is my Net Promoter Score decreasing?
- Why are we losing customers in the first month of onboarding?
Let’s assume customer churn is very high and you want to understand why. Create a specific goal outcome you would like to achieve around improvement, e.g. reduce churn by 1% in three months.
Get team buy-in
Organizations that involve everyone in customer feedback, as well as the actions taken on the back of it, are significantly more successful than organizations that leave the task in the hands of one, or a small number of people. Carrying out survey projects, therefore, requires buy-in company-wide, not just from leadership. These other departments can also help you craft questions.
It helps to be clear what everyone stands to gain. For example, when running a customer churn survey, here’s how other teams benefit:
- Product - helps them improve the product and identify new features
- Marketing - helps them create better messaging by understanding what customers like
- Sales - helps them understand which features to focus on when selling
- Management - helps them understand customer experience to inform decision-making
- Customer support - helps them prepare them for issues they will encounter
Determine your customer survey approach
How will I measure my concepts?
Do you need qualitative or quantitative data? Quantitative data, such as the familiar Likert scale ratings from strongly agree to strongly disagree, are useful because they’re easy to analyze. Here’s an example:
But qualitative data can create far richer insights, opening up answers to the voice of human experience. Using open-ended questions can be a great way to help build context. For example, quantitative data may tell you that a user was unhappy with customer support, but qualitative data can tell you why exactly that was and so produces data that can be acted upon more easily.
Open-ended questions may include:
- What made you decide to end your relationship with us?
- What would have made you stay with us?
- How could we have improved your experience?
Gather ratings with quantitative data, then provide the opportunity for customers to expand on the reasons behind their answers. Be careful not to overload yourself with free text though, or the data will be hard to analyze. Advances in AI starting are now allowing large-scale automated analysis of freeform text, so crunching this type of data is becoming much easier.
Building accurate surveys, the results of which truly represent what is being measured in a population, is no easy task, but it’s important to know that your survey is measuring what it should be. The results your survey produces should be both valid and reliable and requires the consideration of a number of factors.
Are you measuring what you actually think you are measuring? In other words, is your scale accurate? If you think you are measuring how happy your customers are with the business, but ask them how happy they are in general, rather than how happy they are with your brand specifically, you are not measuring what you set out to.
DO: On a scale of 1 to 10, rate your happiness level with [COMPANY].
DON’T: On a scale of 1 to 10, rate your happiness level.
Do the items of a scale capture the same thing over time, in different circumstances? In other words, are the responses consistent?
The easiest way to make sure your survey is reliable is to work with reputable companies and make use of existing scales that have already gone through this rigorous process. For example, if you are looking to measure customer satisfaction, depending on the exact aspect of customer satisfaction you are interested in you may want to look at CSAT, CES, or NPS.
Demographic data are very useful because they give you a way to filter for patterns. If you already have this available through your CRM, then pull in the information automatically, but if not, then make sure you gather it. Some examples of demographic data include:
- Marital status
- Geographic Location
A word of warning: Historically, surveys have been binary around factors such as gender and relationship status. Offer a range of answers that reflects the broader spectrum of ways people identify nowadays.
-Prefer not to say
-Married or in a domestic partnership
Optimal customer survey length
Keep surveys relatively short, so they don’t take much longer than 5 minutes to complete, which may be around 10 questions or fewer, depending on their nature. Ask only what you really need to know and are prepared to take action on. Otherwise, you’ll risk customers not completing it. Even if they do, you’ll end up swamped in data that takes time to analyze and doesn’t offer any real benefit.
Distributing customer surveys
Thanks to the internet, distributing customer surveys has become a lot easier. But there are still a number of considerations you need to take into account when thinking about how, when, and who you want to send your survey to.
How many responses does your customer survey need?
A very common question customer teams ask is “How many customers do I need to survey?” That depends on your particular circumstances. What always remains the same is that you need enough responses to reach statistical significance. In other words, you need to obtain a result that is very unlikely to have occurred by chance, otherwise, you can’t draw trustworthy conclusions.
There are a few things you’ll need to know to work this out.
Population size: The total number of people whose opinion your sample will represent. This could be your total number of customers, for example.
Margin of error: The range of your population’s responses may deviate from your sample. Ideally, this should be 5% and should certainly never go above 10%.
Confidence level: The probability that your sample size accurately represents the attitudes of your population. A good benchmark to use for that is 95%. This is to what extent you can be sure your results are accurate.
Using these factors, you can work out your:
Sample size: The number of people who will take your survey.
Even with a good knowledge of statistics, the math behind working out sample size is a little complicated, to say the least. But thankfully there are online resources to work it out for you. All you have to do is input the numbers.
When should you survey your customers?
When to issue your survey depends on the particular type of survey you are doing. Broadly speaking, there are two types of surveys:
Transactional surveys are triggered on the back of certain customer actions, so survey distribution is determined by when your customers undertake these actions. In these cases, think carefully about which touchpoints you want to use as venues for your survey and distribute them appropriately throughout the customer journey. Focus on high-value touchpoints; for example, when a customer has just finished speaking to someone on your team.
For transactional surveys, a question could be for example:
How likely are you to use this service again?
Answer options would include: Very likely, likely, neither, unlikely, very unlikely.
Relational surveys poll customers about their relationship with your brand. The number of customers who receive relational surveys is entirely up to you. Choosing the precise level of frequency requires some thought. You want to get enough responses to trust the data, without pestering people too much. As a guide, Survey Monkey recommends once every quarter per customer.
For relational surveys, a question could be for example:
How likely are you to recommend [company] to a friend?
Answer options would include: Very likely, likely, neither, unlikely, very unlikely.
You may also wish to survey customers regarding upcoming product or service development they would like to see. This is likely to make sense before a product development cycle, or whenever it fits into your company agenda. Ideally, you would keep this going on endless cycle, making sure you don’t survey individual customers more than once per quarter.
Method of distribution
Choosing a channel to distribute your survey can be tricky.
When it comes to transactional surveys, it’s best to use the same channel as the interaction and keep it in real-time so the customer’s experience is still fresh. For example, through live chat you could survey a customer in the chat widget immediately after an interaction. If that isn’t possible, try sending an email so you don’t lose the data.
In general, surveys tend to be taken through email because it’s easy to set up and automate, though you may suffer if the emails get classified as spam. You could even use SMS, social media, build the surveys into your web property, or reach out via your app. Ultimately it comes down to what is most practical for you and your customers.
Some of the top distribution methods for customer surveys include:
- Email: Ideal for polling your database, in particular, lost customers, who may not interact with your brand anymore.
- Live chat: Useful for transactional surveys relating to a customer support experience that has just been delivered and for personalizing survey questions.
- Phone: Ideal for occasions when lots of details are needed, the company has a very small number of clients, or the clients are of extremely high value.
- Mobile app: Good for younger generations, as they spend more time on mobile. It also helps with transactional surveys, as many users may be accessing services through the app.
- SMS: Good for grabbing attention, convenience, speed, and flexibility. Popular among millennials.
Analyzing data for actionable insights
What will I do with the data?
Forrester reports that while 74% of companies say they want to be data-driven, only 29% are actually successful in their endeavors. Creating actionable insights and following them up gives you a real advantage over your competitors.
If you think about it, knowing that your customers are dissatisfied doesn’t really help you. Knowing why your customers are dissatisfied and how to go about fixing it does.
Let’s assume the customer churn survey returned results that scored poorly on:
“Customer service was helpful.”
It’s clear that customer service is letting you down, but why?
The open-ended questions then allow you to dig deeper and analyze responses.
“What would have made you stay with us?”
A common theme then emerges. It turns out that customers were unable to get in touch with your company because support is only via a call center, which is often closed. Customers want other ways of getting in touch with you.
Offering technology such as live chat provides new channels for support queries. By extending staffing hours and making use of chatbots to pick up on repetitive queries, you cut wait times as well, getting right to the heart of the problem and fixing it.
Sharing is caring
Communicating the findings to the wider team is important so people feel involved. Sharing insights with colleagues and departments that can actually do something about it is also a great way of making sure valuable insights get acted upon.
When conveying findings to the wider organization:
- Pick out the headlines
- Present insights, not data
- Make it visual
- Keep it short
Show others why they should care about what you have learned and how it affects them.
Know your audience. Getting your data points across may rely on different approaches depending on the scenario.
Address the issues that come up and keep track of exactly what was done and when. Study how these trends change over time based on the adjustments you have made.
A cycle of learning
Building a long-term survey feedback strategy provides an invaluable feedback loop. From this, you can constantly improve your offering and make sure you stay in touch with your customers’ expectations.