Do you ever feel like you are flying blind when it comes to your marketing? You have a general idea of what you want to do, but you’re not quite sure how to go about it? Well, you’re not alone. A lot of marketers feel this way, especially when it comes to customer research.

Customer research is one of the most important aspects of marketing, yet it can also be one of the most daunting. It can seem like there’s a lot to consider, and it can be hard to know where to start. But don’t worry – we’re here to help! In this guide, we’ll walk you through everything you need to know about customer research. I’ll explain what it is, why it’s important

Introduction

If you want to increase conversions, you have to figure out who exactly is your primary target audience, what they want, what matters to them and what are the sources of friction for them. If you say your target audience is “pretty much everybody” or “anyone interested in my services”,  you don’t have much of a chance to boost conversions.

Qualitative research is mostly about learning who the customers are, what they want, the language they use. This is critical for copywriting, understanding friction, learning what matters to them about the products you sell, and so on.

Conversions are all about relevancy – if what you offer and how you present it matches their state of mind, you have gained a customer. If your customer is “everybody”, you’re making it extremely difficult for yourself – nobody will identify with “everybody”.

So if you want to learn how to perform customer research for your business, this list is for you.

1. Whom to survey
2. How many people to survey
3. What to ask
4. Analyzing survey responses
5. Word clouds
6. Tools to use for conducting surveys
7. Web & Exit Surveys

1. Whom to survey

Survey people who still freshly remember their purchase and the friction they experienced in the buying process. Only talk to your recent first-time customers (who have no previous relationship or experience with you that might affect their responses).

You want to filter out repeat buyers or people who bought a long time ago. If you ask somebody who made the purchase 6 months or more ago, they have long forgotten and might feed you with false information.

2. How many people to survey

While best online surveys are qualitative (open-ended questions), we still need a good number of responses to get an adequate overview. If you only survey 10 people some loud voices can skew the picture, and it’s easy to identify false patterns.

I’ve found that the best quantity is somewhere between 100 and 200. You don’t need more than 200 as the answers tend to get repetitive and don’t offer additional insight. Remember – this is a qualitative survey, not quantitative (like an opinion poll). Any less than 100, and there might not be enough answers to draw conclusions from.

If you have less than 100 people who recently bought from you, then you do with what you can get. 10 responses is better than zero.

What do the textbooks say about the minimum number of respondents?

The recurring answer to the question ‘how many’ is ‘it depends’.

You primarily are running the survey for qualitative purposes, and you are not going to need to make numerical comparisons between two data sets. This means you can feel reasonably comfortable with fewer responses. The fewer sessions you gather, the wider your margin of error becomes. For example, at 90% confidence, here’s how the margin of error looks for various sample sizes less than 1000:

3. What to Ask

Image Source: CXL Institute

What you want is to get in the heads of your customers, learn why and how they buy, identify sources of friction. Responses will also help you craft customer personas that are based on actual customers (as opposed to your market team’s idea of customers).

My experience is that the sweet spot is around 7 to 10 questions. More than 10 and the number of people who take the survey goes down. Less than 7 and you might not capture as much information as you could.

I recommend asking the following questions as they give the best insight (all open-ended, free format), adjust the wording as you see fit:

• What can you tell us about yourself? The goal here is to see if there are any trends you can spot (e.g. generational). If you’ve got a B2B business, ask about their industry and position in the company (and who makes the decision!). If demographics matter – respondent’s age, sex and income matter for some reason – then you might want to ask this information via multiple choice questions.  Don’t ask it if it’s just “nice to know”, and not crucial.
• What are you using [your product] for? What problem does it solve for you? Here you want to make sure you understand their problem, identify use cases. You might discover some unintended uses as well.
• How is your life better thanks to it? Which tangible improvements in your life or business have you seen? This will tell you the end-benefit your product provides in the words of your customers. If some say really nice things, hit them up for testimonials or case studies.
• What made you sign up for our product / buy from us? What convinced you that it’s a good decision? You want to know what’s working for you in your current website + identify some advantages you might want to emphasize more.
• Did you consider any alternatives to our product / buying from us? If so, which ones / how many? You want to know the intensity of comparison shopping, and who people compare you to. People always comparison shop, but in some cases way more. This is absolutely critical to know in order to make a compelling case to buy from you. You can also use this information to build a ‘compare’ page where you compare yourself to the competition and make a case for your advantages,
• Which doubts and hesitations did you have before completing the purchase? Identify main sources of friction, and address them (or fix them if they’re usability problems).
• What’s the one thing that nearly stopped you from buying from us? This is about identifying friction again, coming from a different angle.
• Which questions did you have, but couldn’t find answers to on the website? 50% of the purchases are not completed due to insufficient information. This helps you identify some of the missing information your customers want.
• What was your biggest challenge, frustration, or problem in finding the right product? This helps you learn about the way people would like to buy.
• Anything else you would like to tell us? Leave room for feedback you don’t know to ask.

Feel free to include some that are specific to your business.

Make sure the information you collect is actionable – don’t ask questions just because you’re curious.  Once you have written your questions, go through them and ask yourself: “What am I going to do with this information once I have it?” Make sure each question contributes something unique and is necessary.

Keep it neutral: try to use language that doesn’t lead the customer any particular way.  Imagine that you are taking this survey as a person with a particular set of answers.  And then go through again with a different (or opposite) set of responses, and see if the question is easier or harder to answer – then adjust the wording so that it is neutral.

Avoid multiple choice (most of the time)

Note that the majority of the answers should be free-form, not multiple choice. You want the customers to be able to express themselves without constraints. You don’t know what you don’t know, and multiple choice will never reveal those things. Never ask questions like “how happy are you with X, rate from 1 to 10” – that’s useless for our purposes.

Remember, you’re after insight! It’s not about ticking the box or creating reports.

Pressure and incentivize

When sending out surveys, remember to put some time pressure on them (“fill this out in the next 3 days”) to get data faster, and remember to reward each and everyone who completes the survey (free product or service, Amazon gift card etc).

Since you want to get up to 200 responses, you want to keep it cheap / free (e.g. digital download). If you don’t offer any candy, the response rate will suffer.

4. Analyze Survey Response

First off let’s be clear: there is no general consensus among qualitative researchers concerning the process of qualitative data analysis. There is no single right way to go about it.

What I’m telling you here is a process that has worked for me and many of my CRO peers + is advocated by some of the researchers.

The process

It’s all manual labor.

1. Be clear about the goals and what you are looking for
2. Conduct an initial review of all the information to gain an initial sense of the data.
3. Code the data: organize it into some manageable form. This is often described as ‘reducing the data’, and usually involves developing codes or categories (while still keeping the raw data)
4. Interpret the data.
5. Write a summary report of the findings.

While these are steps 1 to 5, I want to stress that the process of qualitative analysis is not a linear but rather continuous and iterative. It is perfectly normal and expected that you jump between all these steps, go back and forth.

Be ready to spend at least 4 hours on this, or even a couple of full working days. Don’t be afraid to put in hours to find insights.

1. Goals

Our main goal is to learn about customers. Typically we’re seeking to learn the following:

• Who these people are? What are the common characteristics? Can we form some hypotheses about different customer personas?
• What are the problems they are solving for themselves? We can use this in our value proposition when we state the problem we’re solving.
• What’s the voice of the customer like how do they word things? Your website has to speak the same language your customers do. Notice how they describe the problem, the solution, the desired benefits.
• What are the main sources of friction: doubts, hesitations, unanswered questions? Once we know this, we can take action to reduce the friction.
• How would they like to buy?
• Do they comparison shop? How much? This is important – if they shop around a lot, we need to stress more on our unique benefits and need to be visibly better/different from the competition.
• Any insights about their emotional state?

2. Initial review

In this phase, you go in and look at the responses question by question. Some questions can be grouped together (doubts & hesitations and unanswered questions are both about friction, and “who are you” and “which problem were you solving for yourself” are both about customer personas), and thus looked at together.

The goal here is to identify trends and patterns and create a “code” for each trend. The code is usually a word or short phrase that suggests how the associated data helps us reach the goals we set in the previous steps. Make sure you write the codes down!

Coding enables you to organize large amounts of text and to discover patterns that would be difficult to detect by reading alone. Codes answer the questions, “What do I see going on here?” or “How do I categorize the information?”

In the next phase, you go in and attach codes to as many responses as you can.

NB! Beware of your bias. It’s very human to identify a couple of trends right away (at least a perception of a trend), and then only start looking for information that proves the trend while ignoring everything else. Know that this will happen to you, and self-correct when you become aware of it. If needed, take a break and come back to the data the next day. Or better yet, have a second pair of eyes

NBB! It’s also typical to only pay attention to the first 50 or so results and then skim over the last 150. First responses are in no way more important than later ones. If you get tired and notice that you start skimming over the responses, take a break and come back to it later.

3. Codification

Now that you have a list of codes, go back and attach codes to as many responses as you can (a significant part of the data). Not all responses can be labeled. It’s perfectly fine to tweak, add and eliminate the codes as you get a better grasp on the data at hand. Eliminate less useful ones, combine smaller categories into larger ones, or if a very large number of responses have been assigned the same code, subdivide that category.

The goal is to link elements of the data that are conceived of as sharing some perceived commonality.

For instance, I had a client whose product was ” vegan healthy meal plans”: a weekly grocery shopping list and recipes for each breakfast, lunch, and dinner for 7 days.

When I read through the answers the first time, I noticed that there are 3 typical use cases:

1. Busy mom – too busy to think about what to shop and what to cook
2. Overweight or sick people – want to get healthy by following the meal plans
3. Vegan / people with celiac disease – people who bought it because of the gluten-free and vegan thing

So these 3 became my codes – during the 2nd reading, I went in and added comments/notes “busy”, “overweight” or “vegan”. I counted the number of responses per code to get an idea of the distribution.

This influenced how I prioritized the order of content on the sales page.

4. Interpret the data

• Now that you’ve read the data so many times, what are the patterns you’re seeing? They’re are usually things that stand out.
• Write down what you can about hypothetical personas (as many as you can spot)
• Count how many responses per code you have to prioritize issues

5. Summary report

Write down the key learnings (your memory is not as good as you think) to always keep them at hand for formulating hypotheses (when comparing to other sources of data). It’s also essential for your teammates and clients.

Voice of the customer

Besides identifying trends, pay attention to their language. How do they phrase the problem? Often I copy and use the exact wordings from a survey answer in a value proposition or other key part of the website copy. It tends to work extremely well.

5. Tools to use for conducting surveys

• I absolutely love Google Docs forms. It’s simple and free. (But some don’t since it doesn’t have bells and whistles, and looks kind of plain).
• Typeform. Most beautiful surveys.
• SurveyGizmo

6. Web & Exit Surveys

While customer surveys ask questions from people who bought something from your site, web surveys ask questions from people while they’re on your site.

The main idea here is the same: identify sources of friction. Web surveys can be very insightful here as you’re asking people about it as they’re experiencing it.

Web & exit surveys defined

Web & exit surveys are kind of pop-up boxes that appear to the visitor based on certain rules – like time spent on site, number of pages visited, activity (e.g. moves the mouse cursor next to the browser window closing X).

Here’s an example of what it can look like (appears in the bottom right corner):

We can use this to ask people questions that would help us understand why they’re not completing the purchase.

Won’t visitors hate them? Hate is a strong word. Yes, there’s gonna be some friction caused, but –

• not all of them will see it,
• it’s well worth it and there’s no other good way to get the same kind of data,
• it’s only temporary.

When to pop the question

The main things you want to pay attention to is A) qualifying the visitor (is this a random visitor, or somebody actually considering to buy something), and B) asking the right question at the right time (e.g. asking someone “why didn’t you buy” when they land on the site will cause lots of friction).

• Look at your average time on site and pageviews per person metrics: ask question from people who have above average engagement (for qualification reasons)
• Ask the right question at the right page: don’t ask about NOT buying on the home page, but rather on the checkout funnel pages.
• Ask when they’re about to leave the site (subject to software capability)

Questions to ask

There is no universal best question to ask, so it’s more important to keep in mind the goal here. We want to understand 2 main things:

• Why they came to the site? Does our site match their needs? If not, are we attracting the wrong traffic, or are we underutilizing an opportunity here
• What are the sources of friction? This is more specific than “why they didn’t buy” (understanding that is our main objective, but we have many goals to understand the big picture).

Questions you might want to ask are (changing the wording as you see fit):

• What’s the purpose of your visit today? <– establish user intent
• Why are you here today? <– same
• Were you able to find the information you were looking for? <– identify missing information on the site, best asked on product pages
• What made you not complete the purchase today? <– identifying sources of friction (ask this only during checkout pages, and beware that some people still considering completing the purchase)
• Is there anything holding you back from completing a purchase? Y/N (+ ask for explanation) <– identify sources of friction
• Do you have any questions you haven’t been able to find answers to? Y/N <– identify sources of friction, missing information on the site
• Were you able to complete your tasks on this website today? Y/N, and when No is select, ask “Why not” <– same

Note that there are always trolls that give you stupid answers, just ignore them.

How to get more people to respond

There’s no one magical question that works the best for each audience, so some experimentation is needed.

Typically you want to go down 2 routes:

1. Ask a single free format question (the more you ask, the less answers you get – I don’t recommend asking more than 1 question at a time)
2. Ask a simple yes/no question, and ask for an explanation once they’ve answered it.

The second option works the best for me about 70% of the time. My theory is that it’s very easy to answer a yes/no question, and once prompted with a follow-up question, a psychological trigger called “commitment” (as per Cialdini) kicks in and people have to complete the path they started, thus answering the question. An overwhelming majority who answer Yes or No, also write a short comment.

Here’s an example. I asked 2 questions that got almost the same amount of views, but one got significantly more responses (converted better, so to speak):

What was the difference?

“Losing” question (182) responses: Is there anything holding you back from making a booking? Y/N

Winning question (517) responses: Do you have any questions you haven’t been able to find answers to? Y/N

What can we learn from this? You need to experiment with different wordings. Some work better than others.

Let’s try another experiment. I asked these 3 questions:

1. Why didn’t you complete a purchase today?
2. Is there anything holding you back from making a purchase today?
3. Do you have any questions you haven’t been able to find answers to?

Can you guess which question yielded which result? The results are below (pay attention to views/responses ratio).

 

 

The first question performed overwhelmingly better than the others. Which one was it?

The answer: “Is there anything holding you back from making a purchase today?”.  The second question was “Do you have any questions you haven’t been able to find answers to?” (worst performer) and the last one was “Why didn’t you complete a purchase today?”.

Lesson: “winning” questions might turn into “losing” questions on different websites, and vice versa. Keep experimenting.

Tools to use

I’m going to be honest with you: none of them are perfect. Find one that you like best.

• Qualaroo
• HotJar
• Webengage

7. Conclusion

If you want to increase conversions, it’s not enough to know what your product does and how others have used it. You need to figure out who exactly is your primary target audience, what they want, what matters to them, and why there’s friction for them when buying the products that matter most.

Qualitative research – like surveys or interviews – will help you learn about all of these things so you can better understand how people make decisions around their purchases.

It won’t always be easy; but if you’re serious about increasing conversion rates on your website or landing page, this guide could be a great place to start!

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