February 11, 2020

The basics of customer experience research

Improving customer experience needs a deep understanding of the entire customer journey and makes structured research the key to success. Customer experience is influenced by multiple online and offline channels, and often happens along a long time frame. These facts make it necessary to carefully evaluate what methods and tools are useful for each specific research and innovation goal.

a sign that says: ask more questions

This article will cover the following questions:

What is customer experience research?

Customer experience (CX) is your customers entire individual perception of their experience with your brand, product or service. It is influenced by each interaction happening between your company, product or service and its customer. This includes for example ordering a product in your online shop, receiving the product via the counter or receiving a newsletter.

Visualization of a customer experience in Form of a line with positive and negative valuations
Understanding your customer’s experience helps to improve your products or services.

Customer experience research describes the collection and analysis of any type of data relevant to the experience your customers have when interacting with your company. The goal of customer experience research is to increase a company’s competitive advantage by better understanding customers needs and pain points and using these insights to improve the overall customer experience.  

Why is customer experience research important?

Customer experience research is essential for understanding and meeting customer expectations, driving business growth, and building long-term customer relationships. It allows businesses to continuously improve and adapt their strategies to deliver exceptional experiences that delight customers.

More specifically, CX Research helps you with:

  • Increasing customer satisfaction and loyalty
  • Achieving competitive advantage
  • Generating business growth
  • Higher customer retention and reduced churn
  • Improved product and service development
  • Saving cost

Especially in times of social media, customer experience is becoming a crucial competitive advantage for organizations. Through the quick distribution of information on social platforms, a negative experience can cause enormous harm within a short period of time. At the same time, a positive experience can lead to loyalty and recommendation.

Researching customer experience can provide valuable insights for enterprises and help understanding customer needs, desires or pain points. With this information at hand companies can increase customer satisfaction and develop a customer-centric business model.

Visualization of amount of interactions and emotional evaluation across several touchpoints.
Collecting customer insights can help you identify your customer’s pain points and needs.

How to conduct customer experience research?

It all starts with defining who you want to research and what information you want to gain.

The why: develop a research question and scope

What is your aim with the research? Why are you pursuing this question? The starting point of successful research is a clear research question and a defined aim. You could ask questions like:

  • Why do my customers rate the restaurant’s service negatively?
  • How do my customers experience the booking process?
  • What is the experience like for my employees during the weekend shifts?

Research can also have different scopes. For example: you’ll have a different scope if you look at a service which takes 15 days (e.g., the period from the booking until the flight), than if you look at a specific part of the service that takes 15 minutes (e.g., a customer gets in contact with your customer service in order to solve a problem with their flight booking).

Two people discussing a visualization of a customer experience
Analyzing your customer’s experience is the key for a better product or service.

State if you want to research a specific point or if you want to zoom out and look at your offering from a higher level.

Assumption vs. research-based work

Assumption-based work

This is where the researcher sketches out what they think the customer journey looks like. Assumption-based customer journey maps can be useful as a first draft because they can help you plan your research. It also might help to highlight the assumptions that might have been made concerning a problem. When it comes to making decisions – base them on research.

Sticky notes are helpful when working together in a customer journey map.

Research-based work

To create research-based journey maps or personas, draw on the data you have. For example, with a customer based project – chances are you have knowledge about your customer through analytics, order history, CRM databases and so forth. Co-creative workshops with your customer or folks who have profound knowledge or lived experience of the subject matter can also be a way to create research-based personas or journey maps.

Link to basics of personas article: You will learn what personas are, why you need them, how to research, define and create them and some templates and a cheat sheet.

Of course, research-based personas or journey maps need more time and resources. Ultimately tools based on valuable research are better to reference when making important decisions and are much closer to reality.

Tip: It’s helpful to write the research question down or post it up in your work space so you can always look back to it and align your research with your aim.

The who: sample

Who are the relevant people for your research? Who will you talk to? Is it users? Customers? Employees? Other stakeholders? Do you want to get information about the interactions between these groups? This decision will make sure that you only get relevant data out of your time and financial resources.

Small sample of 1-20 participants (gaining insights) compared to large sample of 20+ participants (discovering clusters)
When thinking about the sample size for your research, keep your overall goals in mind! Smaller samples enable different conclusions than bigger ones.

A few aspects to consider when defining a research sample:

  • The number of participants: what’s the right size for my purpose?
  • The characteristics of participants: do I only want to focus on certain customers?
  • Am I mainly interested in people who have used a specific service, during a specific time period?
  • The type of technology participants use: are they okay with using a smartphone?
  • The amount of time participants have.
  • The way you invite participants: sometimes people participate together, e.g. one parent fills in reports representing the family. Also, do you want a random sample or would you prefer picking participants manually? The method with which you invite people will affect that.

Once your research question has been defined and the participants have been identified, you can focus on what research methods suit your subject best..

Triangulation

Triangulation is used in qualitative research to maximize the quality and validity of the research. The idea of triangulation is that every research you do has its advantages and disadvantages. Triangulating methods, data etc. helps you reduce bias and balance the types of learnings you generate. E.g., if one research method leaves some black spots behind, another research methods can help put some light on it. So even if you don’t manage to triangulate everything, make sure to at least have a second source of data that helps verify your findings from a different perspective.

You can triangulate these research methods:

  • Methods (e.g., interview, survey, and observation)
  • Data types (e.g., text, pictures, and video)
  • Participants (e.g., customers, employees, and management)
  • Researchers (e.g., customer service, marketing and developers)
  • Environmental (e.g., different time/day/season)

Scroll down for a more detailed description of the potential methods.

Time frame

Deciding a time frame is necessary in order to get valuable data. The time frame of your research will depend on your research question, the scope of your project, and the resources that you can allocate to the project.

Make sure your time frame is long enough to really tackle the research question holistically, but keep it as short as possible so you can start working with the generated data as soon as possible and have a few iterations instead of over-engineering things.

Tip: Qualitative research processes evolve. You might need to dig deeper into a certain area or shift focus once you find a specific user need or problem.

Customer experience research methods

In order to research your customers’ experience you can use qualitative and quantitative research methods.

Whilst qualitative research helps you to get actionable insights and provides your with in-depth knowledge, the quantitative counterparts can help you verify these learnings, check for generalizability and monitor KPIs over time.

Using quantitative methods to monitor KPIs over time vs. qualitative methods to get actionable insights

The main difference between qualitative and quantitative customer experience research methods lies in the nature of the data collected and the approach used to gather insights. Here are the key distinctions:

Qualitative Research Methods

Qualitative research methods provide rich, detailed insights into customer experiences and perspectives, using open-ended questions and smaller sample sizes.

  • Data Type: Qualitative research methods gather subjective and non-numerical data. They aim to uncover rich, descriptive insights, opinions, and experiences from customers.
  • Sample Size: Qualitative research typically involves smaller sample sizes, often consisting of a few individuals or small groups. The emphasis is on depth rather than breadth of understanding.
  • Data Collection Approach: Qualitative methods use open-ended questions, interviews, focus groups, observations, or ethnographic techniques to explore customers' thoughts, feelings, and behaviors. These methods allow for detailed, narrative responses.
  • Analysis: Qualitative data is analyzed through techniques such as thematic analysis, content analysis, or narrative analysis. Researchers identify patterns, themes, and recurring ideas to derive insights and develop an understanding of customer experiences.

Quantitative Research Methods

Quantitative research methods focus on collecting numerical data from a larger sample size, enabling statistical analysis and generalization of findings. Both methods have their strengths and can be used together to provide a comprehensive understanding of customer experience.

  • Data Type: Quantitative research methods collect objective, numerical data that can be analyzed statistically. These methods aim to provide measurable and generalizable insights about customer experiences.
  • Sample Size: Quantitative research typically involves larger sample sizes to ensure statistical validity and representativeness. The focus is on collecting data from a broader customer base to generalize findings.
  • Data Collection Approach: Quantitative methods use structured surveys, questionnaires, or scales to gather data. Questions are often close-ended, allowing customers to select from predefined response options.
  • Analysis: Quantitative data is analyzed using statistical techniques such as descriptive statistics, correlations, regression analysis, or inferential statistics. This analysis enables researchers to identify patterns, relationships, and trends within the data.

Experience research methods categorized in quantitative (surveys, tracking, big data etc.) and qualitative (interviews, observation, ethnography etc.)

In general we suggest picking at least one qualitative as well as one quantitative research method. Qualitative methods, like interviews or focus groups, will provide you with in-depth knowledge about individuals, like their expectations or needs. Also they help to bring up topics you did not consider upfront. Quantitative methods will help you verify these learnings to see if the points also apply to other people.

An overview on the most common customer experience reseearch methods

There is a variety of research methods that can be used to collect customer experience data. All of them have their pros and cons, such as a certain bias that each method inherits or the specific types of data that it yields.

To level out potential biases – triangulate. Choose two or three methods that you think are most promising in collecting useful and actionable data.

Surveys

Surveys can be either paper-based or digital

Data collection

Participants are provided with a questionnaire

Types

paper-based or digital

Advantages

makes data and respondents comparable

Disadvantages

• static
• respondents can only answer the questions that are asked

Researcher’s challenge

• asking the right questions
• asking the questions right
• participant recruitment

Interviews

Picture of an interview situation from above
When conducting interviews, try to remain objective and not influence the situation

Data collection

Participants are asked to talk about specific issues or experiences

Types

• structured, semistructured, or unstructured
• contextual or non-contextual Advantages depending on the grade of structure, respondents can express what is important to them

Disadvantages

• time and cost intensive
• interviewer effect: the interviewer influences the situation and consequently could impact the answers

Researcher’s challenge

• being aware of when they are guiding or leading the interviewee
• remaining objective

Observation

observation of a cafe from above

Data collection

Researchers watch and take notice of the behaviors of participants in a certain situation

Types

• participatory, non- participatory, or somewhat in between
• covert vs. overtAdvantagesmore objective view on behavior

Disadvantages

• time and cost intensive
• observer effect: people might behave in a way they think it is expected

Researcher’s challenge

• perceiving important information
• being aware of the influence one has on the situation

Auto-ethnography

Data collection

Participants observe themselves and reflect on their behavior, thoughts and so forth

Types

diary studies, photos, videos, audio, artifacts, …

Advantages

insights into the person’s inner thoughts

Disadvantages

• bias caused by researcher’s prior knowledge and experiences
• data might be highly subjective or contextual and need direct explanation by the participant

Researcher’s challenge

• researcher: briefing the participant correctly
• participant: conscious reflection and report of situations

Cultural probes

A notebook with the title field notes written on it

Data collection

Participants collect diverse material in the situation of interest

Types

diary studies, photos, videos, audio, artifacts, …

Advantages

• abstract descriptions become more comprehensible
• recall of information is supported

Disadvantages

collection might take a lot of effort

Researcher’s challenge

collection/report of cultural probes

Mobile ethnography

person with smartphone at hand

Data collection

Participants use their mobile to report experiences in real-time

Types

open vs. structured approach

Advantages

• mobile device
• recall bias minimized through reports in real-time
• minimal researcher bias

Disadvantages

high effort for participants

Researcher’s challenge

• researcher: briefing the participant correctly
• participant: conscious reflection and report of situations

You collected so much data, now is the time to structure it! This piece of content will help you to structure your customer experience data.

And now, what's next?

Now it's about implementing what you've just learned: start researching customer experience and create a repository of useful CX insights.

With the customer journey tool Smaply you can create a hub of CX research and take your innovation further from there.

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