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The What, Why & How of Customer Behavior Analysis

Case and point: COVID-19. The pandemic put physical experiences on an indefinite pause and demanded businesses accelerate digital transformations to meet consumer needs. As discovered in our “Data Driving Insights Into the Evolving Customer Experience“, many consumers have not only adopted, but have a new-found affinity for some of those digital-first experiences, including telehealth, mobile banking services, and retail subscription models.

 

Now, as pre-pandemic norms start to make their comeback, businesses must reassess how pandemic-purchasing behaviors and changes in media consumption will continue to shift customer expectations, and – as a result – demand new marketing behavior, as well.

 

We saw this first-hand while helping a client map out and navigate the shifting landscape of food supply and distribution. COVID-19 altered the way in which restaurants do business and created a highly changing and dynamic situation for the industry. But before they could alter the customer journey to meet new everyday business needs, they needed to complete a customer behavior analysis and reconsider their customer segmentations. By conducting a customer survey that included 580 decision-makers within the food/supply ordering chain, we were able to pinpoint specific ways COVID impacted the customer journey (specifically menu evaluation, product selection, and ordering). Additionally, attitudinal segmentation helped us uncover new strategies for supporting each of their core customer groups. At the end of the day, it’s a crucial exercise that can drive increased value realization, customer engagement, loyalty, and market share.

 

So, ready to conduct your own customer analysis? Let’s get started.

Customer Analysis and Customer Segmentation 101

Before we dive in, let’s drive alignment around the definitions of and differences between customer analysis and customer segmentation.

What is customer analysis and customer segmentation?

Customer analysis is the process of researching your customers, using both qualitative and quantitative methods, to develop insights and understanding. Customer segmentation involves using those insights to divide customers into groups centered on similar characteristics.

Why is customer analysis and segmentation important?

Customer analysis and segmentation helps you better tailor your offerings and messaging to add value for your customers, addressing their specific use cases. Survey data from McKinsey shows companies using customer analysis to improve their services consistently outperform their competitors. The results showed 93% of companies whose corporate decisions were driven by consumer analytics earned greater profits than their competitors, that number jumped to 112% for sales growth and 115% for return on investment.

 

Also read: How to Holistically Map Your Customer Experience

Businesses must reassess how pandemic-purchasing behaviors and changes in media consumption will continue to shift customer expectations, and demand new marketing behavior.

A Customer Analysis Framework to Increase Customer Engagement

There are four stages that any customer analysis project should follow:

Stage 1: Identify current customers

How much do you truly know about your customers today? Chances are you could have internal data you aren’t fully maximizing that can help you understand more about your customers. This proprietary data could help you form insightful survey questions to ask your customer base so you can get a strong understanding of what drives their purchases.

 

Remember to ask questions that help you understand:

  • Market-based trends influencing purchase decisions.
  • Disruptors, such as changes in technology, that are changing your industry.
  • Competitors that are gaining momentum.
  • Information about your target audience that is missing or inaccurate.
  • Where you can maximize return on investment throughout the customer journey.

Stage 2: Break customers into subgroups based on traits and motivations

After analyzing your internal and survey data, you’ll want to start segmenting groups based on what motivates their purchase decisions. In the case of the leading food service company we mentioned above, we were able to segment customer profiles based on:

  • The level of decision making authority
  • Job role
  • Location — urban, suburban, rural or other
  • Restaurant type
  • Price sensitivity

Although these probably won’t be the exact same segments you’ll use to understand your customers, they give you an idea on how to structure your approach. You want to create segments around realities that could influence what products or services customers want from you and how much they’re willing to spend.

Stage 3: Outline customer groups needs

Once you understand your customer groups, the next step is digging deep into their specific needs. For the example above, we asked questions such as “How long has your business had to close as a result of COVID-19?” or “How have your weekly supply needs changed as a result of the pandemic?” Questions like these help assess new trends for each use case and where customers are experiencing pain points.

 

Needs can develop through a number of avenues so be sure to understand the following when trying to get to the bottom of what customers are actually looking for:

  • Pain points
  • Values
  • Motivations
  • Influences
  • Benefits

Stage 4: Pinpoint solutions for each customer group

Once you know who your customers are and what they’re looking for, you can start to solve the problem! This is where your company will really shine and how you’ll differentiate yourselves from competitors.

 

Here are some solutions you can start to get creative with:

  • What improvements do you need to make to your core offerings, technology or customer service?
  • What resources can you create that would help your customers use your product or navigate their industry?
  • Is there a new product or offering that would highly differentiate your company from competitors?

Also read: How to Use Design Studios For Innovation

Techniques to Improve Customer Analysis

We have a lot of experience with customer analysis and over the years we have found these simple adjustments help create superior customer profiles and insights.

Combine data to create detailed buyer profiles

Using both qualitative and quantitative data can help you create a full picture when it comes to understanding your customers. Qualitative data refers to information you gather from first person interviews, focus groups or observations you make in the field. Quantitative data uses internal metrics and survey results to structure the themes that could be arising from your qualitative information. Using these in tandem can help you understand both functional and emotional drivers to create multi-dimensional profiles.

Customer journey mapping

Customer needs and motivations might change throughout their lifecycle, so it’s important to map their journey so you can pinpoint areas where you might be of greatest assistance (and achieve maximum return on investment). Here’s what to remember when you start customer experience mapping:

  • Chart the important turning points in their journey using the qualitative and quantitative data you’ve collected.
  • Look internally, who are the stakeholders in your organization that are responsible at each part of the sales process?
  • Does your internal map follow the reality of the journey your customers are going on. If not, where do they diverge and how can you adjust your processes to better accommodate for your customer experience?

Tools to ingest, aggregate, and analyze datasets

Data can easily become overwhelming; trying to collate information manually is likely to take a lot of time and cause you to miss themes. Using data software can help eliminate these two problems.

At Tallwave, we empower proprietary software for our clients to help process data, pinpoint customer pain points, and map a digital journey from start to finish. Using a software like this that aggregates all data sources is essential to making sure your customer analysis project gets done on schedule, and is as accurate as possible.

Plan for the design studio and think outside the box

A design studio is a rapid iteration process that helps your team collaborate and align so you can creatively tackle inefficiencies and improve the user experience across your entire organization. This approach could help you understand the way your entire team is approaching the process and arrive at solidified decisions together.

 

If you take a design studio approach, we recommend setting some rules to encourage creativity. Make sure everyone participating is ready to create, not watch. This includes even those who are inexperienced or feel more comfortable watching! Reimagine possibilities together in a space where everyone’s ideas matter.

Create customer feedback system to power agile innovation

Once you’re ready to implement changes, you’ll want to make sure you have a method that allows you to listen to your customers and respond to their feedback fast. Your customers can drive your innovation, so make sure you’re consistently gathering qualitative and quantitative data about them to iterate and continue providing solutions that meet their ever-changing needs!

The Bottom Line

Customer behavior analysis helps businesses across all industries understand where they currently stand and where they need to go in order to improve the holistic customer experience, accelerate value realization, increase customer engagement, and develop new digital-first experiences. As a result of this process, we’ve managed to to improve the ways in which our clients leverage technology and integrate new features to not only understand evolving consumer behaviors – as seen during the pandemic – but plan for their future CX needs.

Want more information about evolving customer behaviors and needs? Read our latest research report or contact our team today.

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Strategy

Qualitative vs. Quantitative Data In CX Design: Everything You Need to Know

This is a common issue for many organizations, big and small, but it’s not an impossible one to solve!

 

If you’re experiencing a similar situation, you need to invest in gathering persona data that will not only tell you who your customers are and what they care about, but why they care and how they expect brands to make them feel.

 

To get started, let’s define each set of data, how it’s gathered and what it’s used for.

 

What is qualitative data?

Qualitative data – or primary data – is commonly gathered by businesses and plays an important role in understanding target audience sentiment and informing customer journey design. By conducting unstructured or semi-structured first-person user interviews, discussions, on-site observations, in-house moderated user testing, web analytics, and focus groups, qualitative data-collecting techniques allow companies to interact directly with their key customers, see how they’re using their products or services and receive feedback in real-time. It helps define the customer journey and establish an initial foundation and understanding of all internal and external customer experiences.

 

There’s just one problem: Sometimes people don’t know what they want, don’t have the words to truly express how they feel, or simply, aren’t honest.

 

That’s when quantitative data comes in.

Quantitative data enhances primary research and design efforts by quantifying key problem areas.

What is quantitative data?

Quantitative data – which can be gathered through a variety of structured surveys, questionnaires, and polls – is essential secondary research. When transformed into statistics, it enhances primary research (qualitative data) and design efforts by quantifying key problem areas. It also allows marketers, developers, business leaders and customer experience drivers to peer into customer details, attitudes, and behaviors from a data-driven standpoint, and test hypotheses established from qualitative data.

Qualitative Data vs. Quantitative Data: When Should You Use Each & How?

Let’s start with the when. To craft the best customer experiences, companies should collect and analyze both data sources on an ongoing basis. Because – and this is a big one – audiences and their expectations are always changing. By executing primary and secondary research to gather qualitative and quantitative data, companies make themselves better equipped to not only identify, but truly understand their customer base – how they interact, experience, and feel about a website, application or overall brand.

 

And don’t forget to gather employee input, as well! Employees are often the first to know what’s working and what’s not. Most organizations shy away from gathering input from employees, but in our experience, leveraging this powerful knowledge base sooner rather than later helps identify root challenges and opportunities to improve faster and more effectively.

 

Also read: Crafting Employee Experiences That Improve Customer Experiences

 

Now, the how. After both qualitative and quantitative data has been collected, follow these steps:

Map your qualitative data

Example of mapping internal & external qualitative data

Using the qualitative data gathered, map internal perspectives around critical touch points and test it against customer feedback that was collected. This should reveal discrepancies between what internal teams believe is important, versus what customers assign value to. By taking this qualitative approach, teams can visually display opportunities and challenges within the current experience. Providing a picture that illuminates the differences between internal and external stakeholder perception makes achieving cross-functional alignment on future plans easier. There’s not a whole lot to argue about when the writing’s on the wall.

Pinpoint exact moments of friction and/or leverage in your customer journey

Utilize quantitative methods via surveys and other previously mentioned techniques to analyze customer sentiment – opinions and responses – as well as perspective at every stage of the journey. Keep in mind, each interaction a consumer can have with your brand, both passive and active, is a touchpoint and part of your overall brand journey. Therefore, every interaction must be diligently and continuously monitored, evaluated and iterated because one singular touchpoint can cultivate customer affinity or aversion.

Pair quantitative customer sentiment with a qualitative understanding of the user journey

Pairing qualitative and qualitative data

Quantifying the customer journey creates a data-driven understanding of the critical inflection points that drive loyalty and churn. This naturally illuminates root causes of friction (or conversion!) and enable teams to be data-driven in problem solving and planning for future CX initiatives and investments.

How To Use Qualitative & Quantitative Data To Decide on Next Steps

At Tallwave, we create an ‘Impact Matrix’ – this tool highlights opportunities for improvement and compares the impact they’ll each have against the level of effort and investment they’ll require. This helps create alignment and buy-in for low-risk, high impact initiatives that are critical to shaping and improving the customer experience.

 

Find a similar exercise or tool to visually demonstrate all the opportunities that lie ahead and inform the build of a new strategic roadmap that can take your teams and company into the future.

 

Perhaps most importantly, don’t let perfection get in the way of progress! Making big system changes to your end-to-end user experience may take time, but avoid trying to solve it all at once. Identifying the biggest opportunities and making incremental improvements over time, while learning along the way, will make a huge difference.

 

Last but not least, don’t stop. This isn’t a “set it and forget it” game. Customer behavior – be it with an existing website, application or with a brand across numerous touchpoints – must be closely monitored to ensure both user and business goals are consistently met. If they’re not, all teams – Content Strategy, Product Development, People & Culture, Performance Marketing – must align to identify solutions for evolution and continue growth.

 

Also read: Why Customer Experience Can’t Be All Data-Driven

Don’t let perfection get in the way of progress! Identifying the biggest opportunities and making incremental improvements over time, while learning along the way, will make a huge difference.

Bottom Line

Let data be your guide. Qualitative input is key, especially early on, but also leverage quantitative data as much as possible to make decisions. The combination of qualitative and quantitative helps you identify where there is friction, but also gives you the context you need to develop solutions that hit the mark. And if you don’t have the right data infrastructure set up today, that’s a good place to start.

If you need help collecting, comparing and mapping your qualitative and quantitative data to improve your customer journey and overall experience, contact our team today!