You might have an idea of who your customers are. But only customer analysis can tell for sure who your customers are, what they want, and how they interact with your products or services.

So how do you start collecting and analyzing customer data with product analytics?

In this article, let’s explore:

• What customer analysis is and why it’s essential for business growth.
• Different types of customer analysis you can implement.
• A step-by-step guide to conducting effective customer analysis in SaaS.

What is customer analysis?

Customer analysis is the process of understanding who your customers are by examining their demographics, behaviors, needs, and purchasing patterns.

This process allows you to segment your customer base and gain insights. As a result, tailor products, services, and marketing strategies to meet the specific needs of different customer groups.

Types of customer analysis

Customer analysis can be broken down into two key categories: behavioral analysis and demographic analysis.

Each provides unique insights for your next product strategy, so let’s go over them:

Behavioral analysis

Behavioral analysis examines the actions customers take during their purchasing journey. It focuses on two factors:

• Buying criteria, which is about understanding what drives customer decisions. The criteria often involve price, quality, convenience, and prestige (though in B2B, factors like service reliability or payment terms are crucial).
• Purchase patterns, which take a look at the actions involved before, during, and after a purchase (especially useful in B2B). It requires analyzing data like purchase frequency, average transaction size, and preferred purchasing channels.

To measure the value of a customer based on these factors, there’s one method called the RFM model (Recency, Frequency, Monetary value). It segments customers based on how recently they’ve made a purchase, how often they buy, and how much they spend.

This method allows you to prioritize marketing efforts and personalize outreach based on customer behavior patterns.

Demographic analysis

Demographic analysis focuses on understanding who your customers are. It allows you to tailor products and marketing to meet the needs of specific customer segments based on age, gender, income, and geography.

For example, knowing your customers’ education levels can influence product development, advertising campaigns, and messaging strategies for a Higher-Ed product.

Key metrics to track with demographic analysis include:

• Age and gender.
• Income level and education.
• Geographic location.
• Family status and lifestyle.

How to conduct effective customer analysis

Conducting effective customer analysis requires a structured approach that helps you gather meaningful insights and apply them to your business strategies.

Below is a step-by-step guide to performing accurate customer analysis:

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Segment your existing customers

Customer segmentation is the process of dividing your customer base into groups based on shared characteristics. It helps target customers’ needs and improve personalization.

To do this, start by identifying the criteria for segmentation that align with your business objectives. For example, if your goal is to attract more enterprise customers, you may want to segment based on company size, industry, or decision-maker roles.

Then, segment your existing customer base based on:

• Geographic: Countries, cities, urban or rural areas.
• Demographic: Age, gender identity, religion, education, and socio-economic status.
• Behavioral: Interaction with your product, usage frequency, and purchasing behavior.
• Media: Where and how they consume media (social media platforms, email, etc.).
• Psychographic: Customer interests, opinions, and beliefs.
• Benefit: What customers value most about your product or service.
• Buying decisions: Their role in the buying process and perceived decision criteria.

Interview or survey them to understand purchase drivers

Once you’ve segmented your customers, the next step is to understand the drivers behind their purchasing decisions.

For this step, surveys and interviews are great ways to gather direct customer feedback. Just make sure to design your questions to uncover what motivates users to choose your product, the problems they’re trying to solve, and what they value most in a solution.

For instance, you can use open-ended surveys to gather qualitative insights such as:

• “What was the biggest challenge you faced before using our product?”
• “What problem were you trying to solve when choosing our product?”
• “Which features influenced your purchase?”

Then, conduct one-on-one interviews with key customers to fill deeper gaps that surveys can’t cover. For instance, if surveys indicate low satisfaction, interviews with customers might reveal that ease of integration with existing CRM tools or the ability to generate detailed reports are their top priorities.

Gather additional data from your teams

Customer-facing teams such as marketing, customer success, and support are gold mines of insights into customer behavior and preferences.

They interact with customers at different stages of their journey on a daily basis, making them perfect sources for customers’ patterns, needs, and challenges than you’ll ever be.

For instance:

• Your marketing team might have data on where customers are coming from (whether through paid ads, organic search, or social media).
• The customer support team may have insights into the most common issues customers face after purchasing.
• Customer success teams can provide feedback on what features and benefits are most valued by long-term, loyal users.

When gathering this data from internal teams, you’ll be able to build a more complete picture of your customers’ journey and improve how you engage with them at every stage.

Leverage insights from your CRM tool’s analytics

Your customer relationship management system (CRM) holds valuable data about your customers and their interactions with your business. It can reveal critical information, such as the typical customer journey, traffic sources, and which marketing efforts lead to conversions.

For example, you can track which marketing campaigns drive the most traffic to your platform, what ads customers engage with, and where customers drop off in the buying process.

Additionally, CRM tools also provide data on customer personas, including their job roles, company size, and industry. This way, it’s possible to tailor your products, marketing strategies, and roadmap to satisfy these personas.

So if you want to fine-tune your marketing strategies, optimize customer onboarding, and improve overall customer retention—take a look at your CRM data!

Build your ideal customer profiles

After collecting high-quality data from different sources, it’s time for you to create Ideal Customer Profiles (ICPs).

An ICP represents the perfect customer for your business based on data you’ve collected about your most successful and satisfied clients. It goes beyond demographics and behavior to include more detailed information, such as:

• Firmographics
• Technographics
• Revenue
• Pain points
• Goals

Also, in SaaS, developing ICPs can be particularly useful for Account-Based Marketing (ABM) strategies. It allows you to target high-value prospects and cater both your outreach and offer based on their specific challenges and pain points.

That said, to create your first ICP, you can use a template like HubSpot’s ICP worksheet. It will provide a base for you to build on later on as you start to learn more about your customers in the next step.

Implement your findings, iterate, and repeat

Once you implement customer analysis and build an ideal customer profile, the next step is to apply what you learned throughout your business, including:

• Personalized marketing campaigns.
• Product roadmap.
• Revamping core features for usability.
• Customer service.
• Churn prevention strategies.
• ABM campaigns.

Here’s a detailed example: Let’s say your existing customer feedback reveals that enterprise customers are your most valuable segment.

You can implement an Account-Based Marketing (ABM) strategy by segmenting potential customers based on your ICP (using criteria such as lead score, revenue/employee size, needs, pain points, etc), and targeting highly personalized campaigns by:

1. Sending 1-on-1 nurturing/outreach strategies to the prospects with the highest revenue potential.
2. Design specific marketing material based on your ICP’s vertical, job role, and goals.
3. Publish inbound marketing content that caters to your target audience’s needs and pain points.

However, customer analysis is not a one-time process.

You must test your marketing campaigns, audience segments, and messaging to validate your assumptions and discard what you got wrong. And then, iterate again by following the same process but with more data and different insights.

This way, you’ll slowly but surely optimize your way to greater product growth.

Conclusion

Customer analysis is an essential tool for businesses looking to better understand their audience and improve customer engagement.

By following a structured approach to gathering insights, you can create more targeted marketing campaigns, enhance product offerings, and improve customer retention.

Want to see how Userpilot can help you collect and analyze user data for your customer analysis? Book a demo to analyze reports, track feature usage, and segment your users without coding!

Customer analysis FAQs

What is in a customer analysis?

A customer analysis includes customer data such as:

• Demographics
• Behaviors
• Firmographics
• Technographics
• Purchasing patterns
• Preferences

The goal is to collect data that can help you make informed decisions to improve customer satisfaction, retention, and overall business success.

What are the three components of customer analysis?

The three main components of customer analysis are:

1. Customer segmentation: Grouping customers based on shared characteristics like demographics, behavior, or psychographics.
2. Customer needs and preferences: Identifying the pain points and needs of different customer groups.
3. User behavior and interaction: Analyzing how customers interact with your product, from purchase patterns to long-term engagement.

How do you write a good customer analysis?

To write a comprehensive customer analysis:

1. Segment your customers based on relevant criteria such as demographics or behavior.
2. Gather data on each segment’s needs, preferences, and pain points.
3. Use tools like surveys, interviews, and CRM analytics to collect customer feedback.
4. Create an ICP based on your research.
5. Analyze this data to identify actionable trends and tailor your marketing, sales, and product development strategies to better serve your customers.

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