Customer Profiling Tools: The Complete Guide & Best Tech

Struggling to find the right prospects, or create personalised experiences that actually convert?

It starts with understanding your customers.

That’s where customer profiling tools come in.

These tools let you gather, analyse, and act on real data, so you can go beyond basic personas and build detailed profiles that drive strategy.

This post will explain customer profiling, why it matters in 2025, and which tools can help you close more deals faster.

Customer profiling is the foundation of effective marketing and sales strategies, yet many businesses struggle to move beyond basic demographic data.

Top customer profiling tools (2025 edition)

Ready to level up your customer profiling? Here are the tools that are actually moving the needle in 2025. 

1. CRM tools

CRM tools centralise customer data and interactions, making them perfect for building comprehensive customer profiles from your sales and marketing activities.

HubSpot

HubSpot’s CRM combines contact management, sales tracking, marketing automation, and customer profiling capabilities. It’s the Swiss Army knife of customer relationship platforms.

Key features:

• Contact and company profiling with custom properties.
• Behavioural tracking across email, website, and social.
• Lead scoring and segmentation.
• Marketing automation integration.

Pros:

• User-friendly interface with tons of training resources
• Strong integration ecosystem
• Solid free tier to get started

Pricing:

Free tier available. Paid plans for the Sales hub start at $90 per month per seat. 

Best for:

Small to medium businesses wanting an all-in-one solution that won’t break the bank (or require a PhD to operate).

Salesforce

Salesforce Customer 360 connects sales, service, marketing, and commerce data for comprehensive customer views. It’s the enterprise-grade option that can handle anything you throw at it.

Key features:

• Advanced data integration and management.
• AI-powered Einstein Analytics.
• Extensive customisation for complex needs.
• Enterprise-grade security and compliance.

Pros:

• Highly customisable and scalable.
• Extensive third-party integrations.
• Advanced analytics and AI capabilities.

Pricing:

CRM plans start at £25/user/month, but may require significant add-on costs depending on which other tools you need. Custom pricing for enterprise features. 

Best for:

Large enterprises with complex data requirements and multiple departments needing unified customer views.

Data enrichment tools

Data enrichment tools automatically fill gaps in your customer profiles by pulling in additional information from external sources.

Cognism

Cognism provides B2B sales intelligence and data enrichment, helping you build comprehensive customer profiles with verified contact information, company data, and buying signals.

Key features:

• Phone-verified Diamond Data® for accurate contact info.
• Company and contact enrichment with technographic insights.
• Intent data and buying signals.
• GDPR and CCPA-compliant data sourcing.

Pros:

• High data accuracy with verification processes.
• Strong compliance focus for international markets.
• Comprehensive B2B data coverage.

Pricing:

Custom pricing based on data requirements.

Best for:

B2B sales and marketing teams needing accurate, compliant data for prospecting across European and international markets.

Breeze Intelligence

HubSpot’s Breeze Intelligence delivers real-time customer insights and profiles through actionable intelligence and real-time data processing.

Key features:

• Real-time API for instant data retrieval.
• Customisable data points for specific needs.
• Industry categorisation and buying intent.
• Dynamic form shortening for better conversions.

Pros:

• Real-time data processing capabilities.
• Flexible customisation options.
• Focus on actionable insights.

Pricing:

Can get started for free. Paid plans start at $45 per month. 

Best for:

Teams requiring real-time customer insights with customisable data fields.

Survey and feedback tools

Survey and feedback tools let you gather direct insights from customers about their preferences, motivations, and experiences.

SurveyMonkey

SurveyMonkey provides survey creation and analysis tools for gathering direct customer feedback and insights for customer profiling.

Key features:

• Drag-and-drop survey builder with templates.
• Real-time analytics and reporting.
• CRM, marketing platform, and payment platform integrations.

Pros:

• User-friendly interface requiring minimal technical knowledge.
• Extensive template library.
• Strong analytics and reporting.

Pricing:

Paid team plans start at $30 per user per month. 

Best for:

Businesses of all sizes gathering direct customer feedback through surveys for profiling and market research.

Typeform

Typeform creates interactive, conversational surveys that improve response rates and data quality through engaging interfaces.

Key features:

• Conversational form interface with conditional logic.
• Multi-media support for engaging experiences.
• Real-time response tracking and analytics.
• Multiple CRM and marketing tool integrations.

Pros:

• User-friendly due to conversational interface.
• Mobile-optimised forms.
• Strong design and user experience focus.

Pricing:

Paid Core plans start at $25 per month when paid annually. 

Best for:

Companies wanting to improve survey response rates through engaging, interactive forms.

AI-powered tools

AI-powered tools use machine learning to automatically analyse customer data, predict behaviour, and create dynamic profiles that update in real-time.

Segment by Twilio

Segment collects, unifies, and routes customer data to create comprehensive profiles from multiple sources and touchpoints.

Key features:

• Real-time data collection and unification.
• Integrate web and mobile data in a single API. 
• AI-powered audience segmentation and profiling.
• Campaign creation leveraging predictive AI. 

Pros:

• The system can connect and work with many types of data.
• Strong privacy and compliance features.
• Extensive partner ecosystem.

Pricing:

Contact sales for pricing information.  

Best for:

Mid-market to enterprise companies needing to unify customer data from multiple sources at scale.

Cognism Cortex

Cognism Cortex is part of our Sales Companion. It’s an AI-powered revenue intelligence platform that analyses customer and prospect data to optimise sales and marketing strategies.

Key features:

• AI-driven customer and prospect analysis with an ICP fit check.
• Integration with Cognism’s data enrichment platform.
• Pre-built prompts that account for business model, strategy, revenue drivers, and more.
• Create tailored ice-breakers with ready-to-go context about the business for the first call.

Pros:

• Advanced AI and machine learning capabilities.
• Focus on revenue outcomes and business impact.
• Integration with existing tools.

Pricing:

Custom pricing based on requirements.

Best for:

Revenue teams needing AI-powered insights to optimise acquisition, retention, and growth strategies.

Defining customer profiling in marketing

Customer profiling is creating detailed descriptions of your ideal customers by analysing demographic, behavioural, and psychographic data. 

The goal is to build comprehensive pictures of your customers, what they want, and how they behave, courtesy of multiple data sources. With this information, you can deliver more targeted marketing, focused product development, and improved customer experiences.

There’s a difference between customer profiles, buyer personas, and segmentation.

You’ve likely heard these terms all used interchangeably before, but they serve distinct purposes. 

Customer profiles are data-driven descriptions of actual customers based on factual information like purchase history, demographics, and behaviour patterns. They’re built from real customer data. They tell you who your customers actually are. 

Buyer personas are fictional representations of ideal customers created for marketing purposes. They include narrative elements like goals, challenges, and decision-making processes, often based on research and assumptions about target audiences.

Customer segmentation divides your customer base into distinct groups based on shared characteristics. Segments are broader categories, while profiles are detailed individual or sub-group descriptions within those segments.

B2B vs B2C customer profiles

B2B customer profiling focuses on organisational characteristics along individual decision-maker traits like: 

• Company size.
• Industry.
• Technology stack.
• Decision-making processes.
• Buying committee dynamics. 
• B2B profiles often incorporate firmographic data and account-based insights.

B2C customer profiling, meanwhile, emphasises:

• Individual consumer behaviour.
• Preferences.
• Lifestyle factors. 
• Demographic data. 
• Purchasing patterns. 
• Psychographic elements like values. 

Why customer profiling matters for businesses

Customer profiling drives measurable improvements across multiple areas of business performance.

Improves targeting and personalisation

With accurate profiles, marketing teams can create targeted campaigns that resonate with specific customer segments, target accounts, or personas. Meanwhile, sales teams can tailor their approach based on prospect characteristics and preferences. 

This targeted approach leads to higher engagement rates and better conversion outcomes.

Lowers customer acquisition costs (CAC)

By understanding which customer characteristics predict success, businesses can focus their acquisition efforts on high-value prospects. 

Customer profiling helps identify the channels, messaging, and offers that work best for different customer types, reducing wasted spend on ineffective campaigns.

Boosts retention and loyalty

Customer profiles reveal patterns in behaviour that can help you assess engagement, customer satisfaction, and even churn risk. 

Understanding what drives loyalty for different customers allows businesses to proactively address potential concerns and design effective retention strategies.

Profiling also enables personalised customer success programmes and targeted upselling opportunities. These initiatives can increase customer lifetime value while strengthening relationships.

Guides product and service development

Customer profiles provide valuable insights for product development by revealing unmet needs, usage patterns, and feature preferences across different customer segments. This customer-driven approach to development increases the likelihood of creating products that resonate with target markets.

Understanding customer profiles also helps your team develop pricing strategies and service offerings based on what different customer types value most.

Types of customer profile data

Understanding the different categories of customer data helps businesses focus their data collection efforts and choose appropriate tools.

Demographic data

Demographic information forms the foundation of most customer profiles, focusing on:

•  Age.
• Gender.
• Income.
• Education level.
• Job or profession.
• Family status.

For B2B profiles, this extends to firmographic data such as industry, company size, revenue, and geographic location.

Psychographic data

Psychographic information helps explain why customers make certain decisions and can improve your messaging. Data points include: 

• Personality traits.
• Values systems.
• Opinions and beliefs.
• Interests and hobbies.
• Lifestyle choices.

Behavioural data

Behavioural data tracks customer interactions across all touchpoints, including:

• Website activity.
• Purchase history.
• Email engagement.
• Social media interactions.
• Customer service contacts.

Geographic data

Geographic information includes location-based data to understand regional preferences and enable localised marketing. Data points include:

• Country and region.
• City and postal codes.
• Climate zones.
• Market demographics.

Technographic data

Technographic data is regularly used in B2B sales and leverages data like: 

• Existing tech stack.
• The system can connect and work with other systems.
• Digital maturity level. 

Lifetime value data

Customer lifetime value (CLV) can help you prioritise high-value customers. The datapoints include:

• Historical spending patterns.
• Purchase frequency.
• Predicted future value.
• Engagement levels.

Customer profiling strategies

Want to get the most from your customer profiling? The key is picking strategies that match your available data, resources, and sales goals.

Psychographic segmentation

This groups customers based on attitudes, values, and lifestyle rather than just demographics. It’s particularly effective for brands where emotional connection drives purchase decisions.

Consumer typology

This involves creating distinct customer types based on multiple data dimensions. Each type represents a specific combination of characteristics that define a recognisable customer group.

Consumer characteristics analysis

This means diving deep into what separates your best customers from average performers. The goal? Understanding what makes customers likely to engage, buy, and stick around.

Step-by-step guide to creating a customer profile

Ready to build customer profiles that actually work? Here’s your roadmap.

1. Define clear objectives

Start with what you want to achieve. 

Better targeting? 

Reduced churn?

Higher upselling success? 

Clear objectives determine which data points matter and which tools you’ll need.

2. Identify your best customers

Look at your existing customer base and find the high-value segments based on revenue, retention, engagement, or strategic importance. These become your foundation for building ideal customer profiles.

3. Gather customer data 

Collect data from multiple sources, including:

• CRM systems.
• Web analytics.
• Transaction data.
• Customer surveys.
• Social media analytics.
• Third-party providers like Cognism. 

The key is ensuring quality and consistency while respecting privacy regulations.

4. Segment your audience

Break down your audience based on traits like spending patterns, engagement, firmographics, and more. Look for clear segments with shared similarities, which can help you define your ICP. 

5. Develop detailed profiles or personas

Transform your segments into detailed profiles with both quantitative data and qualitative insights. Include specific recommendations for how to engage with each customer type.

6. Validate with feedback and testing

Test your profiles through targeted campaigns, A/B testing, and customer feedback. Use results to refine and improve your approach. 

7. Keep profiles up to date

Customer behaviour changes often. Set up regular review cycles and automated data updates to keep profiles current and accurate, and adapt your profiles as needed. 

How AI is changing customer profiling

AI is completely transforming how we understand customers. Here’s what's happening.

Data aggregation and analysis

AI tools simultaneously process massive amounts of customer data from multiple sources, spotting patterns humans would miss. 

Predictive modelling

AI can now forecast customer behaviour, lifetime value, and churn risk with impressive accuracy (especially when combined with human oversight to improve your models). 

These predictions help you engage proactively instead of just reacting to what’s already happened. 

Natural language processing for sentiment insights

NLP tools analyse customer communications, reviews, and social media to understand sentiment and preferences. 

AI is increasingly capable of detecting emotional sentiments in real time, enabling more empathetic interactions (and flagging potential customer concerns before they escalate).

Dynamic profile updates

AI continuously updates customer profiles as new data arrives, ensuring they stay current. Data enrichment tools like Cognism can help ensure that outdated information isn’t ruining your campaigns.

AI-driven personalisation and campaign optimisation

AI automatically personalises content, recommendations, and campaigns for individual customers based on behaviour and past interactions. Hyper-personalised experiences at scale are now possible, predominantly when guided by skilled account managers.

Ethical considerations in customer profiling

Customer profiling has become more sophisticated and data-driven in recent years, raising complex ethical and legal considerations. Let’s discuss the most significant concerns you’ll face (and how to navigate them!). 

Data privacy and consent 

Customer profiling must comply with data protection regulations, including GDPR, CCPA, and other regional privacy laws. These regulations require:

• Explicit consent for data collection.
• Clear communication about data usage.
• Customers’ rights to access, modify, or delete their information.

You want to ensure customer profiling practices include appropriate consent mechanisms, data minimisation, and regular compliance audits. 

If you haven’t yet, update your privacy statement and ask users to opt in to onsite cookie tracking and your current data usage practices. 

Transparency in data use

Customers have the right to understand how their data is collected, processed, and used for profiling purposes. Transparent data practices build trust and help ensure compliance with privacy regulations.

Best practices include clear privacy policies, regular communication about data usage, and easily accessible controls for customers to manage their data preferences.

Avoiding stereotyping and bias

If not carefully designed and monitored, customer profiling can inadvertently perpetuate stereotypes or biases. AI algorithms may amplify existing biases present in training data, leading to unfair or discriminatory profiling.

Researchers are working on ways to reduce bias in AI models to some success, but most working AI isn’t there yet. Human oversight is still needed, and likely always will be.

Regular audits of profiling algorithms, diverse training data, and human oversight help identify and correct potential biases in customer profiling systems. 

Frequently asked questions

What is the best customer profiling tool?

The best tool depends on your specific needs and budget. 

HubSpot offers excellent value for small businesses with its free tier and integrated features. Meanwhile, B2B teams focused on data accuracy might choose Cognism for verified, compliant data. 

How is a customer profile different from a buyer persona or ICP?

Customer profiles are data-driven descriptions of actual customers based on factual information. 

Buyer personas are fictional representations created for marketing purposes with narrative elements. 

An ICP describes customers who derive the most value from your solution and generate the highest returns.

Can AI create customer profiles automatically?

AI can automatically create and update customer profiles by analysing data, identifying patterns, and segmenting customers. However, AI works best when combined with human oversight. 

Skilled sales reps are typically needed to interpret results, ensure ethical profiling, and align strategies with your business objectives. 

What data is needed for customer profiling?

Effective profiling requires demographic, behavioural, psychographic, and transactional data. 

B2B companies need firmographic data, but B2C businesses benefit from lifestyle data.

Is customer profiling legal under GDPR and other regulations?

Yes, when conducted with proper consent, transparency, and compliance measures.

How often should you update your customer profiles?

Demographic data may need quarterly updates, while behavioural data should be refreshed monthly or in real time. Most successful companies review core profiles quarterly and implement automated updates for important and frequently changing data points.

Understand your customers better with the right profiling tools

Customer profiling has evolved from basic demographic analysis to sophisticated, AI-powered insights that drive real business results. 

Success with customer profiling ultimately comes when you combine technology with clear objectives, quality data, and ongoing refinement. Start with one or two tools that address your most pressing challenges and then scale up as you (and your budget!) are ready. 

Ready to transform your customer understanding? Leverage Cognism’s B2B data enrichment to learn more about your customers today. Get your free data sample.