How to Use Customer Profiling to Maximise Value

In the age of data-driven decision-making, understanding your customers is not just an advantage, but a necessity for any business striving to thrive in a competitive landscape. Customer profiling, the process of gathering and analysing data to create detailed portraits of your target audience, sits at the heart of all successful marketing strategies.

For businesses aiming to leverage data insights, creating a detailed customer profiling database is essential.

What is customer profiling?

Customer profiling, also known as “consumer profiling”, is the systematic process of collecting, organising, and analysing data, related to consumers, to create detailed profiles or personas.

The process generally involves leveraging various complex data sources, such as:

transaction history
demographic information
online behaviour
social interactions

With this data, businesses can gain insights into consumers’ characteristics, preferences, and behaviours.

Various statistical analysis techniques, data mining algorithms, and machine learning models are applied to identify patterns and trends within the data, allowing businesses to segment their customer base and tailor marketing strategies and product offerings to specific customer segments.

Why is customer profiling important?

Customer profiling allows companies to better tailor their marketing to specific consumer groups. It sounds great, but why is it important? Well, in this day-and-age, consumers have grown wise to blanket messaging and actively avoid imposing pop-ups. What they want is a more personalised experience that places them at the centre, directly connecting to their needs, and putting relevant, valuable products and services in a click’s reach.

You’d have a hard time meeting current consumer trends with rudimentary user pathways and basic demographics alone. Digital consumers are increasingly asserting control over their online experiences, and now have the ability to select the advertising and marketing content they encounter, and when they encounter it.

As your audience becomes more and more spread out across various digital platforms, devices, and channels, the necessity for personalised interactions becomes evermore pressing.

Customer profiling is able to provide a deeper understanding of customers' needs and motivations, enabling businesses to optimise their marketing efforts, improve customer engagement, and drive business growth.

How to build customer profiles in 6 steps

1. Data collection

The first step is utilising the data that you already have at your fingertips. Gather relevant data from various sources, including CRM systems, social media platforms, psychographic data, website analytics, and customer surveys. ‘Relevant data’ should include demographic information, purchase history, browsing behaviour, and first-hand feedback.

Already, you should begin to get an idea of how your current customer base ticks, and be able to benchmark the impact of your current campaigns and channels. However, you’re going to want to go deeper than this — quite a bit deeper.

2. Data analysis

Once data is collected, it's time to analyse it to identify patterns and trends. This involves using statistical techniques and third-party data mining algorithms, which will help to uncover more specific insights about customer preferences, habits, and characteristics.

As part of the data analysis stage, third-party datasets are critical in putting your top-level customer data into context, building a more granular picture of your customers.

For example, from the initial customer data of an outdoor gear store, you have access to:

information about past purchases, including product types, purchase dates, and amounts spent
data on page views, time spent on site, and navigation paths
insights into customer satisfaction, preferences, and suggestions for improvement

And you know that around 52% of your tracked customers are in their 30s. Then, data analysts begin mining the transaction histories to identify patterns, and they notice that customers who buy winter coats often purchase scarves and gloves within the same month.

Comprehensive third-party datasets can take this a step further. By enriching data mined patterns and trends with more granular consumer data, such as, what kind of holidays your customers go on, and when, you start to get a better idea of what to sell, to whom, and when.

4. Segmentation

Based on the analysis, use machine learning algorithms to group customers into segments or personas with similar traits and behaviours. Continuing the example used above, one segment may include “Skiing Holidayers”, who purchase predominantly winter items, while another includes “Frequent Buyers” who make monthly purchases regardless of season.

These segments will help your business tailor marketing strategies to better resonate with each group.

5. Profile creation

From there, you’ll need to attribute each customer segment a detailed profile outlining their characteristics, preferences, and needs, to tell you a story about who your customers are, and what they want.

You’ll need a method to understand how your customers compare to, and what distinguishes them from, the average person. By comprehensively understanding the various customer ‘types’ based on a broad range of demographic, economic, and geographical factors, as well as population attitudes and behaviours, you can quickly transform your customer data into valuable knowledge.

Your consumer profiles will serve as a comprehensive blueprint for targeted marketing efforts and product development. For example, “Skiing Holidayers” receive early notifications about new winter arrivals and personalised recommendations for complementary accessories. “Frequent Buyers” are targeted with exclusive discounts and early access to new collections.

6. Continuous Optimisation

Customer profiling is an ongoing process that requires regular updates and adjustments. As customer preferences evolve and new data becomes available, your business should continually refine their profiles to ensure long term relevance, accuracy, and — ultimately — growth.

The Pros and Cons of Consumer Profiling

As with any marketing technique, customer profiling has its pros, but it’s not without its cons. Understanding the wider challenges associated with customer profiling can better help you plan and strategise to avoid them, or recover from them if they occur.

Advantages

Personalised marketing: By understanding your customers on a deeper level, you can create highly targeted marketing campaigns that resonate with their specific needs and preferences.

Improved customer engagement: Tailored messaging and offers increase customer engagement and loyalty, leading to higher retention rates and lifetime value.

Enhanced product development: Insights gained from customer profiling can inform product development efforts, ensuring that offerings align with customer preferences and market demand.

Optimised resource allocation: By focusing resources on high-value customer segments, businesses can maximise ROI and efficiency in their marketing and sales efforts.

Challenges

Data quality: Ensuring data quality, in terms of accuracy and consistency, across multiple sources can be challenging, leading to inaccuracies in customer profiles.

Privacy concerns: Gathering and storing customer data raises privacy concerns, requiring businesses to comply with regulations such as GDPR and CCPA. Data protection laws can differ between countries, and it’s always advisable that businesses and organisations stay informed and up to date on the laws and regulations.

Data integration: It’s important to understand that, whilst an integral component of success, consolidating data from disparate sources into a unified customer profile database is a complex process that can be very time-consuming.

Algorithm bias: Data analysis algorithms may introduce bias if not properly calibrated, leading to skewed insights and inaccurate customer profiles.

How can Sagacity help?

Sagacity specialises in data-driven psychographic insights that can be harnessed to significantly enhance customer profiling efforts for businesses worldwide. We assist in integrating data from various sources, ensuring comprehensive and accurate customer information through effective data management.

Our expertise in advanced analytics allows us to identify patterns and trends within your customer data, and predictive modelling tools help forecast future behaviours and preferences, enabling more targeted marketing strategies. We help our clients identify distinct customer segments, which allows for the creation of personalised marketing campaigns that resonate with each segment.

Plus, we ensure that all data profiling activities comply with relevant data protection regulations, emphasising:

ethical data use
protecting customer information
protecting your business

By working collaboratively with our clients, our approach includes continuous improvement, regularly updating and refining customer profiles to keep them accurate and relevant.

Conclusion

Building a customer profiling database is a foundational step towards unlocking the power of data-driven marketing. By understanding who your customers are and what motivates them, you can create more effective marketing campaigns, drive customer engagement, and ultimately, boost your bottom line.

While the process may present challenges, the benefits of customer profiling far outweigh the hurdles, making it a worthwhile investment for any business looking to gain a competitive edge in today's market.