Crafting Comprehensive User Profiles - Part 3/3

Dec 25 / Parth Patel & Siddarth R
We started this blog series by describing in detail a common and critical problem that a lot of businesses deal with, which is understanding and managing multiple profiles created by the same user.

Following this in the second blog, we enumerated numerous key business metrics that companies track based on their domain and how having an inflated idea of your true user can impact these metrics and lead to a false understanding of the business performance. In this blog, we will discuss User Profiles in much more detail to give you a comprehensive understanding of what it consists of and what are the various sources that business taps in to build a User Profile.
User profiles are the cornerstone of personalized experiences in today's digital age. They enable product companies to tailor their offerings and marketing strategies to individual users, ultimately enhancing user satisfaction and increasing the chances of conversion.

Building effective user profiles is a multifaceted task that requires a deep understanding of data collection and analysis. In this blog post, we will explore how different product companies create user profiles in their data warehouses. We will also delve into the attributes that make up a user profile, and the balance between sourcing these attributes internally from company data and externally from various data sources.

Understanding User Profiles

User profiles are a collection of data points and characteristics that provide a detailed representation of an individual user. These profiles go beyond just basic demographics; they encompass a wide range of attributes that help companies understand their users' preferences, behaviors, and needs. By analyzing user profiles, companies can make informed decisions about product development, marketing strategies, and customer support.
A comprehensive user profile can include a diverse set of attributes, which can be broadly categorized into the following:

1. Demographic Information: 

This includes basic details such as age, gender, location, and occupation. While these attributes provide a foundational understanding of users, they are just the tip of the iceberg.

2. Behavioral Data:

Behavioral attributes encompass user interactions with the product or platform. This may include the frequency and duration of usage, features utilized, and the sequence of actions taken.

3. Preferences and Interests:

Knowing what users like and dislike is crucial. This can be inferred from their interactions, stated preferences, or explicit selections of categories or topics.

4. Purchase History:

For e-commerce and retail companies, tracking what users have purchased in the past is valuable. This can include the type, quantity, and frequency of purchases.

5. Communication Preferences:

Understanding how users prefer to receive communications (email, push notifications, SMS, etc.) and the frequency they find acceptable can improve engagement and satisfaction.

6. Device and Platform Information: 

Knowledge of the devices and platforms users engage with helps tailor the user experience. This includes the type of device (mobile, desktop, tablet), operating system, and browser.

7. Geographic Data: 

Users' location can influence their needs and preferences. This attribute can be sourced internally or externally, depending on the level of precision required.

8. Usage Patterns: 

Tracking when users are most active, when they are inactive, and any seasonality in their behavior can inform product updates and marketing strategies

9. User-generated Content:

For platforms with user-generated content, attributes like reviews, comments, and content creation history are critical.

10. Feedback and Reviews:

Collecting user feedback and reviews on products or services can help in gauging customer satisfaction and making improvements.

11. Customer Support Interactions:

Information about users' interactions with customer support, including the nature of issues and resolutions, can provide insights into common pain points.

12. Social Media Activity:

For companies that integrate with social media platforms, data on users' activity and connections can be invaluable.

13. Third-party Data:

External data sources, such as data providers, can contribute data on income, household composition, education, and more, enriching user profiles.

Internal vs. External Data Sources

The process of building user profiles relies on a combination of internal and external data sources. Let's explore the advantages and limitations of both.

Internal Data Sources:

1. First-party Data:

This is data collected directly from users through their interactions with the company's products or services. It's often considered the most valuable because it reflects user behavior on the platform. Examples include purchase history, interaction logs, and user-generated content. 

2. Customer Relationship Management (CRM) Data: 

CRM systems store valuable customer data, including contact information, purchase history, and support interactions. Integrating this data into user profiles can help in creating a 360-degree view of the customer.

3. Data Analytics:

Data analytics tools help in extracting insights from user data. This includes tracking user behavior, identifying patterns, and segmenting users based on their interactions. 

4. User Surveys and Feedback

Companies can proactively gather information by asking users to fill out surveys or provide feedback. This is a direct way to acquire preferences and interests.

5. User Account Information:

Account creation or sign-up forms can collect basic demographic information such as name, age, and location.

External Data Sources:

1. Third-party Data Providers:

These are external companies that aggregate and sell data about individuals. They may provide information on income, household composition, education, and more. This external data can enrich user profiles, but it's important to ensure compliance with privacy regulations.

2. Social Media Data:

Data from social media platforms can be a goldmine of information, including interests, connections, and user-generated content. APIs offered by platforms like Facebook and Twitter allow companies to access this data.

3. Geolocation Data:

External sources provide geolocation data for users, which can be used to enhance geographic information in user profiles. 

4. Market Research:

Data from market research firms can provide insights into user preferences, market trends, and competitive analysis.

Balancing Internal and External Data Sources:

The balance between internal and external data sources varies depending on the industry, business model, and data privacy regulations. Here are some considerations:

1. Data Privacy and Compliance: 

Strict data privacy regulations like GDPR and CCPA have led companies to rely more on their internal data sources, as using external data requires careful compliance measures.

2. Data Quality: 

First-party data is generally considered more accurate and reliable. Internal data is often the primary source for building user profiles, with external data used to enrich the profiles.

3. Data Enrichment:

External data can help fill gaps in user profiles, providing a more holistic view of users. This can be especially valuable for companies that have limited first-party data.

4. Cost Considerations:

Acquiring external data often comes with a cost. Companies must weigh the cost of external data against the potential benefits it brings to user profiling.

5. Data Integration: 

Efficiently integrating external data into internal systems can be a challenge. Data pipelines and data governance processes need to be in place to ensure seamless data integration.

Conclusion

Creating comprehensive user profiles is an essential part of the modern product company's toolkit. These profiles allow for personalized user experiences, targeted marketing, and informed decision-making. The attributes of a user profile range from basic demographics to behavioral patterns, preferences, and interactions. Companies rely on a combination of internal and external data sources to build these profiles, with the balance depending on factors such as data privacy, data quality, and cost considerations.

In a world where data is becoming increasingly valuable, mastering the art of user profiling is a key differentiator for product companies. As technology and data collection techniques continue to evolve, it's important for companies to stay updated and adapt their user profiling strategies accordingly. This adaptability, combined with a commitment to ethical data practices, will enable companies to better serve their customers and stay competitive in the market.

About the authors

Parth Patel
Prinicpal Data Scientist at
Elevance Health
As a data scientist with 8+ years of experience, I have a strong track record of using data-driven approaches to solve complex problems and drive business growth. I have expertise in a wide range of data science tools and techniques, including machine learning, statistical modeling, data visualization, and big data technologies.
Siddarth R
Lead Data Scientist at
Microsoft
Siddarth has 19 years experience across Tech and Healthcare. He currently works as Principal Data Science Manager at Microsoft. He is leading a team of data scientists and engineers to deliver strategies for optimization.
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