Customer data: extracting value from the company’s information assets with BI

Customer Data Business Intelligence


What are Customer Data

When we talk about “customer data,” we refer to the information collected by companies about their customers. These data can include personal details, purchase information, online browsing behaviors, preferences, feedback, and more.

“Customer data” is crucial because it enables companies to personalize and enhance their customers’ experience, develop products and services more in line with users’ needs and preferences, and optimize marketing and sales strategies. Having access to detailed customer data helps companies make more informed decisions, increase the efficiency of advertising campaigns, and ultimately increase customer satisfaction and loyalty.

Customer data and Advanced Analytics

In this context, it is therefore essential for companies to adopt a Business Intelligence solution based on Advanced and Predictive Analytics. This allows them to transform the vast amount of available data (big data) into valuable and immediately actionable insights capable of generating a positive impact on the business, whether it’s cost reduction, process optimization, revenue increase, or any other strategic and/or operational decision.

What Customer Data is available in a company?

Any company has a wealth of information collected about its customers. While this data may be partially organized and available as individual data, it expresses its full potential when integrated with information from various business departments (whether it be finance, operations, sales, or others). In an even more competitive scenario, this data can be integrated with information from external sources (geographical data, movement forecasts, flows, new consumption trends, interaction habits, and so on).

Basic customer data, which every company can access, includes a wide range of information such as:

  • Personal Data: Name, address, phone number, email address, and sometimes more sensitive data such as social security number or financial data.
  • Demographic Data: Age, gender, education level, marital status, income, etc.
  • Behavioral Data: Previous purchases, product or service preferences, website browsing habits, responses to marketing campaigns.
  • Transactional Data: Purchase history, payment details, order history, returns, complaints.
  • Feedback and Preferences: Customer opinions, product preferences, feedback on services or purchasing experiences.
  • Interaction Data: Records of interactions with customer service, notes on calls, emails, social media interactions.
  • Usage Data: How customers use a product or service, including data collected from software or smart devices.

It is important to note that the collection and use of this data are regulated by various privacy and data protection laws, such as GDPR in Europe, to ensure that personal information is handled securely and responsibly.

Tools for collecting Customer Data

The most common tools for collecting customer data include:

  • CRM (Customer Relationship Management) Systems: These systems are designed to manage interactions with current and potential customers. Famous examples include Salesforce, HubSpot, and Zoho CRM. They allow companies to collect, organize, and analyze customer data, from contact information to transaction details.
  • Web and Mobile Analytics Platforms: Tools such as Google Analytics, Adobe Analytics, and Mixpanel provide detailed data on user behavior online, such as time spent on the site, pages visited, and interaction with specific content or ads.
  • Email Marketing Software: Platforms like Mailchimp, Constant Contact, and Sendinblue allow companies to collect customer data through email subscriptions, monitor interactions with sent emails (such as opens and clicks), and segment users based on their behavior.
  • Survey and Feedback Tools: Tools like SurveyMonkey, Typeform, and Google Forms are used to collect feedback, opinions, and preferences directly from customers.
  • Social Media Analytics Tools: Platforms like Hootsuite, Sprout Social, and Buffer offer detailed analysis of social media interactions, allowing companies to monitor mentions, engagement, and follower demographics.
  • POS (Point of Sale) and E-commerce Platforms: Platforms like Shopify, WooCommerce, and Square collect transactional and behavioral data from customers during the purchase of products or services.
  • Customer Service Management Software: Tools like Zendesk and Freshdesk record interactions with customers through various channels, such as email, chat, and phone calls.
  • ERP (Enterprise Resource Planning) Systems: These systems integrate various aspects of business management, including customer data collection, into a single system.

In such a fragmented landscape, where many different tools are dedicated to the individual collection and analysis of data, it is essential to adopt data integration processes, so as to obtain a single set of consistent information that can be related in a simple and intuitive way, acquiring greater meaning and strategic value for the business.

Driving Your Customers' Journey

The customer journey describes the path taken by a customer from becoming aware of a product or service to purchase and beyond. It includes all interactions and experiences of the customer with the brand, divided into different stages such as awareness, consideration, decision, purchase, and loyalty. Understanding the customer journey is essential for those companies that have adopted the philosophy of “customer centricity,” i.e., placing the customer at the center of the entire business strategy.

To analyze the customer journey, companies use metrics such as:

  • Conversion rate (how many people have taken a desired action)
  • Time spent on the site
  • Bounce rate (how many visitors leave the site after viewing only one page)
  • Customer Lifetime Value (CLV, the total value a customer represents to the company over time)
  • Net Promoter Score (NPS, which measures the likelihood that customers will recommend the company’s products or services).

These metrics help companies understand the effectiveness of marketing and engagement strategies. Moreover, companies can leverage knowledge of the customer journey to improve the customer experience at all touchpoints, personalize communications and offers, identify and remove purchase obstacles, and develop targeted strategies to increase loyalty and customer value over time, thus optimizing conversions and overall customer satisfaction.

Customer Journey

Customer Data Platform (CDP)

The first step for companies looking to harness the strategic value of customer data is the adoption of software systems that collect, organize, and activate customer data from various sources: known as Customer Data Platforms or CDPs.

CDPs work by aggregating and integrating information to create a unique and accessible customer profile. Among the most popular are solutions such as Adobe Real-Time CDP, Salesforce Customer 360, Segment, Tealium AudienceStream, and Oracle Customer Data Management. These platforms offer advanced features, supporting companies in creating personalized and targeted user experiences.

However, to fully exploit the hidden value of customer data, CDPs can be integrated with other Business Intelligence platforms through the adoption of customized solutions.

Business Intelligence solutions for Customer Data Strategy

Business Intelligence solutions are, in every respect, the essential tool for guiding a Customer Data-driven corporate strategy to increase consumer benefits and grow business profits.

Adopting BI platforms such as Tableau, Power BI, QlikView, and Dataiku enables easy integration of Customer Data Platform data, extracting meaningful information from customer data through interactive and intuitive dashboards.

Custom solutions like those developed by BlueBI allow companies to invent new significant KPIs to monitor and derive valuable and unprecedented insights. Furthermore, through the integration of virtual assistants, chatbots, and mixed reality systems, they enable even simpler and more immersive data exploration using natural language and virtual reality.

We realize Business Intelligence & Advanced Analytics solutions to transform simple data into information of freat strategic value.


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