Data Science

Understanding Single Customer View for Improved Marketing Strategies

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By Pere Munar, on 2 April 2024

The single customer view is a record that stores data about each individual customer a company has and allows you to create better digital marketing and sales strategies, enhancing results, and providing consumers with what they need.

The data stored in the single customer view originates from various sources, from information provided directly by the customer to data collected by the company by monitoring the customer's journey.

Three of the main characteristics of the single customer view are that it is comprehensive, holistic, and precise, gathering demographic, behavioral, and transactional data.

In essence, the single customer view is a resource that enables businesses to store customer information systematically and to create effective strategies.

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Understanding Single Customer View for Improved Marketing Strategies


Advantages of Using the Single Customer View in Marketing

Marketing, sales, customer service, and data analysis teams can all benefit from using the single customer view tool. Here's how:


Personalized Strategy Creation

Having clear data on all customers compiled in one place helps companies create more tailored strategies to meet individual consumer needs. This goes beyond basic personalization like using the customer's name in emails or newsletters; it involves sending emails with different content to each user based on the pages they have visited on your website, among other aspects.


Boosting Sales and Customer Loyalty

Creating a more personalized marketing strategy greatly helps companies in their efforts to increase sales and enhance consumer loyalty.

Customer Segmentation Ease

A resource like the single customer view makes customer audience segmentation processes easier and more accurate by providing experts with a clearer view of each customer's needs.


Data Regulation Compliance

Data privacy is crucial for businesses, especially with the multitude of regulations, particularly in Europe. With resources like the single customer view, companies can more easily comply with data privacy regulations and individual customer consents and preferences.


Enhancement of Multichannel and Omnichannel Experiences

Improving multichannel or omnichannel experiences is highly recommended today. However, one challenge companies face is the quality and consistency of the data collected. A single customer view helps companies organize customer data to avoid confusion. Additionally, information is more accessible and contextualized within each customer's profile, rather than isolated or scattered across multiple sources.


Quicker and More Accurate Responses

With comprehensive and centralized customer data in the single customer view, customer service experts know each customer's history when they contact the brand to solve a problem or inquire about anything. Thus, they can provide a much faster and tailored response to their needs.


Creating a Single Customer View Step by Step

Now that you understand what a single customer view is and the benefits it can bring to your company, let's look at how to implement this method in your organization. Here's how to create your own single customer view with simple steps.


1. Select a Customer Data Platform

The first step is to choose the customer data platform that best suits your company. A customer data platform is software that collects, stores, and organizes customer data from all sources (both online and offline) in real-time.


2. Choose Different Data Sources

Once you've selected your customer data platform, it's time to choose the different sources from which you want the tool to gather information.


3. Consider Hiring a Data Professional

Data science professionals are valuable resources within companies as data analysis is not an easy task. They can maximize the use of customer data platforms and interpret the information found in each single customer view to improve strategies.


4. Provide Access to the Platform for All Teams

Even if you have a data professional managing the customer data platform, it's beneficial for different teams in your company to access the tool and view customer data. This allows specialist teams to analyze and identify errors and successes in their strategies and propose new ways of working.


What Type of Data Does the Single Customer View Collect?

Typically, the following data is found in the single customer view:

  • Demographic Data: Including age, nationality, profession, ethnicity, education, gender, or income, among others.
  • Personal Data: Usually obtained through CRM systems, including email addresses, postal addresses, phone numbers, or social media profiles.
  • Customer Behavior Data: Includes pages visited, time spent on each page, interactions, products added to the cart, as well as interactions on social media profiles, emails, newsletters, and ads.
  • Transactional Data: Information related to customer purchases, including the quantity and value of products purchased, purchase date, number of returns, and cart abandonment.
  • Preferences and Consent: Customer consent regarding data usage varies, and it's crucial to respect preferences and to comply with regulations in order to avoid legal issues. Single customer views also provide information on customer consent and preferences regarding data.
  • Interaction Data with Sales and Customer Service: Reflects customer interactions with sales and customer service professionals, including how they contacted the customer service team, the reason for contacting them, and the sales process.

In conclusion, a single customer view is a comprehensive resource that gathers a wealth of data that is important and useful for building a personalized strategy for each consumer and deeply understanding each customer. We highly recommend implementing it so that all your customer information is organized and centralized, thus avoiding time losses when trying to find specific data and errors due to missing information.

Data science consulting with Cyberclick

Pere Munar

Data Scientist en Cyberclick. PhD en Astrofísica por la Universitat de Barcelona con más de diez años de experiencia en investigación mediante el análisis e interpretación de datos. En 2019 redirige su carrera profesional hacia el mundo del Data Science cursando el Postgrado en Data Science y Big Data de la UB, así como participando en el programa Science To Data Science (S2DS) en Londres. Actualmente forma parte del equipo de Data Science y SEM de Cyberclick.

Data Scientist at Cyberclick. PhD in Astrophysics from the University of Barcelona with more than ten years of research experience through data analysis and interpretation. In 2019 he redirected his professional career to the world of Data Science by graduating in Data Science and Big Data from the UB, as well as participating in the Science To Data Science (S2DS) program in London. He is currently part of Cyberclick's Data Science and SEM team.