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.
Marketing, sales, customer service, and data analysis teams can all benefit from using the single customer view tool. Here's how:
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.
Creating a more personalized marketing strategy greatly helps companies in their efforts to increase sales and enhance consumer loyalty.
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 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.
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.
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.
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.
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.
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.
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.
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.
Typically, the following data is found in the single customer view:
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.