Personalization from 360-degree Customer View: Step-by-step Guide

Today, it is common to discuss recommendation models that personalize content, customer profiles, offers, and services based on user information. This trend is largely driven by advances in data strategy and technology. Modern cloud architectures, customer recommendation engines, and single customer views (SCV) enable brands to design and implement effective personalization strategies. These strategies enhance user experience and increase the likelihood of positively impacting key metrics, such as cross-selling, average transaction value, and product usage, all contributing to improved user loyalty.

Yet, technology alone does not guarantee an impact on business indicators, and often, the development of this strategy does not deliver the expected results.

In this article, we will examine the main elements to consider when building a 360-degree customer view and learn how to create user profiles that effectively meet the end-user's needs. But first, it is necessary to understand the concept of a single or 360-degree customer view (SCV).

What Is a 360-degree or Single Customer View (SCV)?

The 360-degree customer view is a comprehensive approach consolidating data from multiple data sources and attributes to provide a holistic and enriched view of user behavior and needs. This approach enables companies to personalize customer interactions accurately and in a timely manner.

Having multiple data sources alone does not provide an accurate 360-degree view. Even if information is available, it must be coherently integrated and processed using advanced data models. Without this integration, personalization efforts based on these data sources may be incomplete, inaccurate, or fail to deliver real value.

The four steps that we must follow to build a 360-degree customer view are as follows: 

Step 1: Set business objectives

When discussing user knowledge, it is important to define our scope clearly, as this knowledge needs to be part of a consistent data strategy. The personalization approach will rely on how we gather new user data and customer information.

To define the attributes of the customer we want to understand, we must base our analysis on business objectives, such as:

• To increase the average ticket per user 
• To encourage the use of a specific product (savings, investments, etc.)
• To avoid customer churn
• To increase the use of digital channels
  

Objectives should be clear and measurable, including specific units and formulas to calculate the current status. It is also essential to establish goals and other key attributes.

Step 2: Define information sources

Once we have stated our business objectives, we need to identify the data sources that will help us assess the relevant indicators at the user level. It is crucial to consider both quantitative and qualitative data. Below are some examples of potential customer information sources:

Step 3: Perform information analysis and data modeling

Before we explore the technology, it is important to conduct a preliminary data analysis, typically carried out by a data scientist using tools like Python or R. This analysis will provide an initial outline of the 360-degree view, which needs to be validated with the relevant business teams to ensure it aligns with the business objectives.

In this step, the appropriate data models are identified. A personalization strategy typically includes recommendation and segmentation models that create customer profiles aligned with business goals.

There are tools with pre-trained algorithms that must be used carefully, as not all data fits into X or Y algorithms effectively.

Some algorithms commonly used in a 360-degree customer view (SCV) include:

Step 4: Align with data governance and technology enablement

Once we have an initial 360-degree customer view (SCV), which can be displayed on a dashboard and validated by the loyalty and marketing teams, we need to select the best technology based on the availability and type of customer data.

To begin, we should leverage existing resources. Starting from scratch can often lead to unnecessary costs and rework. To avoid this, we need to design the solution with the following considerations:

• Alignment of the need with the current data governance strategy to ensure best practices in its implementation
• Technology selection based on costs vs. impact supported by cloud data architecture or pre-built tools designed for experience personalization.
• Formation of an implementing team and preparation of an evolutionary work plan
  

In summary, a general scheme that encompasses our previous points would be as follows:

Built knowledge comes to life through user interaction channels and platforms

Creating a comprehensive 360-degree view of the customer is just the first step. To truly enhance user experience, this data must be organized and integrated with the platforms that users actively engage with. Without these integrations, the 360-degree view and customer profiles will serve only for data analytics, rather than improving the user experience. To foster greater loyalty, here are some essential integrations to consider:

• Communication: Email, SMS, and digital advertising
• Service: CRM and contact center applications
• Physical offices for preferential treatment of gold customers (for example)
• Mobile applications and portals for experience personalization
  

At Pragma, we have assisted several companies in developing their data-driven experience personalization strategies. The most significant lesson we have learned is that every business, sector, brand, and customer is unique. Therefore, it is crucial to create a thoughtful strategy that takes all these factors into account to ensure its success.

Pragma has been accompanying its partners for years in building their personalization strategies through 360-degree ​​customer views. Discover our success stories with Comfama, Dislicores, and Familia.