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Foundations of Bloomreach Engagement Data Structure

Foundations of Bloomreach Engagement Data Structure

What Is Bloomreach Engagement?

Bloomreach Engagement works as a Customer Data and Experience Platform (CDXP). You can use it to collect, manage, and activate customer data for personalized marketing and communication. This platform lets you gather information from different sources, create detailed customer profiles, and automate how you connect with people across various channels. Its design allows you to easily adjust and expand your use of data to meet changing digital marketing demands.

Overview of Core Data Elements

The data structure in Bloomreach Engagement centers on four main elements:

  • Customers: These represent each visitor or user who interacts with your business. A customer profile collects all related data, including identifiers like email addresses or internal IDs, personal details such as first and last names, and linked devices. All other data types connect to these customer profiles, making them the central point in the platform.
  • Events: Events record every action a customer takes, whether online or offline. For example, you might track when someone views a product, completes a purchase, or signs up for a newsletter. Each event includes details like the time it happened, the type of action, and any other related information.
  • Catalogs: Catalogs work as reference tables that store organized details about items such as products, articles, or services. Every catalog entry has a unique identifier and descriptive features like name, price, or category.
  • Vouchers: Vouchers contain codes and related data used for promotions or rewards. These can link directly to customers and include rules such as when they expire or how many times they can be used.

How Data Is Stored: NoSQL Structure Explained

Bloomreach Engagement uses a NoSQL, schema-less database model to store data. This approach is different from traditional relational databases, which use fixed tables and columns. In a NoSQL structure, you can store information in a flexible way. Each type of data—whether a customer, event, catalog item, or voucher—can have its own set of attributes, and you can add or change these attributes without needing to redesign the database.

You can picture this system as a set of folders. Each folder stands for a data group, such as customers, events, catalogs, or vouchers. Inside each folder, you store documents that hold the details you choose, and you can add new types of information as your needs grow. There is no set template for these folders. This flexibility lets you quickly adjust to new data types and combine different pieces of information into a single customer profile.

This way of organizing data helps you capture, store, and connect all kinds of customer information. You can build detailed customer views and use the data for more informed and effective marketing activities.

Customer Profiles and Attributes

Structure of Customer Data

Bloomreach builds customer profiles that give you a complete digital picture of each person who visits your website or uses your mobile app. Each profile focuses on the individual, which helps you engage customers based on their specific needs and actions. The platform keeps customer data up-to-date and stores it over time. This means you can always access a clear and current view of each person, even if they use different devices.

Identifiers and Attributes

Every Bloomreach customer profile starts with a unique identifier. At first, when someone visits your site, they appear as an anonymous user. The system uses a browser cookie to recognize them during their visit. If the visitor logs in, makes a purchase, or provides information, Bloomreach assigns a “hard ID.” This hard ID could be an email address, your company’s customer ID, or any unique value. Using this hard ID, Bloomreach connects data from different devices and sessions. As a result, you see one complete profile for each customer.

Profiles gather many types of information, called attributes. Some common attributes are first_name, last_name, and email. You can also collect custom details that fit your business goals. Attributes may include demographic information like age or location, behavioral data like the last visit date, or preferences such as favorite product categories. This approach lets you personalize marketing and analyze customer behavior effectively.

Real-World Example

Let’s look at a profile for a customer named Jane Doe. Her profile could include:

  • Unique identifier: janedoe@email.com
  • First name: Jane
  • Last name: Doe
  • Preferred language: English
  • Loyalty program status: Gold
  • Last purchase date: 2024-05-12

With these details, Bloomreach Engagement allows you to send Jane personalized messages, suggest products she may like, and follow her interactions across different channels. This makes sure Jane’s experience feels personal and consistent, no matter how or where she connects with your brand.

Events and Behavioral Data

What Are Events?

In Bloomreach Engagement, events record every action a customer takes with your business. These actions include things like clicking a button, viewing a product, or making a purchase online. You can also include offline activities by importing them into the platform. Events provide detailed behavioral data. With this data, you can analyze how people use your site, group them into segments, and create actions based on specific behaviors.

Event Data Structure

Each event in Bloomreach Engagement contains several attributes that give you context and details about the action. The main fields are:

  • Event Name: A label that tells you what type of action happened, such as view_item or purchase.
  • Timestamp: The exact time when the event took place.
  • Associated Customer: The unique customer who performed the action.
  • Event Attributes: Up to 255 custom fields with extra information. These can include product ID, category, cart value, quantity, or device type.

This schema-less or NoSQL structure gives you a lot of flexibility. You can decide which events and attributes you want to track. This setup lets you collect many types of data for analytics and marketing campaigns, without needing to fit everything into a strict database format.

Use Case Example

Let’s look at the view_item event. When a customer views a product, Bloomreach records this event with details such as:

  • Event Name: view_item
  • Timestamp: 2024-04-23T15:27:10Z
  • Customer ID: john.smith@email.com
  • Attributes: { "product_id": "A123", "product_name": "Blue Sneakers", "category": "Shoes" }

By collecting and reviewing these events, you can see which products customers look at most often. You might group customers who browse “Shoes” into a segment. You can then set up automated marketing, such as sending a reminder email to someone who viewed a product but did not buy it.

Bloomreach events data gives you the detailed information you need to personalize engagement. With this data, you can respond to customer actions as they happen.

Catalogs and Product Data

Introduction to Catalogs

Bloomreach catalogs work as organized lookup tables where you keep detailed information about products or other business-related items. Each catalog entry has a unique primary key known as item_id. You can use catalogs to manage products, make recommendations, and track inventory efficiently on the platform. Catalogs also help you link detailed product information with the customer experiences you want to create.

Catalog Structure and Linking

Bloomreach Engagement uses two main types of catalogs: general catalogs and product catalogs. Product catalogs are designed for e-commerce and include key fields such as item_id (which identifies a specific product variant), product_id (which refers to the main product), title, description, brand, category_ids, price, and stock_level. You can also add details like color, size, image URL, and availability. This setup lets you identify each product clearly and add useful information to it.

Catalogs connect with other data in the system using shared identifiers. For example, when a customer views a product, the event data will include the item_id from the product catalog. This lets Bloomreach personalize product recommendations and keep track of how customers interact with products.

Example Catalog Use Case

Here is an example of a product catalog entry:

  • item_id: 12345-XL
  • product_id: 12345
  • title: Black Fitted Crew Neck T-Shirt
  • brand: ExampleBrand
  • category_level_1: Tops
  • price: 19.99
  • stock_level: 120

This setup lets marketers quickly find product information for personalized marketing. You can show customers the items they viewed last, or manage inventory across different sales channels. The catalog does not store any personally identifiable information, which helps keep customer data safe.

Vouchers and Incentives

Role of Vouchers in the Data Structure

Bloomreach vouchers are special codes that give customers discounts or special offers. Inside Bloomreach Engagement, vouchers work as a separate part of the data system. This setup lets you distribute, track, and manage rewards right inside your marketing campaigns. You can create groups of vouchers, called voucher pools, and organize them by campaign or offer type. This organization helps you control and review your promotional activities more closely.

Voucher Data Structure

Every voucher in Bloomreach Engagement uses specific fields:

  • Code: This is the unique text string a customer uses to get a reward.
  • Status: This field shows if a voucher is available, assigned to someone, or already used.
  • Voucher Pool Name: This groups vouchers by campaign or discount type, making it easy to find and manage them.
  • Expiration Date: This optional field tells you when the voucher will stop working.
  • Assignment Tracking: This keeps a record of when and to whom a voucher was given.
  • Usage Tracking: This records when someone uses a voucher, helping you collect data for reports and analysis.

These fields let you handle a large number of vouchers quickly. You can assign vouchers automatically and see their status in real time.

Example Incentive Program

Imagine a retailer starts a spring sale and creates a voucher pool called “SPRING10.” This pool includes single-use codes that each give 10% off. During an email campaign, each customer gets their own unique code from this pool. The system tracks which customer receives which code and marks codes as used once they are redeemed. This process keeps offers limited to each customer and lets you measure the results clearly. With this method, you can run focused and data-driven incentive programs using Bloomreach vouchers.

Data Relationships and Interactions

Linking Customers, Events, Catalogs, and Vouchers

In Bloomreach Engagement, four main types of data—Customers, Events, Catalogs, and Vouchers—work together to give you a clear view of each person and help you create marketing that feels personal. Customers sit at the center. Every interaction, transaction, or campaign incentive always connects back to a specific customer profile. Events track what a customer does, such as viewing a product or using a voucher, and each event always links to the customer’s unique ID. Catalogs hold information about products or content that events reference. Vouchers act as incentives that you can give to customers and track across their journey.

These elements connect to build a detailed map of customer actions and show how marketing works in real time. For example, if a customer uses a voucher to buy a product, the voucher redemption event captures the customer ID, the voucher code, and which catalog item was purchased. All this information links together. This way, you can see exactly who used an offer, which products were involved, and how each person reacts to different incentives.

Practical Examples of Data Connections

Imagine a customer views a product from the catalog (event), receives a custom voucher, and later buys the product using that voucher. Each action—viewing the product, getting the voucher, and redeeming it—creates a separate event tied to the same customer ID. The catalog adds product details to these events, and voucher information tracks how the incentive is used. This linked data setup lets you follow a customer’s journey, start relevant campaigns, and adjust your approach using a complete, connected view of engagement.

When you use these relationships in Bloomreach, you can target offers to the right people, measure how well campaigns perform, and improve personalization—all by working within a single, organized data system.

Data Management Tools in Bloomreach Engagement

Overview of Key Tools (Data Manager, Asset Manager)

Bloomreach Engagement offers specific tools to help you organize and keep your data accurate. The Data Manager lets you directly control customer and event properties. You can add new data, edit existing entries, or remove attributes as your business changes. You also have options to group and reorder these properties, making the system easier to use. When you work with sensitive information, you can label certain fields as personally identifiable information (PII). The Data Manager also allows you to map events and attributes, so the platform can always recognize them in the same way.

The Asset Manager works as a central storage space for your marketing templates and content assets. Here, you can keep templates for emails, SMS messages, web layers, HTML blocks, and custom rows. This setup helps your team maintain a consistent brand look and makes it easier to launch new campaigns.

Managing and Updating Data

These tools help you keep your data well-organized and accurate in Bloomreach Engagement. With Data Manager, you can quickly update data fields, monitor data accuracy, and follow privacy rules by marking PII. Asset Manager gives you easy access to content pieces you use often, which lowers the chance of mistakes and makes sure your campaigns always use the correct and approved materials. Using both tools together helps you build a strong and dependable system for managing data in the platform.

Real-World Applications and Best Practices

Using Data Structure for Personalization

With Bloomreach Engagement’s data structure, you can design targeted marketing campaigns by connecting customer profiles, behavioral events, product catalogs, and incentives. For instance, when you combine a customer’s detailed purchase history with product catalog information, you can suggest products that match previous interests. Tracking event data lets you respond to customer actions in real time. As you update and segment customer details and preferences, your personalization becomes more accurate. This approach often leads to better customer engagement and higher conversion rates.

Data Quality and Maintenance Tips

You need to keep your data accurate and up to date. Regularly review customer and event data with tools like Data Manager. Look for errors in data types, incorrect formatting, and outdated information. Always use the correct formats for numbers, dates, and phone numbers. For phone numbers, use the E.164 standard to ensure global compatibility. Filters can help you quickly find and fix problems, such as dates stored as text or phone numbers in different formats. Make sure all new data matches your defined types, and use automated scenarios to correct any errors quickly. Keeping your data clean helps you personalize campaigns effectively and supports the overall performance of your marketing activities in Bloomreach.