Explore your multi-brand sample project

Sample project for the app

The sample app displays data from the Sample Project that demonstrates Kontent.ai best practices for multi-brand companies. The content of the Sample Project is based on a fictional health technology company called FictoHealthtech. The company consists of 3 brands, each with its own website.

• Ficto Healthtech is the base page with the fundamental information about the company. It also points to the remaining two sites.
• Ficto Surgical is the site with the catalog of the products the company offers. It shows articles from the Ficto Healthtech world.
• Ficto Imaging is the last of the sites. It describes the company's research and unique solutions like MRI machines and PET scanners.

These sites are already deployed. Feel free to explore them!

Making changes to your project

We recommend you take our Walkthrough for content creators. You'll get familiar with content items and learn how to find content in your project quickly. Let's edit a title of the homepage in Web Spotlight.

1. In Kontent.ai >  Web Spotlight, click on the right of the main heading. This opens a content item behind the content you clicked.
2. Create a new version of the content item.
3. Make a change in the content item. For example, edit the Title text or another element. After a few seconds, you'll see the changes in Web Spotlight.
4. Publish the changes to see them in the sample app.

Explore the content model

When you click through the content item in Web Spotlight, you can find guidelines with details about each content type. Let's check how the project's content is modeled and organized in more detail.

Differentiating between brands and their websites with collection and spaces

Spaces provide a channel-specific context for your content. Each space represents the context for one brand from the Ficto Healthtech company. The content items and assets are also divided into collections. There are 4 collections in total – every company's brand has its collection and additionally, there is a common collection that stores the content reused on multiple sites. The collections bound content to your business needs and they can serve as a filter when working with content items.

How the content is modeled

The content types in the Sample Project are distinguished with emojis:

• 💡 marked content types are Web Spotlight root and Page. These are related to Web Spotlight, and were automatically created after enabling Web Spotlight. They were extended with an element that defines the website's navigation menus.
• 🧱 marked content types represent building units used to create the landing pages for websites.
  • Content chunk is for rich text content.
  • Visual container is for content rendered in a specific visual format such as hero image, grid, or stack.
  • The building units can be used only within the💡marked types.
• 🧩 marked content types are used as components in rich text elements.
• 🧭 marked content types represent content for creating the menu on the web page.
• No emoji content types store the actual content that can be reused across all channels.

Reusing parts of content model

When content types share common elements, content type snippets come in handy. The Sample Project uses snippets for extracting shared guidelines used in the emoji content types. This creates a single source of truth for content type metadata.

Tagging content with taxonomies

The Sample Project shows two main use cases for taxonomies:

1. Internal categorization – this can help simplify filtering among the content item inventory. For this case, you can look at the Fact type taxonomy. 
2. Defining the type of the structure – for example, Article type defines whether an article is a research paper or industry news.

Summarized