Sitecore Content Hub is a world-class platform for centralizing and managing content across various channels. It helps businesses organize and streamline often chaotic, messy content operations. It does this by providing an architecture or schema for content and its interconnections. A schema defines how different types of assets are structured, organized, related to each other.

What is the basis of that architecture? I struggled with understanding completely when I first began with DAMs. So, hopefully, the following concepts I’ve put into more understandable terms will help make Content Hub’s data model clear for you:

• Entities: A distinguishable object or concept. A person, a product, a company, a brand. These are the core items in the system.
• Relations: Connections between entities. How entities are related to each other.
  • Parent-Child relation: two entities where one entity, The Parent, holds a hierarchical position higher than that of its related entity or entities, The Child or Children. The Child is dependent on the Parent.
• Cardinality: Cardinality is the number instances of an entity that are connected to another entity. It’s the nature and scope of the relation.
  • Cardinality types
    • One-to-one: One item connected with only one other item.
      • Simple example: Mike has a BMX bike, and he owns no other bikes.
      • Real world example: A bicycle has one specific product image used across all marketing materials.

• • • One-to-many: One item connected with multiple items.
      • Simple example: Mike has a BMX bike, a mountain bike, and a ten-speed bike.
      • Real world example: A bicycle brand, Cool Cycles, has images, videos, and spec sheets used across all marketing materials.
    • Many-to-many: Multiple items connected to multiple other items.
      • Simple example: Mike, Spike, and Ed have bikes. Mike sometimes rides Spike’s bike, Spike sometimes rides Ed’s bike, and Ed sometimes rides Mike’s bike.
      • Real world example: Cool Cycles has a summer marketing campaign sharing a video from another summer marketing campaign, and both campaigns are sharing images with multiple Q3 campaigns.

All of these interconnected elements create a robust framework for organizing and managing content in a scalable, efficient way, bringing order to content chaos.

Let’s test a button color! I hear this a lot with clients. While that can sometimes be a valid beginner AB test, your web designer and UX specialist likely chose the current color based on years of sound research. That likely makes it an unfavorable candidate for a good test.

So, what makes a good test then? What’s the secret sauce?

The Attributes of a Good AB Test

It Tests a Component/Page that Influences Conversion

A conversion is quantifiable and definitive, providing concrete data on whether the change positively or negatively impacts user behavior and outcomes – and potentially revenue.

It is User-Centric

Make sure your tests deliver value to the user’s experience. Create a test based on site analytics, heatmaps, user testing, and other tools to ensure your test aims to improve a user painpoint, and they will reward you with increased engagement and leads – or a lesson in what they do not want. Even a failed test has value.

It Has an Adequate Sample Size

Your test needs enough visitor traffic to hit statistical significance. Check your analytics and ensure you are testing a high-traffic page or collaborating with marketing to find a page that will drive campaign traffic. Setting up your AB tests with a confidence level of 90-95% is recommended. Without adequate traffic, your test will take significant time to hit the above 90% milestone – or it may not at all. The larger your sample size, the more you can trust the results. Many testing tools will calculate this for you and provide an estimate for how many hours or days the test will take to complete. If you want to manually determine what sample size you need for a particular test, there are many calculators online, including Sample Size Calculator (Evan’s Awesome A/B Tools) (evanmiller.org).

It is Easily Configurable

This is for those who want to keep things as easy as possible. Consider whether a content author can test the element requested by the business. If a developer is required to configure the test, it may take additional time to get through the development workflow. If the test is difficult to set up, it may be a more efficient use of time to pivot to a more straightforward test that may yield results with similar takeaways. It’s more about what you are trying to learn about your visitors.

It is Run at the Right Time

Choosing your test date could be just as important as the others. Running a test during a time with a seasonal increase in traffic could create false confidence that can’t be replicated in other months.

Follow these suggestions, and you’ll be on the right track towards better tests and a more effective website!

A Hypothesis is important for understanding what you are trying to prove with your A/B test. A well-formed hypothesis acts as a test guide.

A hypothesis is going to challenge an assumption you have about your website’s performance and/or visitor behavior. What is the assumption you want to validate as right or wrong?

Ask yourself these questions when coming up with your test hypothesis:

• What assumption are you addressing? Is there data to support your assumption?
• What solution are you proposing to address the challenged assumption?
• What is the anticipated outcome of your challenge? What metrics will be impacted if you make the specific change?

Asking those questions will help us ensure the hypothesis is S.O.U.N.D.:

Specific – the hypothesis should clearly define the change that is being tested.
Objective – while the test is proving or disproving an assumption – that assumption should be based upon actual insights – analytics, industry research, or user feedback for example.
User-focused – the hypothesis should address a user pain point. Focusing on user experience will increase test engagement and result in better outcomes.
Needs-based – the hypothesis should address a business need. Spend time on tests that will bring value to the business as well as the user. Keep ROI front of mind.
Data-driven – always make sure the hypothesis has measurable metrics and a clear quantitative goal.

Some examples of a solid hypothesis are:

The current headline on our landing page lacks a clear value proposition, so changing the headline to a more concise and benefit-oriented version will increase conversion rate.

Our promo banners blend in with the page design causing users to scroll by them, so testing a more contrasting color will increase CTA clicks on the banners.

The lead capture form is too long causing users to exit the site, so reducing the number of form fields from 20 to 10 will increase the number of leads.

You signed into Sitecore Content Hub and you have your Excel sheet ready with assets to upload. You go to the Create page and … wait! Where is the option to upload from Excel? Don’t worry! If you have the right privileges or can grab the nearest Super User, you can enable the option!

Out of the box, Content Hub will only provide the basic Upload option, where you can browse or drag and drop files.

Enabling Excel uploads is as easy as following these simple steps:

Click the Manage icon in the upper right hand corner. It looks like a gear wheel.

On the Manage dashboard, choose Pages.

Once in Pages, navigate from Home to its User Import child page.

Once you select User Import, you’ll need to access the Creation component. It’ll be in the layout to the right. Click the three dots and choose Edit.

You’ve made it! Inside the Creation component toggle the Import Excel to on (green). You can now import from an Excel file.

Now when you return to the Create page, your Upload button will now say Add. Click it and you’ll see the new option Import Excel.

Check back for the next Sitecore Content Hub post, where I’ll show you how to prepare your Excel sheet for a bulk upload.