Your Wallet is Full of Intelligent Content

How U.S. Currency is a Great Analogy for Content Strategy

During the Intro to Content Strategy Workshop, we discussed what it means to have intelligent, modular content. Remember, the world's most impressive library is useless if all the books are scattered on the floor. By using metadata, content types, taxonomies, controlled vocabularies and an intelligent content model, we can create an extensible infrastructure for content to live and for users to happily find what they need.

The other day I was waiting in line to pay with cash (a rare occurrence these days), and I was noticing all of the intricacies of the dollar bill. Then it hit me – content elements. U.S. currency is a great example of the relationship between content types and elements. Let's break it down.

Currency comes in multiple forms and is something used around the world, but for the sake of this example the U.S. one dollar bill will be our content type. 

Content Type: U.S. One Dollar Bill

The way in which we exchange this currency for goods is with a cotton/linen blend of rectangular green cloth. This is our content format. If it was a credit card, our format would be rectangular plastic. Often on websites, our formats are text and video. It's the way the content is delivered.

Content Format: Rectangular green cotton/linen cloth. 

As we discussed in the workshop, content types are meant to serve as reusable templates. Dollar bills come in a wide range of denominations. $1, $5, $10, $20, etc. All of these are distinct content types that share common content elements. These content elements include:

Content Elements

  • Headline - Federal Reserve Note
  • Subhead - The United States of America
  • Denomination title - One Dollar
  • A photograph - In our $1 example, George Washington
  • Federal Reserve Bank Seal - On this one it's San Francisco, CA
  • Serial Number
  • Series Number - On this one 2003 A
  • Signature of the Secretary of the Treasury
  • Signature of the Treasurer of the United States
  • A note about legal tender
  • Plate Position
  • Facility Mark - On this one it's Fort Worth, TX
  • And so on...

These elements will be populated with different information from dollar bill to dollar bill; however, all one dollar bills will contain these same elements. 

If we add metadata into the mix, it would include things that we don't necessarily see on the dollar bill. For example, the year printed is part of the Series. However, we don't know who the first person to spend this dollar bill was. More examples of metadata about this dollar could be:


  • Number of people who've used it
  • How old it is
  • Where it originated
  • Where it currently resides
  • etc.

Controlled Vocabularies 
Lastly, the Federal Reserve uses a controlled vocabulary with currency. You don't see discrepancies or different terms and language used across different bills. It's consistent. Everyone knows to expect THE UNITED STATES OF AMERICA across the top, not USA or another term. Consistency can be an important part of training a user to interact with content. 

Now, if you have a bunch of U.S. currency of different denomination spread across a table, you could construct a content model out of your various content types. Isn't this fun?

I hope that this analogy has helped crystallize the idea of intelligent, modular content for you. Curious to know if this content was helpful. Let me know by answering 2 questions