What can my teapot teach you about designing for analytics?

My teapot, or rather the water heater, helps me make great tea, based on the type of tea I want to drink.

It also was a reminder for me about how good design means translating quantitative values into qualitative values people can relate to:


As a tea drinker, my goal isn't to heat the water to 175 degrees.

It's to enjoy the best green tea I can make.

The lesson here can be translated to charts, analytics, and messaging that your product's customers interact with.

Are you just dumping numbers on them, and triggering actions or messages based on threshold values etc? Or, do you translate the quantitative into useful, qualitative labels like this water heater?

Granted, some complex software systems and analytics cannot be watered down to this level of simplicity, but the interface does a good job of helping me to achieve my actual goal. 

In the next edition, we will talk about a small design tweak that could make the interface for this water heater even better. Can you guess what it is?

It comes down to "loudness."

I often talk to my clients about "loudness" on the screen (boldest, biggest, etc.). What data is screaming for attention? What is subservient? Are things balanced properly?

In this case, the proper green tea water temperature is 175 degrees. However, the 175 label is "louder" than the "green" label. This suggests that I should care more about the quantitative value (175)  than the fact this setting is what makes good green tea.

Making "green" the louder label, and the "175" a bit quieter, would improve this interface for the average tea drinker. It's a small tweak, but when you have a rich UI with a lot of data, all of these minor UI details add up and either compliment or hinder your product.

If you need help designing your own water heater interface, or your software product, you can schedule a free 30-minute consultation with me.

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