Another example of this in the digital space would be e-commerce.

E-commerce websites are the most common area where a user is subject to an overwhelming number of choices.

Now the with e-commerce is not just the of similar products available for the users to choose from, it is also the numerous websites to choose from. When purchasing a cell phone, a customer would look at multiple websites to see which one offers the best deal. Not only that, they might even decide to wait for a sale period to begin to acquire the best bargain.

What can we as Designers do to deal with the problem of abundance?

1. Categorise, Filter and Search

To help users find their way around an e-commerce portal with thousands of products at their disposal, Designers should categorise their products very well.

If categorised well, the user would be able to navigate through the system better, and start their journey at a more relevant spot.

This would help them escape lot of unnecessary cognitive load that they would otherwise need to go through.

To assist the user with further narrowing down the catalogue, they should be equipped with relevant filters and sorting methods. For users who want to browse through products of a certain type or range, filters come very handy and leads them to relevant results.

Filters on Myntra

For users who know exactly what they want, search bars lead them to their destination in an instant. As designers, we can bring up items closely related to the search query for customers so that even if there is an erroneous entry, the next few results lead the user to the product they need.

Interactive search bars add further delight for users

2. Choose for the user

By employing Machine Learning, systems are able to predict what the user might need. As designer, we should use this data to our advantage by auto populating all areas of the UI that we can.

When choosing for the user, accuracy is key

If accurately predicted, the user will be able to build a trust with the system. So the next time a user’s screen is pre filled with data, they would be able to skim through it quicker and make faster and easier decisions.

Machine Learning

In systems that do not have the capability of employing Machine Learning, defaulting the choice on basis of history and relevance reduces their effort to a great extent. The advantage in defaulting is that the user expects it coming due to his past choices. Hence even if the defaulted value is not what is needed by the user, the frustration is far less than a predicted value.

3. Display limited options

Reducing the number of options available for the user is unfair, both to them and to the business. While not having enough choices causes dissatisfaction to the user, having too many disorients them. To deal with a large number of options, designers can choose to display the most relevant options for the user upfront, and hide the remaining on the UI. This way, we are reducing the cognitive load for the user without compromising on the flexibility of choice.

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