Online product filtering top tips

By Dan Marley

With the online retail world offering a wide variety of products, consumers need to be able to cut through the masses of products available in order to find the single product that they actually need.

The technological world can be hugely complex, with an ongoing game of adding small specifications to the product you want and then removing them to get the ideal product within budget. This is where filtering products becomes more of an art form. If this is not done well then users can become frustrated and bored very quickly.

Here’re my top tips for product filtering design:

Don’t forget the context

Consumers generally know what they want, and as such will apply multiple filters. Results that automatically update after each individual selection can be a great and engaging experience. However if results are not instant it can be very frustrating. It must be taken into consideration that not everyone will be on a laptop with fast broadband; some may be accessing the site through a tablet or Smartphone and therefore relying on 3G or even slower.

Show filter options relevant to your target audience

If you don’t provide filter options that appeal to your target audience they are likely to be left frustrated. Savvy tech users are less interested about colour of a laptop and more interested in graphics cards, RAM and the processor.

Prioritise the filter options

Ensure the most important/used options are at the top and all others are under ‘More options’. The use of ‘Advanced filter’ may be overwhelming for less confident consumers.

Give an indication of the number of results relating to a selection

There is nothing more frustrating than selecting a particular filter option only to discover there are no results. Provide a numbered indication in brackets alongside each filter option. When an option is selected the other numbers should dynamically update to take into consideration that selection.

Allow multiple selections

Don’t force users to select one of multiple options. Selecting more than one option should dynamically influence the number of results displayed for all the other options, as mentioned above.

Who does this well?

Some examples of well executed filtering include, comet and John Lewis. For something a bit different it is worth brushing up on your Nobel Prize winners with this filtering system: elastic lists. It has a huge amount of playability as well as being very quick at dynamically updating filter options.

What do you think?