Too much choice can overwhelm and discourage us. It’s human nature.

It’s called a “paradox of choice”. We say we always want to have more choice but the more options to choose from the less likely we are to make any decision at all.

This can be a problem when we are confronted with a large product range and have no easy solution to filter the results according to our mental shopping lists.

The article is based on Mindberry‘s findings when working with their clients.

Adjust filter options to suit the “mental shopping list” of users

Shoppers usually have some idea of what products they are seeking. It’s their “mental shopping list.” This list contains important key data, as well as inclusion and exclusion criteria for the desired products. It can vary considerably, depending on the information stage, the type of product, or the shopper.

Often, a notable discrepancy exists between the criteria on this mental shopping list and the filters offered in online stores.

The “language” of visitors, the way they think and decide about the products, can be very different from the language in filters offered in online shops, which are usually classified according to industry-standard categories.

How Megaparkett makes filters easier to understand for its visitors

Megaparkett is Austria’s largest online store for branded hardwood floors. To facilitate the selection process in their wide range of products, they offer a number of filters.

The first step in improving their effectiveness was adapting the existing filters to the users’ language.

For example, the industry’s common descriptions “lively,” “natural,” and “quiet” (this is how the look of parquet flooring is described) have not always been clearly understood.

Usability tests uncovered many statements similar to the following:

“It would make it easier for me if I knew what’s behind those individual categories.“

So they added additional explanations with tooltips:

How Megaparkett introduced new filters based on user feedback

In the second step, they determined which needs were not being covered by the existing filters. Usability testing helped them to better understand the mental shopping lists of hardwood-floor seekers.

Again and again, they observed how users lacked important exclusion criteria in the predefined filters. This fact annoyed the shoppers, since they wanted to have set their desired criteria with the filters instead of finding out on the product pages whether the desired criteria did or did not apply:

“I do not want to have to look in each product page if the hardwood floor is not compatible with underfloor heating.”

The usability tests have clearly shown that users are looking for very practical things, such as

• whether underfloor heating is compatible with a particular floor;
• which floor is suitable for a kitchen and living room combination; and
• which floor is recommended for pets.

On the basis of this feedback, the filters were supplemented with additional options that contained the exact words that went through the shoppers’ minds.

End result: improved comprehension, improved user satisfaction, improved conversion rates, and increased revenue.

Conclusion

Usability tests consistently show how missing or inappropriate filtering options lead to frustration and site abandonment.

Product filters frequently do not “speak” the language of the website visitors. In-house categorizations or industry jargon are not understood. Important filter options are often missing from the selection list.

When you conduct usability tests, pay particular attention to the users’ filtering behaviors.

• Which specific words do visitors use when searching for their products?
• Which selection criteria are missing, resulting in users searching for them in vain?
• Are there technical terms that are not understood?

How successful e-commerce sites adapt their product filters to reflect the users’ mental shopping lists

PS. To see users’ behavior after you implement the changes, use heatmaps to determine which filters are used most often.