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While some customers will arrive at an e-commerce site with a clear idea of what they want, more will prefer to browse, so it is important to accommodate this user behaviour and make browsing for products as easy as possible. 

Providing effective and relevant filtered navigation can make a huge difference to the customer experience; it reduces the amount of cognitive effort required of visitors, and makes it more likely that they will find a product that suits them. 

I've been taking a look at how some UK e-commerce sites handle filtered navigation (or feature filtering, faceted navigation, whatever you want to call it), and providing a few tips...

The Get Elastic blog has some excellent creative examples of filtered navigation taken from websites from the US. For instance, on myShape, women can browse clothing collections on the site according to one of seven body shapes they are closest to.

Buzzillions makes great use of customer reviews by allowing users to drill into the detail. They can search by reviewer profile (technically challenged / tech-savvy etc), or by keywords that reviewers have used to describe products, such as reliability, speed of loading, and so on.

There are some other great examples in the post as well, though I haven't manage to find many examples as creative as this on UK e-commerce sites so far (let me know below if I've missed any), but there are some sites that provide good basic filtering options:

Comet

This kind of filtered navigation is especially useful when shopping for potentially complex products like TVs, computers and mobile phones. This kind of product search requires a lot of filters to help users find the product that suits them best.

Comet provides a great example of this, simply by providing as many different product features as possible for customers to filter by. In this search for a laptop I have 11 different filtering options, which should enable me to reduce the hundred or so laptops on offer to a more manageable selection:

Comet filtered navigation

Filter includes product specifications like RAM, operating system, and screen size, along with other important factors for customers such as price and free delivery. The additional ability to filter by reviews can also be useful if you have no fixed idea of the laptop you want. 

Also important here is the fact that the number of products in each feature set is shown in brackets, something which helps customers to narrow their searches without returning no results at all.

It is also vital that filters can be added and removed easily so customers can browse by different combinations of features. Here, filters can be removed with one click, and the results update instantly:

Comet - remove filters

Compare the Comet site to a rival such as PC World to see the difference that good filtered navigation can make. PC World has fewer filters, which makes it harder to narrow down the search, and they are also less easy to add and remove. This means customers have to work harder to find products that suit them.

mydeco

Interior design website mydeco has a large range of products available through its site (100,000+ just for bathrooms), so some effective filtering options are pretty essential to make it usable for shoppers.

Like Comet, mydeco displays the number of items in each category to help users return results, while the filters are smart enough to narrow down the search to a manageable size.

mydeco filters

They are also well-suited to the kind of products the site is selling, allowing users to filter by size in this search for bedroom furniture, as well as using a colour chart to help users match the rest of the decor in their rooms.

Zappos recently introduced a similar feature allowing users to browse through shoes, and filter by colour as well as size, price range etc, and it is something that can make browsing much easier for customers, and can work well for fashion items.

Hotels.com

This site makes hotel searches a little easier to narrow down with some very useful filters on the search results page. In this example for hotels in Paris, a search produces 1,688 results, which is too many to look through. 

Hotels.com filters

The filters here are very good, though my one criticism is that the results page can be slow to refresh after selecting each option. Alongside more obvious options like star rating and price range, users can narrow the search by a hotel's proximity to a range of Paris landmarks, by the facilities offered (internet access, pool, restaurant etc) or by type of hotel (boutique, historic, and so on).

A few tips for effective filtered navigation:

Show the features selected in a breadcrumb trail

This will show shoppers the filters they have selected so far, and allow them a shortcut back to any previous point in their selection history.

Make it easy to add and remove filters

Customers may add too many filters and end up with too few results. Making it easy to add and remove filters with one click as on Comet's website means that customers can easily refine their searches,

Refresh the page quickly

Though I liked the filter options on Hotels.com, having to wait five seconds or more for the results to be updated can become frustrating. Making it as fast to load and user-friendly as possible will mean more customers will take the time to search.

Avoid returning no results

This can also be frustrating for shopper, so don't allow customers to filter to the point where no relevant products are returned. 

Present the customer with meaningful filtering options

Filter should be things that customers typically look for from the products in question. Do not just present data because it happens to be available for a product.

Show customers that they are making progress towards a purchase decision

This can be achieved in a number of ways; such as showing the number of products available for each available filter, and that these are reducing with each selection, or showing that the filters available are reducing and becoming more specific.

Make the filtering options suit the product

Filtering by colour makes perfect sense when looking for shoes, shirts or home furniture and accessories, but is less useful for TVs or laptops.

Make sure product metadata is accurate

This is essential to provide effective filtering, and users will lose trust in the process if the filtering options they have selected return inaccurate or irrelevant product results.

Graham Charlton

Published 18 March, 2009 by Graham Charlton

Graham Charlton is the former Editor-in-Chief at Econsultancy. Follow him on Twitter or connect via Linkedin or Google+

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Linda Bustos

Nice work with a UK twist :)

One UK site I remember that is creative with filters is I Want One of Those's Gift Finder.  You can even narrow by type of gift recipient and personality (Miserable Sod, Child from Hell, Lady Who Lunches, Happy Hippy etc):

http://www.iwantoneofthose.com/giftfinder.jsp

over 7 years ago

Graham Charlton

Graham Charlton, Editor in Chief at ClickZ Global

Thanks Linda,

That is a good example, I'll use that one next time.

over 7 years ago

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Ted S

Good information and examples. Many sites try to filter but just don't make it work well enough to be useful.

Keying in on one of your first points, I really think there's a great opportunity in combining the filtering tools with personality based information like what Buzzillion has in their reviews. That way as a shopper narrows things down they can identify traits that others "like them" have. Data capture is a challange but it makes for much more meaningful sorting.

over 7 years ago

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David Reinke

My business touches fashion ecommerce and I see little progress in creating online filtering in the fashion space that allows consumers to quickly and confidently make purchases. 

The insight that's missing is that with fashion (unlike say electronics) the purchase is both rational and emotional.  In addition to product attribute filtering (rationally answering - here's what I'm looking for), the Social Shopping breakthrough in fashion is going to figure out how to let consumers also identify their fashion peers for the particular search they are performing and then filter the product results based on the preferences of that peer group (taking those 238 product results and filtering them in a meaningful way).

That will allow the fashion consumer to get peer validation before she forks over her credit card that the purchase she is making is the "right" one.  I would argue that often times folks don't really want to browse....it's just there is no faster, more direct way to get the required answers to make sound purchase decisions. Peer-based filtering combined with traditional product filtering will be the breakthrough social shopping has been waiting for.

David Reinke

founder, StyleHop.com

over 7 years ago

Graham Charlton

Graham Charlton, Editor in Chief at ClickZ Global

Hi Brad, great article, it does seem crazy that Google should punish retailers for producing more usable websites though.

over 7 years ago

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Mike De Luca

For good use of ecommerce filtering check out Merrell's new site and online store:

http://www.merrell.com/us/#store/M/M-F/

over 7 years ago

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Alex

Totally agree with you, that's why I like Amazon style. They provide a complete information starting from the product itself then followed by related products that are bought together, similar products, customer reviews. Everything the customer needs are placed in one page.

almost 6 years ago

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Mike

I totally agree the price camparison and rate and review makes the mind into buying level.I really like the shopping program to be work on.

over 5 years ago

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Nova

Very good article but it says nothing on where to find these filters. I like but how would one go about implementing one of these solutions, such as the one on comet.com?

over 5 years ago

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