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Cyber Monday Search Review: Walmart, Target, Best Buy, Amazon & eBay

Black Friday & Cyber Monday are single-handedly the two most important days of the year for retail & e-commerce players alike. On Friday, American shoppers spent $5 billion dollars online  – that’s 17% more than in 2016 – on a selection of deals that were too good to refuse. Whether in store or online, shoppers looking for flash deals are going to rely heavily on search & discovery in order to proactively find the best deal on headphones, for example, as well as to discover an item, brand or category that they might not have thought of initially.

Today I’m taking a look at search experience of five of the most popular retailers and e-commerce pure players. Starting with the Algolia Search Grader, I’ll dive into the fundamentals of each site’s search speed, relevance & design. Afterwards, I’ll take a look at some of the interesting aspects of the search bar placement, the initial search experience, the results page & the search refinement experience.

For this review, I’ve chosen in advance three keywords that I’ll use (with and without typos): my queries can be categorized as Vague ‘headphones’, Long ‘iphone case blue with red stripe’, and Branded ‘bose headphones’.

Best Buy

Best Buy knocked the Search Grader out of the park with a 100% score (here), meaning they have all the fundamental features we would expect from a great search experience – there are a few places where it was a close call, though. Best Buy is typo-tolerant, but it’s not immediately visible in the drop-down menu. Instead, when you hit enter to see the results page for ‘haedphones,’ the page automatically displays results for ‘headphones.’ This may seem small, but if a user starts typing and see the dropdown menu showing nothing, they may get the impression that what they’re looking for isn’t available here (even if they’ve misspelled their query).Best Buy’s search bar is a bit small, and the suggested queries before you start typing give you the impression that you’re in for a text-only drop-down menu, but once you start typing you immediately get both suggested queries and results – this is a great use of the drop-down menu providing both discovery (queries you might not have thought of) and finding what you’re looking for (you can skip the search results page altogether).

Brand queries like “Bose” take you straight to the dedicated brand page, while Vague queries like “headphones” give you a search results page that empowers you both to discover categories like “true wireless” that you may not have thought of (or thought existed). In addition, refinement of the query is very easy via facets on the left-hand side, which have counts and are searchable by Brand.

That said, Best Buy doesn’t seem to handle my Long Query too well – I didn’t get blue or red iphone cases, let alone a blue iphone case with a red stripe. Color identification is a great way to deliver more relevance to longer queries – no need to go full machine learning to interpret ‘blue’ and the color blue on a product.

Like many retailers, Best Buy leverages Click & Collect with it’s “Pick up Today” tab, a different way of displaying a facet than in the left-hand bar. Best Buy’s lack of slider for pricing isn’t unique; however, we find that a slider for pricing adjustment, such as you might see on Airbnb, is a much more intuitive way to filter by price.

eBay

eBay came in at a 73% on the Search Grader (results here). Not providing results as-you-type, but simply query suggestions in the drop-down menu, makes a big difference in the UX when compared to Best Buy. The results are not instant, and displaying results for anything other than products, like Brands, is not nearly as visible as it could be.

The white search bar on a grey header is notably less visible than on most ecommerce sites, and eBay’s dropdown menu only provides two suggestions: query suggestions and categories to search my given query inside of. With so much blank space, eBay could display top results like BestBuy does and help shoppers who know exactly what they’re looking for skip the search results page altogether. I liked the fact that empty search queries with a specified category in the right-hand drop-down menu took me directly to the category page; however, if eBay’s search was a bit quicker, they could take me to the category page without me having to click-to-search in order to get there.

eBay struggled with my Long Query – I began looking for the New York Rangers case I found on other sites which perfectly matched my query and didn’t find anything; however, with a few query tweaks I did find an appropriate FC Barcelona case and a Coach case that I would’ve expected to show up give my query. eBay also struggles with query variance. If you’re looking to buy a PS4, for example, the two accepted normal queries ‘PS4’ and ‘Playstation 4’ will give you structured results that encourage you to go to eBay’s dedicated PS4 page; however, ‘play station 4’ and even ‘playstation four’ return ad hoc results that won’t likely convert Cyber Monday shoppers looking for a discounted PS4.

eBay’s left-hand facets could use a bit of work as well. Facet counts on the categories, search for facet values & replacing the pop-in modal when I click ‘More Refinements’ would improve the user experience here a bit.

While eBay performs better on paper than some of our other sites, the quality of the experience is still rough around the edges.

Amazon

The Search Grader gave Amazon a score of 70% (results here) – Amazon most notably gets docked hard for being slow to load results and requiring users to click to display results, instead of displaying instant search results as the user types. Instead, Amazon displays suggested queries in the dropdown menu bar, along with some options for category filters. Still, this is pretty common practice among top e-commerce sites today, and Amazon is making a conscious decision here to make their desktop and mobile drop-down search look the same.

Amazon’s home page makes search pretty prominent, displaying a white search bar on a dark header, meaning the search bar doesn’t have to take up a lot of real estate. Amazon’s home page is very geared towards discovery, displaying Black Friday deals by category, recommended deals, hot deals. It’s deal-city!

Amazon displays a category drop-down menu directly, but selecting a category doesn’t show you results and hitting enter without a query doesn’t take you to the well-designed category page, but instead displays top results in that category for an empty query.  Amazon’s drop-down menu displays suggestions, but takes up a lot of real estate which could easily be used to display results directly in the drop-down. Our Solutions Engineer Olivier Lance pointed out that this may be because many ecommerce sites imitate what works on mobile for their desktop version, opting for experience parity instead of optimizing for each interface.

Amazon’s search results page performs well across a variety of queries, including the typo-ed ‘iphone case blaue with red stirpe,’ which turns up a nifty New York Rangers iPhone case that meets all my typo-filled criteria.

My Vague query pushed a ‘Recommended’ result as well as a ‘Best-Seller’ result, which is a great way to drive the user to discover products. For refining my search, I am disappointed that the facets lack counts, and I can’t search for facet values (like refining my search to find Bose headphones) inside the long list of brands, and are all-around a bit too cluttered for me to really make use.

As an accepted authority on shopping, Amazon makes its recommendations known, appearing regularly in the first few results. It could be easier to get access to the long-tail of Amazon’s catalog – I had to open up ‘Show all departments’ and select electronics to see other cases, even though case was in my query. By not displaying results instantly with each keystroke, it also takes longer to check Bose headphones and then change your query to Audiotechnica headphones.

Target

Target scored an 83% on the Search Grader (here) – like most sites we’ve looked at today, Target doesn’t display results in the drop-down menu, so users have to click-to-search. Query suggestions aren’t typo-tolerant on the drop-down menu, meaning my Vague Query only gets suggested popular brand queries if I don’t make an error. The left-hand ‘categories’ section is also a bit of a rabbit hole – sub-sub-categories is a lot of diving before seeing results.

While they may not be typo-tolerant, I did like that query suggestions appear after you click the search bar before even typing – this is a great way to encourage discovery in a minimalist way that doesn’t feel promotional. After typing, the lack of instant results and typo-tolerant query suggestions means that Target is hoping you’ll click-to-search and that their results page will seduce you.

Target’s search results page stands out for a number of reasons. They have a lot of the features we love to see in a search results page – search for value values in the brand facet, facet counts for almost every facet – they even have a few features that eCommerce stores could get inspired by. For a retailer, I think Target’s execution on the click-and-collect feature is among the most natural I’ve seen – the simple checkbox ‘get it today’ above the results is very inviting, and the UX is very slick. I also very much enjoy the hover-triggered second image that Target displays on results – it’s definitely eye-catching, and if the load speed doesn’t suffer, it’s a great trick for image-centric search results pages.

When digging in with a long, typo-ridden query like ‘iPhane blaue case’ (I actually typed that by accident – don’t judge), I found that, while Target understood ‘iPhone,’’ it didn’t understand ‘blue,’ and I really started to feel the limits of Targets relevance here. I tried a Vague query ‘Phone’ and was a bit surprised to find two flip phones &  a landline among the top results – this may be the most relevant results for their shoppers, but I would’ve expected newer products, as someone looking for a flip phone will likely drill down by price or category to get there.

Walmart

Picking up a 90% on the Search Grader (here), Walmart has all of the same characteristics & features I’ve come to expect in these five Cyber Monday deals sites. It’s typo-tolerant, it’s injecting business metrics, and results load pretty quickly. There’s not much feature-wise that can be said about Walmart that hasn’t already been said about our predecessors, so let’s jump in to the experience.

Walmart’s relevance really blew me away. It crushed it on my Long Query, and when I refined by device (not in image), I got various options on striped & colorful phone cases. I would’ve preferred to see facet counts and the facets are a bit too cluttered for me, but Walmart really came through here.

My vague query turned up headphones for under $10 – a truly Walmart experience – and when I refined my query to ‘Bose Headphones,’ it picked up on the brand and gave me a full-banner ad letting me know that the high-end brand was indeed available at Walmart.

The experience itself was a bit cluttered – not just the facets, but the drop-down menu and the second menu that runs underneath the search bar – it took me far too long to find out how to to click-and-collect, for example.

Best Practices & Opportunities

Across these five sites, it was clear that there are some common practices and some places for improvement.

In terms of placement, it is pretty common practice to make the search bar as visible as possible – you can’t go wrong with a white search bar on a dark header. Dropdown query suggestions are the mode du jour, but I think Best Buy takes the cake for leveraging the width of the desktop drop-down bar to display instant search results. It’s one less load time, one less second of attention before shoppers go somewhere else.

If content is king, then relevance is queen here. The sites that stood out to me were the ones that dug through the color interpretation, through the typos, and through the vagueness to provide me not only with relevance results, but with context-enriched suggestions for categories, brands & products that I might be interested in.

Balancing discovery & finding isn’t just a relevance problem. Shoppers are increasingly willing to refine an initial search if they don’t find what they were looking for – they’re having a conversation with your search bar – but many of the biggest e-commerce sites could make that conversation more fluid by providing more value to their facets and by providing instant search results for queries that are refined within the search results page.