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Search Beyond the Box: 4 Ways To Use Advanced Search Technology To Improve Conversion Rates

  • Written by  Matthieu Blandineau, Algolia

0aaaMat Blandineau AlgoliaSearch is a way businesses can connect with their users — to understand what they are looking for, anticipate needs and deliver a great shopping experience. However, search is not simply about helping the customer find what they are looking for; today’s consumers come to your web site for a relevant, personalized experience. When a shopper can discover something new or feel inspired to browse through recommendations, you’re turning a one-off buyer into a loyal returning customer.

At its core, a powerful search experience harnesses the consumer’s intent and connects it to the product that the user wants to find. Innovative retailers use search technology as a strategic weapon — driving metrics that impact their business like conversation rates, “stickiness,” engagement and increased basket size. We’ll take a look at strategies in which search and discovery can help you understand your users and move your KPIs forward.

Why Search Matters In E-Commerce

To establish a foundation, let’s first discuss why your organization should dedicate valuable time and resources to progress your site’s search experience.

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Users have come to expect a great search experience. Consumers won’t just turn to your competitor for that single purchase when they can’t find what they are looking for on your web site — they will remember their bad search experience, and moving forward they will be hesitant or unlikely to return to your web site. While great search provides an impression of an overall smooth customer experience, bad search is far more memorable.

Covering The Basics

With that said, great search also has a direct impact on your business results and KPIs — no matter the industry. This includes increases in click-through rates, average order value and conversion rates from searches to checkout. While advanced capabilities are critical in order to stay ahead of the curve, establishing the basics as a foundation is critical. Here are some tips:

  1. Textual relevance. The name of a product, its brand, keywords in the description — what we call attributes — constitute textual relevance. Textual relevance means reading correctly into the user’s intent even if they misspelled a word or used a stop word, such as “the,” “and,” “at” or “with.” It also means giving them a synonymous result — such as offering a parka when they typed in “jacket” — and making sure that plurals are accounted for. For example, when consumers search for “feet warmers,” results should also display foot warmers.
  2. Business relevance. You can leverage your own business metrics to further impart relevance, ensuring that the user sees content they are most likely to act on. For example, you could (and should) be tracking conversion rates on your products, so displaying the result with the highest conversion rate first will help guide users to products that have been viewed favorably with consumers seeking similar results.
  3. Personalization. This is the proverbial cherry on top for stellar relevance, and it can be considered at a user level or at a group level. Let’s say a user is not logged in but you know they are in a certain age bracket or from a certain country — in that case, we are talking group-level personalization. If they are in fact logged in, and you know their browsing or purchase history, you can take advantage of personalization at the user level.

Advancing Search Capabilities To The Next Level

There was a time when search was not only a box for users to enter queries into, but a box to check off on your list of web site elements. This is no longer the case. Search needs to serve a variety of purposes — from shoppers looking to find a specific item to shoppers browsing to find something new. This means going past the standard usage of the search box. Here, we’ll take a few examples to illustrate how search technology powers search experiences beyond the box.

1. Multi-category results — multiple paths to conversion: In this type of experience, the user is offered multiple content types as a result of their query. This allows the user to choose their favorite content type preference by further diving into it. For example, if a user types “planner” in the search box, they can instantly choose a subscription, a category and a collection related to planners — or, if none of that works, dive into a blog post. This offers the user multiple paths into different types of content, which translates into multiple paths to conversion, based on a user’s personal preferences and ways of processing information.

2. Facets — filters with special intelligence: We are all familiar with filters as a way to narrow down our search result options. A facet is a filter that is intertwined with the result sets: the only facets that appear are the ones that match result sets. This prevents a “no result” type of screen experience, which almost universally causes users to bounce.

Let’s say a user types in “dress” in the search box, which turns up a certain number of results with filters to hone in on the perfect product. If a user refines their search query to a “silk dress,” categories available will decrease, showing only applicable facets. This means that, in a few keystrokes and clicks, the user finds the very item they want and gets a superior experience to that of a long list of items that comes with a standard search bar.

3. Autocomplete overlay — letting the user define the interface: When the user types in a query, a new, large overlay window pops up, offering users to dive into additional facets via the “Show more” and “Show less” buttons, as well as a price range filter. This is called an autocomplete overlay. Another positive consumer experience addition to include is letting the users toggle the view, indicating what is useful for them in terms of the interface itself.

4. Recommendations and related searches: An extension of multi-category result experience is to provide recommended results that not only show matching keywords but also matching brands and categories as recommendations. In short, you are giving users an easy way to drill down into what they really want.

Here, we can also apply an advanced use case of related searches. For example, when a user searches for “iPhone”, they get refined search suggestions in the results page, such as “iPhone case,” “iPhone charger,” or “iPhone XS 128GB,” so they have another path to find the right product for them.

Advanced Search Technology Is A Win-Win

Search matters because it improves the experience, conversion rates and the relationship with the user. Bad search is expensive not only because your users remember it, but also because they inevitably bounce from your site.

Advanced user experiences go beyond the search box: they include powerful discovery through browsing, faceting, innovative user experience buttons and much more, shortening the user’s path to the shopping cart while driving your KPIs and resulting in a win-win for everyone.


 

Matthieu Blandineau is a product marketing manager at Algolia, the leading Search and Discovery API for web site and mobile apps. In this role he focuses on marketing and strategy for Algolia's retail solutions. Blandineau is passionate about packaging advanced technologies to help retailers achieve their goals and offer their customers the best user experience.

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