Site search personalization: How to configure & use cases

Site search personalization: How to configure & use cases

25 Aug 202210 min read

Personalization is a broad topic in E-commerce that includes a variety of components. One of the most critical ones is the configuration of internal site search and tailoring it as per the needs of each unique customer based on their profile data, purchase history, or preferences.

Site search is sometimes underestimated, yet poor or no site search has a direct impact on brand loyalty. Up to 43% of buyers are using the site's search box. So customizing search results may be a key source for making information available throughout your site and, thus, closing sales more quickly.

According to Google's research, on-site search rejection costs businesses more than $300 billion each year. Another research shows that 80% of customers will exit a website after having a bad search experience. When done right, personalization of site search helps minimize bounce rate, boost conversion rate, promote brand loyalty, and much more.

However, there are lots of details to figure out before personalization. In this article, we will explain how the personalization of site search works and how your business can benefit from it. Besides, we will take a look at practical ways to personalize the customer experience through site search and mainly analyze one of the leading search engines – via Elasticsearch integration.

What is personalized site search, and why does it matter?

Before we cover best practices, let's define some terms and answer frequently asked questions about personalization.

What is personalization?

Personalization entails adding user-specific signals on top of all other signals to increase the relevance of your product. It is a set of practices of showing different items to different customers based on demographics, intent, preferences, browsing history, past purchases, how they use their device, and other factors.

The purpose of personalization is to enhance the customer experience by anticipating and meeting customers' needs and preferences before they express them. Using data on each individual customer, you can make it simpler for customers to find what they want, based not just on the WHAT of previous purchases or browsing, but also by knowing the WHY behind their preferences.

Relevance is an important metric of personalization, which is determined by delivering personalization within the context of the digital experience. Good personalization is about using the right channel to deliver the right message to the right audience at the right time.

Why is personalization important today?

Customers love personalization. By providing an advanced customer experience tailored to your client's demands, you make them feel more compelled by your brand and this directly impacts conversions. As a result, personalization is a current trend in many domains, particularly in site search E-commerce, where it has long been a rallying point, and one of the major E-commerce site search best practices as of 2022.

Let's take a look at the statistics:

  • 91% of customers are more likely to shop with businesses that identify, recall, and provide relevant offers and suggestions.
  • Marketers report an average increase in sales by 20% when implementing personalization. E-commerce enterprises that engage in sophisticated personalization regularly achieve additional sales increases of 10% or more.
  • Businesses that use advanced personalization claim a $20 return on investment for every $1 spent.

What is on-site search and why personalize it?

The search feature is frequently the first point of contact for visitors to your site. Doing it correctly might be the difference between someone becoming a lifelong customer and leaving your site and going to a competitor. Other than that, customers frequently don't know what they're looking for. They occasionally misspell search queries and require a little nudge in the proper direction.

Personalized search results are more accurate and relevant, allowing customers to quickly obtain the information they require. Search personalization is also known as query understanding. It entails leveraging information about the searcher to either personalize query probability estimation or supplement the question as a signal for query interpretation.

When to use site search personalization?

Personalizing site search won't magically improve your product, especially when user intent is clear. However, when user intent is broad, and you offer several options, personalizing site search helps connect customers with relevant information. Site search E-commerce allows organizations to look at each click, search, and every item added to a cart to better learn what each consumer appreciates and predict what they’re most likely to buy.

Known vs unknown visitors

All customers were once unknown visitors to your site. Even if a customer is not logged in or is visiting the site for the first time, a search may be tailored by browser type, IP location, time of day or year, mobile versus desktop, and other criteria. You can advertise items based on their IP location even if you don't know their gender, age, or purchasing history. For example, in Miami, you may promote different winter clothes than in Minnesota.

Customers who log in to their accounts and have a purchasing history, such as pages viewed, items purchased, gender, age, and so on, are considered known visitors. You may tailor results depending on their profile and site behavior. In general, the more information you know about someone, the more customizable results the system can provide.

Top 5 site search personalization practices

Once you have customers' data, you can evaluate which practical method is the best suited to leverage personalization for your website. There are various approaches you may take to implement intelligent site search and customize search queries for your customers.

Key approaches to site search personalization

  • Behavior-based ranking. According to this model, we build the search that is constantly learning from your customer user experience on your website. In other words, you analyze the behavior of your customers on the website and predict the possible actions they want to make. The user can affect the results with their own choices and browsing history. This model also refers to in-session personalization that seeks to offer relevant experiences from the moment a consumer enters your site. This approach helps us to take into account every action the user performs on the site to learn about their individual search experience. The idea is to determine the user's purpose fast and utilize that knowledge to direct them to the most appropriate product suggestions.

  • Rule-based ranking. This approach is built by the principle that we first define the audience based on their data such as demographic information, devices, browsers, and similar, and based on such specific parameters we set up rules according to which we show particular products to particular groups of customers that drive search personalization. As a result, customers get results offered based on their profile automatically. This method is also related to history-based personalization which is based on the knowledge of who the customers are and what actions they previously have done on the website. With every new interaction, this model collects information about user intent building its knowledge base. Often, users are added to engagement groups on the guidance or recommendation of the personalization algorithm.

  • Did you mean & You might also like. This approach allows automated search assistance for each unique customer. First, we analyze user profiles, then make suggestions on what’s better to recommend them, based on the current trends and their profiles. Besides, we can also take into account what other similar user personas are browsing, or purchasing while interacting with the website.

  • Personalized query probabilities. When the visitors are known, you can use this approach to predict what they will search for. Searchers often repeat queries, and sometimes even within the same session, which then is saved in historical query logs. Using this information, we can analyze a searcher’s interests and personalize query probabilities.

  • Personalization as an intent signal. Personalization might be used for query rewriting or result ranking. Searchers on a clothing website, for example, are most likely seeking things that they can wear. If we know, or can guess, the gender and measurements of the searcher, we may alter the query to filter or enhance results that fit those criteria.

How Elasticsearch enhances personalized site search

Custom E-commerce development includes a variety of options for implementing site search personalization. Elasticsearch, a well-known and powerful technology for personalizing site search, allows you to add scalable, relevant search experiences to all of your apps and websites. It offers a wide range of search result customizing possibilities right out of the box.

Technical details behind Elasticsearch

It is a RESTful search and analytics engine. Released in 2010, Elasticsearch is a Java-based API built on Apache Lucene. Elasticsearch personalization indexes your data using keywords. This makes search queries go quickly because Elasticsearch searches through the keywords instead of the full text (this is called an inverted index).

What Elasticsearch offers for site search personalization

  • Personalized search, superior relevance
  • Accurate results
  • Leverage machine learning
  • Promote your best results
  • Refine results during the process

What Elasticsearch offers for site search personalization

  • Personalized search, superior relevance. With excellent out-of-the-box search relevance, Elastic gives all of the tools you need to create compelling search experiences that help people discover precisely what they need. Rich relevance tuning tools and cutting-edge machine learning assist you in further implementation of rule-based and behavior-based ranking.
  • Accurate results. Elastic's search relevance, as well as plenty of customization options, allows you to curate results based on real-time corporate data. As a result, you better understand customers' demands by providing relevant search results that help them get from where they are to where they want to go.
  • Leverage machine learning. Machine learning may complement search and business insights to improve your search applications and customer experience, whether you're introducing new ideas to extend the effect of your search or looking for new methods to increase search accuracy. Improve semantic relevance with vector search, NLP model support, and model management.
  • Promote your best results. With automatic, data-driven suggestions based on search metrics, you can prioritize your best-performing results. Accept, reject, or implement curation suggestions automatically. Your automatic suggestions grow increasingly relevant over time as a result of machine learning.
  • Refine results during the process. Precision tuning allows you to easily change the recall of your findings, as well as give weight or boosts to certain data fields. Elasticsearch personalization allows you to add synonyms for frequent search phrases to tailor the search to the needs of the company and the user. There's no need to redeploy because the modifications to search relevancy are live in production as soon as you're ready.

Best cases of personalized site search in E-commerce

Here are some of the best examples of site search personalization to learn from.

Frans Hals Museum

This website reflects the duality of the classic and contemporary, showcasing a collection of 17th-century art alongside modern pieces and colorful design.

Challenge

The website offers plenty of tickets to reserve and buy for exhibition programs in the art museum. The goal is to make it easy for customers to use the website and give them useful recommendations.

Solution

The Discover section provides some interesting and unexpected methods to view the museum's collection. Visitors can explore artworks by mood, color, medium, or artist, or they can choose Random to be provided with a group of items that are produced casually. A navigation bar on the site helps visitors to find key information, such as the museum's location, opening hours, and daily events, without having to go through the Visit us pages.

It is not necessary to register on the site because the Frans Hals Museum uses an in-session personalization model. The site actively analyzes all requests made by each specific user and outputs not only all relevant results but also those that are similar in style to artists, exhibitions, locations, and more. By opening each of these results, the visitor sees another portion of recommendations that match their interests.

Zenni

Zenni, as a pioneer in the eyewear market, provides a one-of-a-kind experience to its clients. Augmented reality (AR) is used in this technology, which lets people try on the glasses on their own devices before buying them.

Challenge

Zenni wanted to create a more engaging customer experience by providing personalized product recommendations through its digital store.

Solution

Customers can register and enter their prescription information, such as pupillary distance (single or dual PD) and preferred lens type (single vision, bifocal, progressive, or readers). All search results will be personalized according to the provided parameters.

Other than that, the website offers autocomplete recommendations with visuals by making the search box visible. For example, when users type kids, product photos from the Kids category are displayed.

Ryanair

Ryanair is based in Dublin, and its flights link 37 countries and 225 locations. Ryanair has positioned itself as Europe's greenest airline in recent years.

Challenge

Ryanair intends to show customized search results to customers to preserve its competitive edge long-term and to continue providing higher value for customers.

Solution

The great feature on the website is pre-flll search options based on past searches, purchases, and locations. When customers use the search function again, Ryanair includes a dropdown of suggestions of appropriate terms and categories. This practice works well both for customers that are browsing and those that have arrived on the site with a specific repeat purchase in mind. Browsing visitors will be able to select from a range of relevant categories while returned customers can quickly select the options they require.

Patagonia

Patagonia is a manufacturer of outdoor apparel and equipment for the silent sports of climbing, surfing, skiing and snowboarding, fly fishing, and trail running.

Challenge

The aim of Patagonia was to offer query predictions for customers that are tailored to the site’s specific content, so users can be confident they’re finding their desired content.

Solution

Patagonia provides a great example of personalized autocomplete on E-commerce site search. When a user starts typing, autocomplete displays options in a menu beneath the search. Users can click the recommendation or use the arrow keys to go up and down the suggestion list and choose an alternative.

Key takeaways

The following are the important conclusions from the article:

  • Personalized customer experiences are integral to business growth.
  • Personalization is the process of understanding your online users' preferences using historical information and prior interactions with your site. Your customers tell you which products they like to buy with every search, click, bounce, add-to-cart, and purchase.
  • Customers who use your on-site search capabilities are telling you exactly what they're searching for, and it’s important to help them find it promptly before they leave.
  • Site search personalization is often overlooked but this component is a powerful way to offer better recommendations and help customers find what they’re looking for. The key to success in site search personalization is to use the right algorithms at the right touch point of the customer journey.
  • Among primary methods to personalize site search are behavior-based and rule-based ranking. Best practices to implement site search include autocompleting, autocorrect, personalized query probabilities, personalization as an intent signal, did you mean & you might also like, and more.
  • Elasticsearch personalization helps to configure all of the mentioned methods of personalization and even more. It puts search power at the heart of the fastest, most reliable, and most scalable E-commerce experiences.

If you are looking for additional guidance on the implementation of site search functionality, the Wise team can provide you with Elasticsearch consulting or launch an audit of your existing search engine. We can also assemble a dedicated team to ensure end-to-end Elasticsearch integration and handle all tech challenges of your specific case.

At Wise Engineering, we implement advanced personalization that helps deliver real-time recommendations to users based on multiple factors, including purchase history, card additions, and more. Contact us to discuss details.

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