By Kait Spong
13 min read
Search relevance is an essential aspect of the search engine experience. The whole point of using a search engine is to find relevant search results quickly and easily. Early web search engines had basic algorithms that returned generic search results, but with advancements in technology, modern search engines have become smarter and are now able to return more relevant and personalized search results.
Improving search relevance involves using search algorithms and relevance rankings to provide users with the most relevant search results. Measurable relevance improvements can be achieved by employing techniques such as incorporating secondary data sources, which can provide additional context and depth to a user's search query. By doing so, search engines can return engaging search results that align better with what users are searching for.
Users' search behavior has also changed, with people now typing in more specific and complex queries into the search bar. Creating a relevant search experience is crucial for any search engine. By incorporating secondary data sources and using smarter search algorithms and relevance rankings, businesses can deliver the most relevant search results to their customers. This can lead to more engaged users, increased conversions, and higher customer satisfaction.
As human beings, we appreciate choice. All of us have unique preferences for everything, from ice cream to streaming services. In its purest form, choice is the ultimate expression of free will. These days, there are a lot of choices out there, especially when it comes to online shopping. It can be tough to feel like you’re making the right decision as a customer. This often leads to the common phenomenon of analysis paralysis where the paradox of choice rears its ugly head, and you’ll only end up with too many options and fear of making the wrong choice.
From a digital commerce perspective, it might be just as difficult for you to select a technology vendor (or vendors) that will accommodate the customer, help you stand out from the rest of the digital crowd, and improve your company’s return on investment (ROI). If you’re looking to help your customer along their purchase journey, the solution lies in creating winning digital experiences with a flexible, agile tech stack.
Bloomreach CEO and co-founder, Raj De Datta, believes these winning digital experiences are built for the seeker, not just the customer. Too often, we think of our target prospects in a limited way: They are customers — plain and simple. But human beings are much more complex and assume multiple roles in their daily lives: an employee, a mentor, a parent, a sibling, or a spouse, to name a few. Before they become customers, they are seekers with a purpose that they hope to fulfill. It’s your objective as a business to ensure their success.
By shifting from a “customer-centric” to a “seeker-centric” viewpoint, your company upholds answers over results and participation over consumption. According to De Datta, “These companies recognize that while choice is great, we can do much more to make the experience positive and productive.” But where do you start when there are so many solutions that seem to be worth your investment dollars?
Fortunately, the e-commerce industry is quickly refining itself to meet the demands of the seeker, as indicated by CommerceNext’s recent report with CommX, “2022 Digital Trends & Investment Priorities.” The data collected in this all-new report illustrates that 31% of the surveyed retailers believe “on-site experience/conversion optimization” is their top sales priority for this year, while 64% see it as their top two priority.
Findability is crucial to both on-site experience and conversion optimization, and businesses must leverage seeker-centric solutions that properly align with the customers’ needs and expectations to win. In this guide, we explore the potential for increased revenue once you’ve implemented relevant and cohesive on-site experiences that begin with one of the most important phases of the purchase journey: product discovery.
Because transactions have been the main focus of e-commerce over the past two decades, many companies haven’t begun to unravel search’s significance in digital experiences. Search relevance, a digital strategy that attempts to bridge queries to answers via search results, is a tactful approach that appeals to a prospect’s interests and motivations. This guide will help you unpack the basics of search relevance, its importance in today’s market, and its ability to generate more revenue for your business.
What Is Search Relevance?
The Basic Definition of Search Relevance
Search relevance sounds pretty great on paper, but what is it exactly? In the simplest terms, search relevance happens when a page of search results matches what a user types into the search bar. Of course, there’s a lot more to it than just this.
Since the internet is overloaded with choices and all the information that accompanies those choices, it’s difficult to monitor and solve for search relevance with human effort alone. By investing in a top-tier product discovery solution, you’ll guide the seeker to the transactional portion of their journey where they can convert into a customer.
The Basic Objective of Search Relevance
Millennials and zoomers aren’t just looking to purchase a product or service on your e-commerce website; they’re also searching for memorable customer experiences that align with their concerns and beliefs surrounding sustainability, ethics, and inclusion. Because seekers have harnessed the power of choice in today’s market, they have room to insert their values when making purchasing decisions. So, while the internet has helped us in many ways, it has also shifted our expectations in many others.
As a business trying to survive the tumultuous landscape of the world, your company must focus on these preferences to thrive, and search relevance is just one of the numerous ways you can provide better experiences online. After all, the seeker can simply hop over to your competitor if they don’t like the user experience (UX) of your website, so why wouldn’t they do the same when your search bar returns irrelevant or even null results? If you truly see your business as part of the seeker-centric movement, you’ll need to eliminate any frustrations for your prospects, beginning with product discovery.
How Is Search Relevance Delivered?
A Review of Semantic Understanding
Contextual knowledge is extremely valuable when you’re having an in-person conversation with someone. Your tone, delivery, and body language all convey meaning to the person on the other end of the exchange. But search bars on e-commerce sites often miss out on the nuances of human speech.
Thankfully, artificial intelligence (AI) will allow your search bar to understand your products on a deeper level and present them in ways that make sense to your customer. Smart search bars with extensive dictionaries and multilingual capabilities can identify words and separate product types from attributes like colors, brands, and sizes. Take “chocolate milk,” for example. AI would separate the attribute (chocolate) from the product (milk), so there will never be a mix-up between “chocolate milk” and “milk chocolate” again. This combination of natural language processing (NLP) and machine learning (ML) is referred to as “semantic understanding.”
Even though the words are the same in our example above, the order changes their meanings completely, and if there is a lack of semantic understanding, your search bar won’t do its job properly. Most search bars are looking to match keywords in the query, not the intent behind the arrangement of keywords. The technology used to optimize your site’s experience needs to be as knowledgeable as your top merchandiser, or your brand will be shelved for a competitor that better understands the seeker’s objective.
Retrieval and Ranking Algorithms Uncovered
Although the inner workings of semantic understanding are far from simple, site search technology simplifies the approach into two algorithms: retrieval and ranking. While these algorithms are not unique to the commerce industry, they both work together to create an optimal search bar that retrieves all relevant products and ranks them accordingly to maximize business impact.
Once the search query is parsed by attributes and product intent, search technology will enhance the query with synonyms. This enhancement serves a two-fold purpose: to eliminate null results and expand the relevant ones that are returned. Not only will expanded search results help the seeker find exactly what they’re looking for, but it will also encourage them to look beyond a singular intended purchase while converting into a customer.
For example, if someone is searching for a “crimson evening gown,” the color attribute “crimson” will be enhanced with other similar descriptors, such as “ruby,” “rose,” “maroon,” and so forth, and the product type “dress” will become interchangeable with “gown,” “cocktail dress,” and “party dress.” An expansive list of synonyms for a product and its accompanying attributes ensures relevant results that match all parts of a query in an order that makes sense to the seeker.
The Value of Good Data Quality
Big data has been a big deal for the past decade, and its acceptance has allowed for innovation and convenience in just about every facet of our lives, from fighting the spread of COVID-19 to allowing our businesses to operate more efficiently. Despite the strides that big data has made in recent years, organizing, managing, and even storing data can take a village, which is not exactly a smart approach for your company from a labor perspective.
Unfortunately, product discovery won’t live up to its full potential without good data. First, you’ll need rich product data — information about a product that can be read, measured, and structured — in a usable format. Add in some customer data from your customer data platform (CDP), and your e-commerce site will have the commerce data it needs to identify and adapt digital experiences to each seeker’s preferences. The better the commerce data, the better the product discovery and overall digital experience.
Even if your product data is far from perfect, the right technology can fill the void. Search solutions in the e-commerce industry often tap into historical data to improve findability, merchandising, and recommendations for brands. As time goes on, self-learning AI will gain a deeper understanding of your customers and apply this contextual knowledge to your product catalog. The mutually beneficial relationship between data and AI is a huge advantage when gathering deep analysis to refine your search strategy, tailoring online shopping experiences, and improving conversions.
Strategies to Optimize Search Relevance
Site and Search Merchandising 101
When it comes to in-store merchandising, physical displays of products are strategically arranged to appeal to the customer and achieve sales goals. Think of lavish holiday window displays or the hard-to-deny, last-minute purchases that stare at you down in the checkout lane. Window displays and checkout lanes are prime locations with a lot of visibility inside a brick-and-mortar storefront, making them the perfect spot for “big bet” products.
Your intention online should be the same as it is in store: leveraging product placement to maximize conversions. In other words, your site search is an excellent way to place products in front of a seeker at the most opportune time. This is why site search and digital merchandising are such popular strategies among commerce businesses hoping to better arrange and optimize their website, especially as they look to these various digital solutions to increase revenue.
Similar to traditional merchandising, the way you display your products online is completely up to you and your business goals. Whatever your strategy, your objective should always be curating search results that guide and engage the seeker and inspire them to take actionable steps in the sales cycle.
How Self-learning AI Contributes to Search Relevance
It’s no secret that cloud infrastructure has promoted the democratization of AI. These days, AI is available to everyone, and more importantly, the technology has seen major improvements due to its larger availability. This fortunate chain of events has led to a significant shift in the ways we can use AI to our advantage, whether it’s supplementing people or processes. Yet, AI is quite the umbrella term, and its meanings are so diverse and complex that they can often be lost or even taken for granted. It’s crucial to grasp how AI breaks down into multiple applications, tasks, and types, such as ML, NLP, and neural networks.
The AI behind your search bar heavily relies upon ML and NLP. NLP can step in to decipher search queries, while ML allows the technology to become smarter over time without help from humans. The reasoning for utilizing these two types of AI is simple: The way people communicate across languages can be confusing — even for another human, much less a machine. It’s not uncommon for us to use the same word to describe different things, or be somewhat ambiguous in a question we ask or a description we give.
With the right search solution, businesses can leverage AI to crunch large volumes of data coming from prospect information, product catalogs, and business transactions. Then, commerce teams can apply this contextual knowledge to their set objectives, as the AI continues to learn from ever-changing consumer behavior, product changes, and manual team updates.
A Headless Tech Stack Is the Future
Now that you know more about site search and the AI working underneath it, you might wonder where all of it fits into your e-commerce game plan. Since monolithic platforms are slow to adapt and far too limiting for many contemporary businesses, more companies in the commerce space are looking to a “headless” approach.
While it might sound like a horror movie gone wrong, headless commerce is a new ideology that continues to turn heads — in a good way. Unlike a monolithic solution, headless commerce decouples the front end (or “the head”) from the back-end commerce functionality. This allows for updates or edits on the front end without interfering with the back end. This approach helps teams move faster during projects, is easily integratable with other solutions, and promotes personalization at every level of the customer journey.
While you’re probably no stranger to APIs, you should know that they strengthen your business’ commerce technology stack by leveraging microservices that own their particular area of expertise. To put it simply, the headless approach upholds best-of-breed API architecture, and cutting-edge businesses are now constructing their tech stacks through these point solutions that are nimble, customizable, and data-driven to deliver growth.
In response to this growing trend, there are collaborative collectives, like CommX, entering the market. Their objective is to create a linked ecosystem of technology providers that power key phases of the commerce experience to create end-to-end customer journeys.
The Importance of Search Relevance
A (Very) Brief History of Search Engines
If you think about it, search engines are the ultimate index to all the information available on the internet. Since the web contains a large amount of content varying in quality, search engines were introduced to present the most prevalent information to users by weighting, or ranking, websites according to their authority and trustworthiness. Ranking is done by evaluating a series of on-page and off-page signals, such as title tags, headings, and page content, and ensuring mobile-friendliness and fast-loading pages. These signals allow search engines to determine which pages are worth presenting versus the ones that are not.
Although the subject is up for debate like much of tech’s history, experts trace search engines back to 1990 with the release of Archie by McGill University student Alan Emtage. Whether it was the first of its kind or not, Emtage’s contribution paved the way for pivotal developments in commercial versions of search engines, which eventually included the likes of Excite, InfoSeek, Lycos, and Yahoo. Once Google.com was registered as a domain name in 1997, it would redefine how people saw search engines forever — by upholding relevance above all else.
While there are many tactics to appeal to Google’s algorithms, your business needs to concern itself with the on-page experience, and not just ushering the seeker to your site. As websites, like yours, continue to grow their content and product offerings, seekers are now increasingly relying on the site search bar to show them the way and keep them on the page. The NLP beneath your site’s search bar should deeply understand every word typed into it to put the right information in front of the right person at the right time.
Why Does Search Relevance Matter?
With more customers trusting search bars for findability purposes, it might seem obvious why search relevance matters, but let’s dig a little deeper. Like many workflows, search has an inherent scaling problem. Not only does your company have to consider all of its products and services with their price listings, inventory and availability data, and item descriptions, but your business also must examine the individual consumer with their hundreds of different characteristics before processing it all to present personalized results — at scale.
Although search engines have revolutionized the way that we find and consume information, options can often overtake relevance. But a merchandiser, or product manager in the case of B2B, doesn’t have time to manually consider all of these elements, and that’s where self-learning, AI-powered search stands to make its most crucial impact. Search relevance will tame the oversaturation of information online — a place where everything is available, but nothing can be found — and add up for the following entities in a big way:
The Seeker (Your Potential Customer)
Here’s something to chew on: In North America, there will be an 87.5% uptick in rewarding non-transactional behavior within the next three years. As we move away from that “quid pro quo” model of shopping online, businesses have to organically connect all of the stages of the purchase journey and invest in customer experiences (CX) that prioritize the seeker’s purpose.
There are multiple factors behind the evolution of consumer expectations. The disruptive nature of the internet — along with all the technologies that succeeded it, such as cloud, mobile, social, and AI — is one of the many reasons that prospects now appreciate experiences over material possessions. Your business must cater to these preferences by understanding a seeker’s explicit (what they type into a search box) and implicit (what they click on a page of results) intent to convert them into a customer.
When it comes to site search, businesses often find that they want to make small, manual fixes to the way results are displayed. That’s fine at first, but these patchwork fixes can snowball into major obstacles for your team. Ultimately, these changes can become time-consuming to maintain as your product catalog grows and customer behavior changes. The rules you’ve created will only overlap and have contradictions — that’s where automation comes in handy.
An automated search solution will keep your commerce team operating at full speed and prevent you from overloading one person or department with too much specialty information. The level of findability provided by NLP and ML can take your digital merchandising strategy and product placement to a whole new level.
Like shoppers, businesses are adjusting to an increasingly digital way of life. Since it’s easier to discover and engage with brands we’ve never experienced, there’s more competition than ever before. Pair the pandemic-accelerated move towards digital with supply chain issues and lockdowns, and suddenly, we find ourselves amid “The Big Switch,” where digital channels are the primary way to communicate, and direct consumer relationships are everything.
From automotive and banking to healthcare and manufacturing, AI — like NLP and ML — fills in voids that businesses experience every day. It can do the same with your site search and create top-notch digital experiences that speak to customers on a personal level, help scale your business, and increase revenue.
The Personalization Play (and How It Increases Revenue)
What Is Personalization?
Personalization is one of those common industry terms that could be described in hundreds of ways. Bloomreach defines e-commerce personalization as “the responsible use of commerce data to better know, guide, and wow your customers with experiences so relevant and contextual that they feel like magic.” Since data privacy and protection discourage the use of third-party data, many brands are pivoting their personalization strategies to rely on zero-party data, which is provided directly by the customer, and first-party data that is drawn from your company’s channels and sources.
Although many people think of personalization as the sole domain of marketers, every touchpoint of a digital experience should make the seeker feel understood and valued as an individual. Not only should your personalization strategy lead them through the product discovery process, but it should also encourage brand awareness and loyalty in today’s low-loyalty environment. By incorporating implicit personalization, or a combination of those retrieval and ranking algorithms we discussed earlier, conversions are optimized from the beginning of the prospect’s journey — at the search query level.
Personalization’s Significance in Search
Although it’s vital to think about your search bar in your strategy, it’s just as crucial to consider the seeker — who they are, where they want to go, and what they are hoping to find. They often don’t have the time or patience to sift through hundreds or thousands of products, so give them a better experience by surfacing the items that personally speak to them within a matter of seconds. When it’s all said and done, you need both relevance and personalization to deliver successful customer experiences.
While search engines like Google attempt to deliver relevant information, social media companies such as Meta, set the precedent around personalization. Sure, intent matters, but it’s nothing without considering the person behind it. Yet, despite 85% of businesses saying they are providing these “somewhat personalized experiences,” only 60% of consumers agree that brands are actually delivering on this promise.
Search Relevance + Personalization = Revenue
As you’ve learned, there is more to site search than just the technicalities of it all — what tends to get lost in translation is the value of such a service. Certainly, you’ll want a return on that investment when you devote a portion of your spend to any solution. You’ll also want to ensure that you’re allocating your budget to the best tool(s) for your short- and long-term goals. Based on the data collected from CommerceNext and CommX, respondents believe that both personalization (61%) and site search/guided navigation (57%) are the website experience upgrades with the most potential to drive growth, conversions, and revenue in the immediate future.
By committing to a seeker-centric mindset and investing in personalized site search, your business can improve revenue per visit (RPV), average order value (AOV), and add-to-cart rates. Site search also converts higher than browsing, meaning that 15% of your visitors using the search bar today should account for 45% of your revenue. If you're seeing anything less, it's time to consider a new search solution.
Personalization Search Relevance IRL
So, we’ve talked a lot about search relevance, why it matters, and how it can impact your company’s revenue, but at the end of the day, words are just words. What we mean is that it might be more significant to see search relevance in action. Let’s start by introducing one of Bloomreach’s partners, who is a well-known and respected player in the industry: SAP.
Going Beyond “Good” Search Experiences
At Bloomreach, we understand that building relevant, personalized experiences isn’t all you need to succeed in the commerce space. Actionable steps, such as buying, do matter, too. Otherwise, you’ll have nothing to show for your efforts. Although Bloomreach’s mission is to provide relevance and personalization that’s algorithmically optimized for lucrative business outcomes, we rely on our partners to complete other phases of the customer journey.
SAP Commerce Cloud, for instance, is just one of the many products available in the SAP universe and makes a perfect partner for Bloomreach’s objectives. Bloomreach Discovery — which offers the four core modules of search, recommendations, merchandising, and SEO — seamlessly integrates with SAP’s back-end commerce services to create an end-to-end shopping experience when connected to any front-end platform of your choice (like SAP Spartacus, for example). Located in the SAP Store, Bloomreach Discovery nurtures the seeker’s intent and converts them into a customer. Then, SAP assists the customer through the purchase and fulfillment phases of the journey.
Here’s how some of Bloomreach and SAP’s customers took advantage of our partnership:
Canadian Tire’s Multiple Subsidiaries Team Up With Bloomreach and SAP
Everyone in Canada has heard of the prolific Canadian Tire brand name — but what they might not know is that Canadian Tire has multiple subsidiaries, including Atmosphere, Mark’s, and SportChek. Like any major entity managing multiple brands, Canadian Tire wanted to create consistent digital experiences across all of its e-commerce websites to convert more online visitors (or seekers) into customers. The company was especially concerned with making its wide-ranging products, including auto parts, homeware, sports equipment, and apparel, more accessible to the seeker.
The Canadian retailer approached its targeted outcome from a product discovery standpoint and focused on findability through — you’ve guessed it — search relevance. Bloomreach Discovery’s site search and merchandising modules served as the perfect solution and provided Canadian Tire with the NLP, advanced attribute extraction, and past visitor behavior intel the company needed to succeed, increasing conversions across all of Canadian Tire’s subsidiary brands by 20%.
As Bloomreach Discovery is a part of SAP’s Industry Cloud program, the partnership between Bloomreach and SAP played an integral role in Canadian Tire’s success. After customers found what they were looking for through Bloomreach’s AI-driven search bar, SAP Commerce Cloud served the transactional portion of the customer journey. While this use case highlights the success of search relevance, it also clearly shows the value of a harmoniously integrated e-commerce ecosystem, where tech solutions can enhance digital experiences together in their respective areas of expertise.
Annie Selke Leverages Bloomreach and SAP for Increased Brand Loyalty
The Annie Selke Companies, a relatively newer company comprising the lifestyle brands Pine Cone Hill and Dash & Albert, is a business founded on making people happy. They achieve this by designing beautiful, quality-conscious products that bring joy to people’s homes. To reach its next stage of business growth and further commit to its company mission, Annie Selke wanted to increase brand awareness and loyalty. Their approach would be similar to Canadian Tire: creating frictionless and personalized online shopping experiences.
Annie Selke started with product discovery, believing it was important to display its products in a way that appealed to the seeker. As they had attempted to handle search internally before, the American-based retailer knew they couldn’t achieve their objective without the help of Bloomreach and SAP. These powerful partners assisted Annie Selke in its strategy to present the customer with the correct product in the place that they’re looking for it.
In the first six months after implementing Bloomreach’s search and merchandising modules, Annie Selke saw a 40% increase in revenue generated from search and a 34% lift in all its merchandising activities. While improved revenue was certainly a goal of Annie Selke’s, the retailer was also very pleased with the brand trust they created through its thoughtfully constructed product discovery and transactional processes.
Search relevance is relevant to your customer, and it needs to be a core part of your business strategy moving forward. The seeker behind your potential customer doesn’t want to be part of lumpy and impersonal segmentations with little true insight into who they are and how they exist in this world. When you think of marketing’s past contributions, you should think of this loosely targeted segmentation.
Forward-thinking commerce professionals, spanning from engineering and merchandising to marketing and customer relationship management (CRM) departments, will invest in on-site personalization that understands the seeker and ensures the offerings you present to them represent your best perception of their intent. These trailblazing businesses will put the seeker at the center of the experience.
By combining the seeker’s intent, principles, and motivations with search relevance, your business will build a solid seeker-centric approach that intentionally converts them into loyal customers. To get started with your search relevance strategy, check out our latest blog on Bloomreach Discovery’s pricing, or take an interactive tour of our solution.