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When searching an app or a website, do you know what you really want?
When you’re typing a word or phrase in the search bar, can you picture exactly what you need? Or do you hope the search software is going to sort out those lexical details based on the target keywords and related terms in your plain-English query? Perhaps one of the related searches suggested will help?
Semantic similarity — words that are related in meaning — is one way to facilitate your finding just the right item.
In terms of linguistics, we’re talking here about the semantic relationships between English words rather than words in isolation. With the added context and depth provided by semantics, a search engine can more clearly grasp what you’re seeking — what you really want, your true intent — and then start parsing the semantic relations to accurately suggest your search results.
According to SEO expert Semrush, an example of a semantically related keyword for something like “search volume” would be “keyword research” or “online marketing”. These pairs of words are conceptually related but they’re not synonyms.
Here’s a baseline ecommerce example: you want new high-quality shoes for the gym. You enter “gym shoes” in the search bar. In an online retail scenario, semantic keywords for this might include similar words like “sport shoes”, “sneakers”, “[brand name] shoes”, “trainers”, “running shoes”. Your search results would be aimed at the perceived bull’s-eye, and you might also be shown a content-marketing banner promoting top athletic shoes. You might click the banner, and, after reading happy-customer reviews, put a recommended pair of shoes in your cart but continue to browse.
People are used to the convenience of seamless experiences online. Regardless of how a user’s search query is phrased, they expect the search functionality to understand their intentions from the get-go.
Everyone knows specific keywords are a crucial way online businesses help people find items. That’s been the case for years, as “traditional” search engines have faithfully matched words and phrases to pages containing those specific words and phrases.
The whole field of search engine optimization (SEO) grew out of the need to help businesses include the right keywords in content so their content would rank and appear higher on Google’s search engine results pages (SERPs). As part of setting up SEO strategy, companies have become accustomed to optimizing SEO keywords. And consumers have become accustomed to simply entering keywords and selecting the best search results to locate a desired piece of content.
When it comes to keywords, the role of Google is of course always the first data point. Ten years ago, Google changed its algorithm — the update was called Hummingbird — to better reflect search intent.
Before Hummingbird, it was possible for content providers to overload their text with a single keyword to reliably impress Google’s search spiders (the bots combing the Web and determining SERP ranking). This “keyword stuffing” succeeded in driving people to sites, which were unfortunately populated with painful-to-read, low-quality content.
Semantic keyword facilitation was desperately needed. By providing a handful of secondary, semantically related words (not the same as latent semantic indexing — LSI keywords), you could give Google more richly defined context for your web pages, which for consumers improved both searching and reading experiences.
Semantic keywords fill a pressing need. By incorporating semantically related keywords in your search functionality, you can give your search algorithm additional context on what words mean and how they’re related.
By utilizing semantic relatedness to make meaningful connections about words and phrases, an algorithm can interpret content in a more holistic way. That means you can help site visitors or app users quickly navigate to the content and product pages they want without ruminating too much on what they really want and perhaps retrying their search terms.
There’s another benefit to using semantic keywords as well. Do you know the words your target audience is typically entering in your site or app search box? You can add those words — plus the words that are connected semantically to them — to your product pages and perhaps to promotional content you’re running.
So semantic keywords should play a crucial part in your strategy to ensure that all your content — from product pages to blog posts — is optimized to align with your users’ behavior, trends, and intent. With semantic search factored in, you can provide better search results and better recommendations, giving your visitors personalized experiences that impress them and make them want to come back.
So how does this semantic-search magic work? And more importantly, as an online retailer, how can you optimize keywords — including the semantic ones — for your site or app search? To grasp why semantic keywords are so vital, it’s good to know what makes for quality search. Let’s look at what happens when search goes well and what happens when it doesn’t.
Both on Google and on individual companies’ sites, you may not realize just how much work search engines must do. Whether it’s autocomplete suggesting terms in real time as a query is entered or the search algorithm processing a vague query like “quality headphones” and coming up with a selection of industry-leading, five-star headphones, with competent search, shoppers become successful buyers and repeat customers, conversions go up, and sales can skyrocket. In a recent survey of businesses that invested in search, more than half pointed to search as a strong revenue driver.
What if it doesn’t work this way? For instance, imagine a shopper enters “top quality headphones” in the search field on a large ecommerce site. What the consumer doesn’t know, because they aren’t doing keyword research or understanding the full search parameter picture, is that in addition to some higher-end brands, the store stocks a cheap brand called Quality Headphones.
The search functionality on this company’s site or app is fairly dismal. It hasn’t been optimized with semantic keywords to help distinguish between the query words entered and the meaning behind them. Interpreted literally, the search results are limited to headphones made by Quality Headphones, including low-price ones but also “related topics” — other electronics made by Quality Headphones, including speakers, car radios, and even laptop monitor screens.
Oops. In the real world, where a positively perfect user experience is essential to business success, this level of missing the mark won’t fly. If a shopper in a physical store were shown low-quality headphones after asking for high-end ones, they would probably march off of the premises in exasperation.
The same holds true for a website or app: we’re used to search functionality accurately predicting what we mean when we enter search queries. Presented with “dumb” search results, a shopper may quickly “abandon shop” and go someplace where searching isn’t a trip down a rabbit hole.
How much damage can an unsatisfactory search experience inflict? A lot. Google says 82% of people will avoid a company’s website after a bad search experience.
While poor search is an annoyance on the individual level, it’s a red flag on the enterprise level. Google adds that search abandonment costs retailers globally more than $2 trillion a year; in the United States, this amounts to more than $234 billion.
So getting search wrong can be monumental. Of course, the flip side is that getting search right for your users or shoppers can substantially impact your site or app metrics.
Semantic keyword considerations are crucial to providing quality search experiences, but wait, there’s more. Here are three pluses of incorporating semantically related keywords:
Imagine there’s a reemerging trend for rock guitar music that’s popular on social media. And, as in the past, every kid from Brooklyn to Portland is potentially wanting some Converse sneakers.
As an ecommerce business, you could use “Converse sneakers” as a literal keyword. However, you might want to give this main keyword phrase the status of primary keyword, but also supplement it with a list of words and phrases like “rock band shoes” and “hip trendy sneakers”.
Let’s say you’re a kid searching Google for “Converse sneakers”. You might not know what you really want; you might be browsing. You might even be a clueless parent trying to surprise your teen music fan with a beloved birthday gift.
You might start with a vague list of keywords, searching for “cool sneakers”, “hipster shoes”, or “what sneakers are teens wearing today?”.
If the company has incorporated semantic keywords to the full effect, you might find yourself on a landing page that’s promoting those very all-the-rage sneakers.
Now imagine you’re an ecommerce merchant. A returning customer’s search and purchase history indicate interest in Converse. They’ve read your blog post on cool shoes for the rock scene. As they browse the shoes, they see prompts such as “People who bought this item also buy” and “Similar items”. They select a model and size and check out.
Quick, seamless, personalized shopping is at the heart of today’s consumer experience. Whether you’re using AI with natural language processing (NLP) to recommend relevant products to potential customers or using intelligent search algorithms that provide uncannily personalized results — consumers expect contextually accurate experiences on the fly and that you know their brand preferences.
The good news? You can meet (or beat) these expectations. And with semantic keywords, you can reach a larger audience — a wider pool of people who may be searching by entering different target words.
Here are three ways to provide the right semantically related keywords for your users’ needs:
Congrats — you’re now in the know about semantically related keywords impacting quality search results.
Incorporating semantic keyword considerations in your search and content can help you win over users or shoppers by showing them the most relevant results, ultimately boosting your ROI.
Here at Algolia, as our clients can attest, we can help you with that. We provide scalable, secure enterprise-level semantic search. At the forefront of vector search technology, we harness proven, machine learning–driven semantic search to generate rewarding user experiences.
We’re ready to help you:
Ready to investigate how search that incorporates semantic keywords can lead to a meaningful change in your bottom line? Contact us today.
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