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Have you ever wondered how search engines work? There are literally billions of web pages available online with millions more being created every year. Search engines do not only help you find a particular site, they also help find content and information within that site.
Consider the fact that search results need to work within a website also helping you find the specific “widget” you’re looking for so that you can make your purchase.
If you’ve been successful in either of these activities – finding the site and finding an item on a site – it is only thanks to the fact that the target or product web pages perfectly matched your search intent. Ensuring that search engines and search functions classify target pages as relevant to the search term entered (so-called search relevance) is an important part of search engine optimization (SEO). The more relevant the search results and thus the target pages you visit, the more likely you are to be satisfied. The more satisfied you are, the less likely you are to become frustrated and leave the web pages.
Tip:
Use the help of the crowd to optimize your search engine/search function. Thousands of Clickworkers rate the results of your search engine/search function according to their actual relevance to the search term and thus help you perfect the algorithms.
Learn more about our Search Relevance service
Optimizing search functions and search engines for search intentions is about showing the user the desired search result. It is crucial for the accuracy of the results to a search query or his search intention.
Online users today are spoiled for choice. Their expectations are colored by the positive experiences they have on sites like Amazon and Netflix where it seems the service intuitively knows what they are looking for.
In reality, those sites have extensive databases of previous decisions and actions paired with powerful algorithms that can help them predict user behaviour. While their search engines are undoubtedly powerful, they are not the only key to their success.
Many companies suffer from this comparison and even more so when internal searches provide results that are useless and irrelevant to the query.
Optimizing search functions and search engines is ultimately about making it easier for the user to find what they are looking for.
There are two types of search results that you should be aware of:
Broad search results are not as desirable as exact results. They are also less likely to result in a conversion or purchase. Users that are provided with results that match their search query are 2-3 times more likely to make a purchase.
The World Wide Web became available to the general public in the early 1990s. It had been preceded by the text-based bulletin board system (BBS) a decade earlier, and the earliest web pages replicated that look.
As time progressed, more pages were added along with graphics, images, and hyperlinks that connected pages together. Finding information in those early days was difficult until the advent of the search engine.
Excite and Yahoo were the precursors to today’s Google and Bing. By “web crawling” – simply reading all of the words on a page – these search engines index and catalogue all of the different websites online.
Early search engines used keywords as a key means of determining how relevant content was. In this way, if a keyword was mentioned multiple times, the page was more likely to be presented at or near the top of search results.
Unfortunately, this method often led to unscrupulous individuals “gaming” the system and decreased search relevancy by providing links to information that did not match the users’ intent.
This often led to user frustration and dissatisfaction as search results did not match expectations. At times this could be resolved through manual means by adding additional keywords that were relevant, but this didn’t always work.
Companies came to realize over time that this was a losing proposition and the promise of the internet was being squandered. Modern search engines were designed and built that are significantly more complex than the ones in the early days of the internet. These search engines look at multiple factors including:
An example of this that is worth understanding is a simple recipe search.
Perhaps you were looking for a quick pasta recipe to impress a new dinner date. When you search online you will find hundreds of recipes. So which one is the right one for you?
In most cases, people will select the first option in the search. If that recipe takes over an hour to make, it probably isn’t the best option for you, so you’ll go back to the search and make another choice. This one takes less than 15min and is perfect for your requirements
Over time as more people select the second option, it will increase in the ranking and move up in relevance in search results.
Search engines are constantly evolving to stay ahead of the curve in terms of providing relevant results to users. The more sophisticated they become, the harder it is for people to game the system and the better experience users will receive.
Optimizing search relevance is something that every company should be concerned about. It is the difference between satisfied customers and frustrated users that will not return. Companies that depend on search like Google understand this and have made search relevance a cornerstone of their strategy.
When a company is able to provide relevant search results, they are able to provide better customer service. The more relevant search results, the more likely a customer is to make a purchase and the higher the likelihood of a conversion.
There are many ways to optimize search relevance.
Search today also uses fuzzy matching with text so similar results can be provided with words that have the same context or meaning. In addition, keywords are no longer restricted to a single word but can match phrases as well.
Search engines continue to evolve. They are more sophisticated than ever before and getting better every day. The more competitive the landscape becomes, the more important it is to ensure that search relevance is optimized.
Recent advances in machine learning, artificial intelligence, and natural language processing have given search engines new ways of providing relevant results to users. These advancements let users make more conversational searches while at the same time letting search engines improve the tracking of search and browsing patterns.
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