How search results exactly match the search intent of the user
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 search relevance. Search relevance is an important part of search engine optimization (SEO). The better the search results, the more likely you are to be satisfied. The more satisfied you are, the less likely you are to become frustrated and leave.
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Understanding Search Relevance
Search relevance is all about providing the right search experience to the user. It is a measurement of the accuracy of a search query and the results of that query.
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.
Why Does Search Relevance Matter?
Search relevance 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:
- Exact Search Results: This search result is an exact match to the search query. There is no vagueness to the question. The search engine matches the words in the request exactly. This search result is the most desirable because it is what the user was looking for.
- Broad Search Results: In this search result, the search engine returns results that are similar to the search query. There is no way to know if the results were an exact match, but the results are close enough to the original search request.
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 History of Search
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.
How Modern Search Engines 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:
- Keywords: Keywords are still important, but they are no longer the only factor that determines how relevant a site is.
- Link structure: This is the way in which sites link to one another. Links to other sites can be powerful indicators of how relevant or helpful a particular site is.
- User information: Search engines collect data about the user’s search intentions and search history. This data allows the search engine to predict user behavior and provide results that the user is more likely to click on.
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.
- Page structure: This describes the content of the page and how it is arranged. This is particularly important for eCommerce sites where the layout and organization of information are critical to a successful conversion.
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.
The relevance of search today
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.
- Client history: Companies keep comprehensive databases of their customers. They look to these databases to help them provide customized suggestions. This helps the user when searching as the results are more likely to match the intent.
- Keyword research: This is one of the most important aspects of search engine optimization. Identifying the right keywords and ensuring that they are used in copy throughout the site is critical to success.
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.
- Design: The layout and design of a site can significantly impact search relevancy. Search engines are looking for pages that are well organized with plenty of white space and content that is clearly marked for the user.
- Mobile optimization: Google has made it clear that mobile optimization is just as important as desktop optimization.
- User experience: The way users interact with sites affects how relevant a site is. Search engines look at how many pages people visit, how long they stay on a site, and whether they return to the site.
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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