November 12 2021

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Understanding Semantic Search with The B-SMART® Method

As Google and other search engines continue to evolve, it is even more important to understand a user’s intent and meaning behind their searches. The search engines are attempting to understand language in a user’s search query the way a person would. Understanding semantic search helps deliver users more relevant results for the information the user wants. This can affect how we optimize our keywords and our content.

Semantic search is the way search engines are attempting to better understand search intent by taking into account the context around a search query’s meaning. This makes for a personalized and relevant search experience.

As SEMRush puts it: “In short, the main thing to understand [is] that semantic search uses the intent, query context, and the relationships between words to produce the most accurate search results.”

For instance, current news about a subject, the user’s location, and previous searches can all impact what results are going to come up.

If you are interested in steel prices and did a search on Google for “steel prices” before semantic search, the results would likely have included a history lesson on steel prices. Now, Google recognizes that most people who are searching “steel prices” are likely looking for current steel prices.

The B-SMART® Method can help search engines understand the relationship between phrases as it helps provide more context in the content developed using it. Each letter of the B-SMART® Method represents a part of the bigger picture that tells the story of what our clients offer and for whom. Brand, Size, Shape, SKU, Material, Area, Application or Industry, Requirement, and Type are all elements that are related and connected to one another.

To learn more about The B-SMART® Method, download our B-SMART® checklist.

Separate, each element does not have the same meaning to a user as when combined. Using two or more of these details helps the search engines to identify a product or service real users would be looking for.

For example, a search for a Brand like Caterpillar would not deliver the most relevant results as would a search for tires (Type) for a forklift (Application) for their Caterpillar M20 (SKU) with a weight of 2000 lbs (Size) and a drive tire of 16 1/4 x 5 x 11 1/4 (Size). Having all this information on a relevant topic page about Caterpillar would help users find the right page, whether they are searching for “caterpillar forklift tires” or “caterpillar m20 tires.”

In this example, the first, more specific search yields the type of search response you would want if you were looking to purchase Caterpillar m20 tires. The second, more general search, gives a broader amount of results that may or may not give you what you are looking for.

What This Means for You

With semantic search, Google is attempting to understand the relationship between phrases to be able to offer the best results for its users. We should make sure our content has a clear focus, and we should create content that is high-quality and not just focused on keywords. We should be focusing on topics and including phrases that are related to each other within the content.