Search Intent Best Practices

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ℹ️ What is search intent?

Search intent is the reason behind a person’s online search. It’s about understanding what someone wants to find when they type a query (a word or phrase) into a search engine and where they are in their buyer’s journey. Ensuring your content matches what people are looking for increases your chances of ranking higher. Common Types of Search Intent

• Informational keywords (like “choosing comfortable running shoes” or “how to pick a running shoe”) indicate people are looking to learn more about a topic, product, or service.
• Commercial keywords (like “adidas ultraboost vs nike react”) indicate people want to compare multiple products or services.
• Transactional keywords (like “adidas ultraboost for sale”) indicate people are ready to take action on a website, like purchasing a product or service.
• Navigational keywords (like “nike.com returns”) indicate people are looking to visit certain websites or pages.

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ℹ️ What should I look at to understand a keyword’s search intent?

Understanding search intent is a key step in keyword research. To understand the search intent behind a keyword, look at:

• The keyword’s length.
• Whether the keyword is branded or unbranded.
• The keyword’s top search results and result types.

Keyword Length

• Keywords that are only one or two words (like “shoes” or “running shoes”) are called head terms. They are usually popular but have vague search intent because they lack specificity regarding what the user is actually looking for.
• Keywords that are three words or longer (like “most comfortable running shoes”) are called long-tail keywords. They are usually less popular but have more obvious search intent because they include clues to what the user is actually looking for.

For example, the search intent for “shoes” is vague because it can mean many different things, like sneakers, boots, or sandals. When people search for “shoes,” they might be looking for all kinds of information, from buying shoes to learning about them. On the other hand, when someone searches for “most comfortable running shoes,” it’s much clearer. They’re trying to find running shoes that feel really nice to wear and are looking to research or compare products. In a study, Conductor found that once a long-tail searcher arrives at the website, they convert at a rate more than 2.5x higher than visitors who searched on head terms. Branded vs. Non-branded Keywords Branded keywords are search terms that include the name of a specific brand, company, or product. When people use branded keywords in their searches, it typically indicates a high level of search intent related to that particular brand. The search intent is often navigational or informational. They are usually looking for a specific website, product, service, or information related to that brand. For example, someone searching for “Nike store locator” likely intends to find information about Nike store locations to call or visit. Non-branded keywords are search terms that do not include any specific brand names. They are typically more generic and can relate to a broader category or topic. The search intent for unbranded keywords can vary widely. Top Search Results Take a look at what content is ranking for the keyword. Typically, the top search results will all fall into the same search intent group. This gives you a good idea as to what the search engine is considering a valuable answer – Are the pages educational or instructional? Are they product pages? Or something else? For example, look at the top results for “best gifts for toddlers.” All of the top results are gift guides from established media publishers. You can also look at what result types appear for the keyword. Answer Boxes are usually associated with informational searches and Shopping results for transactional searches.

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💡 Best Practices for using Conductor Intelligence to research Search Intent

The content you create should map to the intent your customers have when they search. To accomplish this with Conductor Intelligence, the Search Intent column in the Related Keywords table in Explorer’s Topic reports shows up to two intent labels based on what our classifier identified as the strongest match or matches. You can filter by different intent, combine with other filters, and save filters that use intent. Here are some potential ways to use this data to take action on your content: ❔Informational Consider: Building topical authority and capturing users early in their journey. Filter FOR informational intent to identify opportunities for comprehensive guides, how-tos, and educational content. Identifying bottom-of-funnel content opportunities. Filter OUT informational intent to focus on the topics where users are closer to taking action rather than just researching. Here’s how you might use this… A content strategist at a cybersecurity SaaS company is tasked with improving brand authority. They filter FOR informational intent and find searches like “how to prevent phishing attacks” and “best cybersecurity practices for small businesses.” Using these insights, they create a series of in-depth blog posts, webinars, and downloadable guides to capture early-stage researchers and nurture them into potential leads. ⚖️ Commercial Consider: Targeting comparison and evaluation-stage searches. Filter FOR commercial intent to generate review content, product comparisons, and buyer’s guides. Focusing on either purely educational content or direct conversion opportunities. Filter OUT commercial intent to remove middle-of-funnel evaluation terms. Here’s how you might use this… A product marketer at a B2B software company launches a new CRM tool and needs to attract buyers in the evaluation stage. They filter FOR commercial intent and discover searches like “HubSpot vs. Salesforce comparison” and “best CRM for startups.” To capture these potential customers, they develop detailed comparison pages, customer testimonial videos, and an interactive quiz to help prospects choose the right solution. 🛒 Transactional Consider: Prioritizing product pages and conversion-focused content. Filter FOR transactional intent to identify terms where users are ready to make a purchase or complete a specific action. Building brand awareness and authority. Filter OUT transactional intent to focus on educational content rather than immediate conversion opportunities. Here’s how you might use this… A digital marketing manager for an e-commerce company selling fitness equipment wants to optimize their product pages. By filtering FOR transactional intent, they identify high-intent keywords like “buy adjustable dumbbells online” and “best price for resistance bands.” They use this data to refine product descriptions, add customer reviews, and create targeted paid search campaigns that drive conversions. 🧭 Navigational Consider: Auditing your site’s key landing pages and monitoring competitor brand terms. Filter FOR navigational intent to find queries that users frequently use to access pages directly. Getting clarity for your content-driven ranking potential. Filter OUT navigational intent to focus on true organic opportunities by excluding branded searches where users already know their destination. Here’s how you might use this… An SEO specialist at a large hospitality chain might want to ensure their brand dominates branded search results. They filter FOR navigational intent and notice frequent searches like “Hilton rewards login” and “Marriott cancellation policy.” With this insight, they optimize key landing pages, improve FAQs, and create structured data to ensure these searches lead directly to the correct pages, reducing friction for existing customers.

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What sets Conductor’s Search Intent apart from other data providers?

Intrinsic Search Intent Other vendors in the enterprise SEO space have search intent classifications, but we developed our own methodology using AI to not just recognize the words people use to search (what we call “reflected search intent”), but the meaning behind the words—the “intrinsic search intent”—which reflects more nuance and understanding of less common language usage, leading to more accurate and complete assessment of search intent. When data providers focus on only reflected search intent, they can fail to account for how people use language in nuanced ways that may mean different things, but appear the same. This reliance on search term frequency leads to issues like difficulty differentiating Commercial intent from Transactional intent and the inability to recognize brand names in queries. For example, when someone searches “best cleaners nearest”, a data provider that uses only reflected search intent might identify the word “best” as an obvious indication of a Commercial intent. However, using intrinsic search intent signals to determine intent might recognize that same potential Commercial intent but also recognize that the users could be searching for the nearest location for a business called “Best Cleaners”. By recognizing signals in queries that help identify intrinsic search intent, Conductor can provide a more nuanced understanding of what people might really want when they search. In the “best cleaners nearest” example, Conductor could provide both Commercial and Transactional as possible intents where other providers might determine one or the other. This expanded, nuanced understanding of intent can help you create a content strategy that doesn’t neglect potential markets for your products or services. Multi-language Support Your audience probably searches in more than one language, so what good is search intent for only English? Conductor’s AI solution for intent also supports non-English languages better than other providers that attempt to provide search intent. Earlier approaches to determining search intent used natural language processing (NLP) models that were trained on English libraries. Because it’s more complicated to train an NLP model for each language, those English models were then applied to other languages, leading to intent classifications that didn’t accommodate the cultural differences and nuances inherent in unique languages. The reason Conductor can support non-English languages better is that our solution, by nature, includes language understanding, and it is not language-specific to begin with. So it’s not just that we’ve “expanded” support to other languages, but it’s multi-language from the ground up. This means you can account for the cultural differences and nuances represented in different languages—so you always meet your customers on their terms, not just on yours. Want to learn more about industry best practices around keyword research? Take the SEO Enablement: Keyword Research video course.