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Search engines are one of the most indispensable tools in our daily lives. Case in point: Google processes over 3.5 billion searches per day and 84% of searchers use Google 3+ times a day according to Moz. Before search engines, we often struggled to find information, and sometimes we conceded defeat, but with search, we now expect immediate answers to our questions.

Where Search Came From

1953 american league mvp - Google Search
1953 American League MVP in Google Search Results

Believe it or not, there was a time when a heated debate over who won the 1953 Major League Baseball American League MVP award included a spirited discussion of a few potential players’ individual stats. Without access to a definite answer, we would think of who had the highest batting average, home run, RBI, or stolen base total that year and make an educated guess. We could feel confident in our evidence-based conclusion given the information available, but we couldn’t be certain. 

Now, failures of findability are no longer acceptable given the technologies at our disposal. Subjectivity, strong opinions, and even logic have largely been replaced by an unapologetic devotion to validating facts.

Immediate information retrieval on the web really only became possible once technology allowed for scalable scanning, indexing, and categorization of content using language-based queries. The developing sophistication of web search, correlates directly with the arc of the Internet itself. Use cases for findability and discoverability eclipsed use cases for linear, direct traffic to webpages. 

"Just as the GPS replaced the compass, we've realized that it's far better to arrive exactly where we want to go than to wander in search of our destination."

We’ve deliberately referred to search as ‘web search’ because we strongly believe the behavioral patterns we’ve witnessed reflect both organic search (search engines like Google) and on-site search (a website’s search bar that just scans the site).

Before web search became sophisticated, to find a pair of black golf shoes at a clothing website, you would navigate to the ‘footwear’ section, then to the ‘athletic shoes’ section, then to ‘golf shoes,’ and then visually examine options to find a black pair.

The association of ‘shoes’ with the ‘footwear’ section or ‘golf’ with the ‘athletic shoes’ section is similar to figuring out who won the MLB AL MVP based on their home run or RBI totals. These are contextualizing aspects of a topic that help us arrive at an answer to our question.

Good web search experiences have allowed users to bypass these contextual deductions and associations of reason. We forecasted the ascending popularity of search as a findability mechanism several years ago, and these shifts in web behavior patterns are not going away, so it’s imperative to understand and appreciate users’ rapidly diminishing patience.

Optimizing for Contextual Signals

Optimizing your website for organic search and for on-site search are not mutually exclusive exercises. Popular site search products like Solr and Coveo utilize many of the same algorithmic natural language processing signals that search engines like Google use to parse and categorize webpages. These include parsing meta titles, page headings, image alt text, and body copy.

But there are some key differences. Where search engines often rely on backlinks to a website or webpage to evaluate its eligibility for ranking against a search term, site search products often rely on underlying site taxonomy and tagging architectures used to categorize your website’s content. In the previous example, the website would potentially have the black golf shoes categorized under taxonomies of category=footwear, type=athletic, sport=golf, and color=black. 

Optimizing for the Likely Motivations of Your User

Successful searches often lead people to increase their use of web search platforms, as they make more complex or hyper-specific queries. This can be traced to the sophistication of web search engines and their ability not only to interpret a query string’s relevance to a results, but also the user’s underlying intent.

While users expect search engines to retrieve the most recent version of a given piece of content based on their relevance algorithms (Google’s favoritism towards freshness dates back to 2007), you may need to finetune your site search to award more weight to recency or to demote stale results. Advanced search features can be leveraged by users to override these tunings, but it’s important to consider the use cases for your content before defaulting to raw relevance in your site search configuration.

Building Trust and Reliability

Examining your on-site search query patterns regularly can be enlightening. Not only does it reveal what your users are looking for, it can often reveal user experience flaws in your site’s navigation or other wayfinding mechanisms.

Additionally, high search volumes for a given term but low click-through rates may suggest there are flaws in your on-site search configuration. This practice can also be helpful when examining your organic search queries in Google Search Console to understand where there are large disparities between search impressions and clicks.

Some of the common reasons for these disparities in on-site search include:

  • Recency bias (or lack thereof): This occurs when your site is defaulting to the most relevant result based on the keywords of the query instead of the most recent version of a given web object.
  • Content/document type: This is another instance where your site’s relevance algorithm may be awarding too much weight to the keyword rather than the authority of the document. For instance, if your site search is returning a blog post instead of a product or service page, you may be missing out on traffic directly correlated to your monetization strategy.
  • True content gaps: This occurs when there is a pattern of searches around a given topic but your site lacks content relevant to that topic. These cases require a level of analysis as to whether the topic aligns with your brand’s core offerings, but this is one instance where your audience can help guide your content strategy.
  • Synonym disparities: These are cases where the phrases you’re using in your content conflict with the way your audience describes the same topics. For instance, if your healthcare website has many great articles on ‘melanoma’ but your audience is searching for ‘skin cancer,’ you may need to either optimize for the more commonly searched phrase or tune your site search platform to correlate those phrases as being synonymous. Synonym disparities are a great use case for organic search keyword tools like Google Trends or Keyword Planner.

It’s important to optimize your organic and on-site search because a dead-end search could frustrate users, lose you customers, or a prevent key decisionmaker from assessing your brand. These are all competitive disadvantages you can avoid if you optimize your website for organic and on-site search for contextual signals, finetune based on user intent, and leverage data on how your audience searches to improve your content and the ways people can find it.

Given how often people leverage search in their daily lives, they expect great search experiences in their digital interactions. So your organization must adapt your website’s user experience and content accordingly to ensure users find relevant content that matches their intent. Learn more about our capabilities in experience strategy and experience design or reach out to Velir for help improving your site’s search experience.

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