Stronger Consumer Engagement and Higher Sales for eCommerce – Why Improved Search Functions Lead to Better Results

Precision makes all the difference when it comes to search results. In fact, close to 80 percent of people will leave a site and never return after searching for something twice unsuccessfully. Knowing this, companies that have been able to effectively implement accurate search solutions tend to retain their customers at much higher rates. According to Salesforce data, customers who use search spend more than twice the amount on mobile and desktop retailer’s sites compared to customers that do not use search. 

Despite the numbers overwhelmingly supporting the need for solid search solutions, several ecommerce players are still hesitant about investing proper time and resources into improving their search functionality.

The Overlooked Potential of a Powerful Search

Companies continue to overlook the benefits of search on their customer metrics. Typically, the majority of their focus and resources are funneled into things like site layout and usability, clean product categories, and monitoring inventory issues. These variables are incredibly important, however when paired with a poor search function all that work can go to waste. It’s hard to buy what you can’t find. 

Search solutions can also provide great insight for decision-makers behind the scenes in addition to the navigation benefits it provides consumers. Marketing managers and data analysts are constantly inundated with information. When sales are lacking, finding the root cause can be extremely difficult. Looking at the number of searches made tied to the bounce rate is one key metric that can uncover problems within the search function if it’s not producing quality results. 

As a result of the pandemic, e-commerce competition is much higher. An orthodox search tool with limited functionality no longer gets the job done in this highly competitive space. The modern mobile consumer expects every business interaction to happen efficiently and accurately—and search is no exception. 

The Bottom Line for Revamped Search Function

Customer engagement is front of mind for every ecommerce platform. When people find items quickly, can sort easily, and receive relevant recommendations, then search is providing irreplaceable value. 

Transitioning from a traditional search solution can be a long process, but it’s possible to make small improvements over time. Every refinement to the tool’s capabilities and accuracy will ultimately lead to higher customer satisfaction rates and purchasing results. Enhanced usage of the search bar also provides companies with critical data that can be used to analyze revenue generation. Consider the revenue Amazon derives from its product recommendations, which is driven by its search and buying pattern data. The way an ecommerce firm sets up their search taxonomy relates to the quality of their “product recommendations” engine, so it provides long-tail benefits beyond improving individual search results. 

Breaking Down the Back-End Tech

Wayfair is a perfect example of an industry leading search and sort tool. A customer can find or build their perfect product with search tools that help them filter by color, material, and style.. It’s a quality tool, but far from the best available option. The next level of search would be to enable granularity through the search bar with regular syntax. Ideally, customers would be able to type exactly what they want, and all the filtering happens on the back end, without manual inputs.

Top search solutions providers will offer a range of improvements and features for search, including:

  • Recognizing synonyms and colloquialisms to avoid customers reaching dead ends
  • Search platforms should feed into custom ranking processes for optimal ranking of search results for better retention and more sales
  • Type-ahead suggestions to speed searching and offer best-match keywords for customers who might be unsure of what they need
  • Highlighting functions that bring the important parts of a site to a visitor’s attention based on their searches

Machine learning technology can help vastly improve search function relevancy for users. For example, site search leader Lineate works with ecommerce companies to provide the best results that are tailored to their specific needs using machine learning. Customizable search functions can use machine learning to refine itself over time to ensure the same information is presented regardless of who is doing the searching, and specifically how they search. 

This dynamic tool can help improve results for different groups of people who think about products and perform searches in different ways. 

Ecommerce firms that commit to improving their search functions through technology, are giving themselves a great competitive advantage by utilizing the right tools to complete the customer journey. Through stronger search functions, companies are solidifying their trustworthiness and providing the satisfaction customers are looking for. With improved search, e-commerce players can look forward to completing more sales, gaining referrals, and ultimately increasing brand advocacy. 

Author Bio
Elizabeth Gallagher is the Chief Revenue Officer at Lineate—an NY-based custom software development company—where she oversees marketing, sales, and product development. Previously, Elizabeth was Co-founder and CEO of the award-winning ed tech company, Pixeldream, where she brought dozens of high revenue technology products to market for leading organizations including McGraw-Hill and Pearson.