Obviously, that’s not how online search works. Online shoppers don’t function like robots. Search engines, on the other hand, are robots that do precisely what they have been programmed to do — and since everyone shops differently, search engines perform billions of search queries each day based on each consumer’s unique terms and search preferences.
But search is only the first step toward conversion. When consumers eventually establish a connection with a prospective ecommerce retailer, they have to be able to quickly locate the products they desire and navigate a path to checkout. Any barriers to sale (e.g., price, lack of adequate product information) can be disastrous since websites are one-dimensional and incapable of providing traditional retail responses, like a salesperson can, to customer concerns.
The result is that ecommerce retailers live with the constant fear of shopping cart abandonment — the very real possibility that shoppers will visit their site, participate in the online shopping experience, and then ultimately abandon their cart. Average cart abandonment rates hover around 65% and can surge even higher for mobile commerce sites. However, many retailers often overlook an even larger looming issue in the abandonment realm.
The Problem Of Site Abandonment
Although most ecommerce brands and retailers are extremely sensitive to the impact of cart abandonment on overall revenue and conversion rates, significantly fewer are concerned about site abandonment. In a site abandonment scenario, shoppers don’t immediately find the products they are looking for and quickly leave the site without engaging in any shopping activities.
Many times this is due to a text-based search bar, which does not understand human terminology. Sites with a text-based search bar report an average 40% site abandonment rate, with site visitors viewing six pages or less per session. In comparison, providers that feature a semantic-based search bar report a much lower site abandonment rate (2%) and site visitors view an average of 16.2 pages per session.
While it’s helpful for ecommerce retailers to identify strategies to minimize cart abandonment and to reconnect with shoppers after they walk away from their carts, it’s even more important to develop a strategy that addresses the problem of site abandonment. Why? Because it saves retailers the time and money that retargeting campaigns cost to bring back customers who leave the site after establishing little connection.
Leveraging Search To Reduce Site Abandonment
Site performance is a core driver of ecommerce success. Across the board, websites that present first-rate user experiences, optimized conversion paths, and other enhanced features outperform sites that fail to strategically combat performance-related obstacles. By targeting reductions in site abandonment rates, ecommerce retailers can significantly improve site performance by ensuring that larger numbers of consumers participate in the online shopping experience. Site search plays a central role in mitigating site abandonment and can be leveraged to deliver new life — and more conversions — to your ecommerce site.
Here are some ways to reduce site abandonment using search:
1. Enable a Semantic-Based Search Platform:
Semantic-based search is an intelligence feature that acts as a bridge between a consumer’s unique search terminology and an ecommerce product catalog. With a semantic-based search platform, consumers can speak to the search engine using their preferred terms or search queries. The platform intuitively understands what the consumer is looking for and displays only actual, relevant products.
On most ecommerce sites, it’s easy for shoppers to find search results for the top-selling products. These products are usually displayed prominently or promoted by the retailer through ads, so customers don’t have to rely solely on search to locate the most popular products.
But typically, 70% of a brand’s products are embedded deep in the ecommerce catalog. If the merchant’s product line contains thousands of unique SKUs, it can be difficult for shoppers to quickly locate specific products. Semantic-based search platforms minimize site abandonment by understanding what shoppers and searchers are looking for and quickly delivering search results, even for products that are warehoused deep within the site.
A semantic-based search approach can also be very effective in helping shoppers locate products based on long-tail search strings (e.g., “men’s white Adidas shoes size 13”), enabling shoppers to identify very specific products via a diverse range of possible search terms. This allows shoppers to enter what they want in the search bar as if they were speaking to an actual salesperson.
With consumers embracing mobile and other web-based technologies in record numbers, more and more companies are rushing to sell their products online. For most etailers, a robust, semantic-based search tool delivers a key competitive advantage. If your company doesn’t carry a specific product, site searchers will never see a blank page. Instead, they will receive a list of the best-selling products in their desired category.
The measurable impact of semantic-based search solutions can be substantial. Recently, Walmart converted to semantic on-site search technology and experienced a 10%-15% increase in completed purchases after shoppers searched for a product using the new search engine.
2. Leverage Intelligence Features and Functions:
Semantic search isn’t the only application for intelligence features and functions in an optimized ecommerce strategy. There are many other tools, including auto-complete and algorithms, which leverage intelligence functions to reduce site abandonment by providing shoppers with faster and better search results.
Many ecommerce merchants mistakenly limit their view of auto-complete as a user resource that completes fragmented search queries. But the intelligence capabilities of a full-bodied search platform should enhance the search experience even further by delivering images of products and other content as part of the auto-complete function.
Likewise, search algorithms can be used to improve product pairings associated with the customer’s desired products. For example, at Celebros we use natural language processing (NLP) technology as part of our concept-based search platform. Leveraging 250 different NLP-based algorithms, the platform gives ecommerce retailers the ability to source highly relevant search results to customers using their unique search terms and other variables.
The best site search solutions are designed to improve the intelligence function with use. As more site visitors use the search engine, it should become smarter and more accurate based on machine learning — automatically adding synonyms or adapting algorithms based on historical on-site behaviors.
3. Use Search to Improve Cross-Selling Capabilities:
It’s not uncommon for customers to search for products that are out-of-stock or items not contained in your ecommerce catalog. In a brick-and-mortar context, the usual response to unavailable product requests is for a salesperson to cross-sell, moving customers to similar products rather than watching them leave the store. With the right tools, it’s possible to perform a similar cross-selling maneuver in an online shopping environment.
Landing pages can be effective cross-selling tools. When customers search for products that are unavailable, they can be automatically presented with a landing page that contains messaging about similar product options (e.g., customers who bought this product also bought X, Y and Z) as well as enhanced content for alternate product options.
Although most cross-sell functions deliver results based on prior searches, the most accurate cross-sell results originate from search engines with custom algorithms. These algorithms give the platform visibility not only to previous orders, but also to the entire product catalog.
The measurable benefits of algorithmic landing pages and other search-based, cross-sell features are reduced site abandonment rates and increased conversions. Rather than overwhelming customers with a large volume of unrelated product choices, these features deliver only related product options, significantly improving the likelihood that shoppers will convert on cross-sell suggestions.
4. Monitor with a Live Website Analytics Tool:
Live analytics are valuable resources for monitoring and evaluating on-site behaviors. The best analytics tools allow you to create heat and click maps that show what site visitors are viewing and clicking on in your ecommerce website in real-time.
In the brick-and-mortar world, retailers modify their selling strategy or the customer experience to accommodate real-time changes in customer preferences and shopping behaviors. But online, merchants often find themselves behind the process. Instead of modifying the shopping experience to stem the flow of customers away from the site, online retailers struggle to win back customers after cart or site abandonment has already occurred.
The real-time element of live analytics is important because in addition to improving your understanding of the ways customers interact with your website, it provides the information you need to rapidly modify the online customer experience. Ideally, these changes will result in short-term and long-term wins to your site in the form of increased customer engagement and lower site abandonment rates.
Conclusion
Increasingly, ecommerce merchants are realizing that site abandonment can be just as devastating as cart abandonment, especially when it comes to conversion rates and overall site performance. But by strategically implementing search-based solutions, ecommerce retailers can decrease the incidence of site abandonment by providing customers with substantially enhanced online shopping experiences.
