It’s no secret that e-commerce search and online merchandising have a magnetic attraction. These applications morphed into the e-commerce lexicon as “searchandising,” enabling merchants who integrate search and merchandising to realize higher levels of customer satisfaction and returns.
Seventy percent of retailers surveyed in the recent Aberdeen Group benchmark report, “Web Site Search: Revenue in the Results,” said that visitors who used search tools were more likely to convert from browsers to buyers.
Attaining Profitable Clicks
The average conversion rate for nearly one quarter of online merchants was 5 percent or greater. With conversion rates for e-commerce sites averaging from 2 percent to 5 percent, it’s encouraging to see that search tools help to exceed averages for nearly one quarter of the survey group.
Retailers were asked just how they attained these profitable clicks.
Among merchants achieving the highest profits, conversions and returns from their online offerings — termed “Best-in-Class,” 54 percent utilize search as a merchandising tool.
Additionally, 62 percent continually fine tune search for desired results based on user actions, current promotions and collective behavior. Further, 38 percent of Best-in-Class retailers segment search query results using faceted search tools.
These metrics clearly show that leading companies are thinking about their search tools as a way to serve up products and inextricably link their merchandising processes to their product discovery tools.
Merchandisers Shine With Faceted Search
When asked about specific processes used to merchandise to customers, Aberdeen found that 50 percent of Best-in-Class companies use “faceted navigation” to segment products into manageable categories.
Faceted information can be described as topics broken down into categories or attributes (e.g., topic equals “music” and attributes equals “genre, artist, album, song, lyrics”). This method of categorizing information is extremely useful when presenting online search results.
Adoption of faceted search is on the rise among online retailers and will penetrate 92 percent of Best-in-Class within 24 months. Only 23 percent of all retailers surveyed stated that they did not have plans to implement faceted navigation on their e-commerce Web sites.
Faceted navigation begins with the way metadata is tagged and associated throughout the site. The goal is to produce search results that facilitate product discovery or additional drilling to reveal more choices for buyers.
Challenges include search tools that provide too many responses, which forces users to wade through lines of products and/or data to find relevant information or not enough responses — it leaves them wanting more.
To combat these challenges, half of Best-in-Class companies use a faceted search taxonomy that segregates query matches by attributes.
For example, a customer visited an online consumer electronics site and searched for a 6-megapixel digital camera. He checked the results, which were segregated into categories (i.e., cameras and camcorders, computers and office products), brands (Canon, Casio, Fuji, etc.) special offers (On Sale, Free Shipping, Package Deals) and actual products.
The site used faceted navigation to display navigational choices to narrow the search and focus on specific selection criteria. The customer clicked on the camera category and was presented with additional product choices with options to sort by price, brand, best sellers or new products.
Sites that are not built with a navigation structure designed to accommodate search taxonomy have significant challenges to implement these best practices.
Vendors Stake Out Facet Technologies
Companies that compete in the search and merchandising arena provide decision-making tools for customers to allow them to find products quickly and easily. Although the concept is called faceted search, vendors have different names for it and are busy registering and trademarking their segmented search descriptors, including the following:
- Endeca calls their faceted search Guided Navigation;
- Mercado goes by Product Data Optimizer;
- FAST provides faceted search but doesn’t apply a moniker;
- SLI Systems trademarked their faceted technology Learning Navigation; and
- DieselPoint calls theirs Search and Navigation.
Each of these solutions offers a slightly different approach to segmenting search results into a structured schema, with the end result of driving relevant, understandable results and adapting to user behavior.
The benefit to consumers is that they can refine their search requirements based on information specific to their needs without sifting through a multitude of results. Currently, 82 percent of laggard retailers do not use a faceted search structure, but this is likely to change as 44 percent of all respondents plan to implant this taxonomy within the next 24 months.
Faceted navigation is a searchandising mentality that plays on a shoppers’ inclination to start with a vague idea of what they’re looking for and to browse a site until they stumble upon relevant products. Yet, retailers serve up these products through a series of calculated rules-based procedures (used by 72 percent of Best-in-Class retailers), working behind the scenes.
In this way, sites can merchandise based on user analytics data and build upon the collective behavior of the best paths to conversions and to profitability.
Search analytics data is currently used by 65 percent of Best-in-Class retailers to build customer profiles, evaluate buying patterns and discern successful keywords and conversion paths.
This data can be modeled to anticipate customer behavior and is leveraged by 26 percent of Best-in-Class merchants to tune search results in order to merchandise to customers and customer segments on a predictive basis.
It should be noted that this process can be achieved in real-time — but it is extremely difficult to do. Sophisticated search technologies can deliver real-time merchandising results based on information gained during a consumer’s current online session, but most often this is not the case.
Predictive analysis and collective behavior are capabilities inherent to some search applications, but retailers must start with segmentation and faceted search basics prior to getting accurate predictions of what customers want and what they will purchase.
Additionally, 68 percent of leading sites use data collected from search to feed back into their merchandising tactics to influence results. What’s even more important is the ability to measure and manage the conversion process to key into what works and to modify tactics that fail.
According to 55 percent of leading retailers, they actively monitor conversion rates achieved from search optimization tactics and continually fine tune results as a corrective measure.
Customer conversions for online shoppers that use the search tool vs. those that do not show significant advantages to drawing customers into the search tool.
Twenty-two percent of retailers reported conversion rates 26 percent to 50 percent better than those who did not use search; 11 percent of Best-in-Class retailers reported improvements in conversion rates that were 51 percent to 75 percent better than non-search users.
To achieve these increases in conversion rates, companies first must align their navigation structure to accommodate search queries, as well as ensure that zero yield searches and failed search attempts are kept to a minimum by measuring and managing these metrics.
If these processes are put in place, sites can maximize the profits of searchandising to provide a more relevant shopping experience for customers — and higher profits.
John Lovett is an e-commerce research analyst atAberdeen Group. He focuses on e-commerce as it relates to the business environment, including the B2C (business to consumer) landscape. Areas of research include e-commerce platforms, search technologies, Web analytics, content and publishing management tools, and transaction engines necessary to conduct business online.
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