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Site search may be an integral part of the online shopping experience, but even more than a dozen years into the online retailing revolution, most e-retailers are still content to return results that are not necessarily ranked in a meaningful manner to the shopper, such as alphabetically or highest to lowest price. Consequently, the search process becomes more cumbersome as shoppers scroll through results to find the item for which they were searching.
With online shoppers accustomed to more sophisticated web technology, such as video, consumer reviews, and blogs-all of which expand the content around items in a retailer’s catalog and can be used to guide shoppers to products and related merchandise-retailers can no longer afford to take such an unsophisticated approach to site search.
“There is a lot of data on retailer sites outside of the product page that can be used to create more meaningful search results that direct shoppers to the item or information they were looking for, and that can improve the overall shopping experience and conversions,” says Shaun Ryan, CEO of site search provider SLI Systems. “Ensuring your site visitors can find what they are looking for quickly and easily can be a big point of differentiation for retailers, and a profitable one, especially in this economy.”
The first step to achieving that goal is to examine the metrics used to rank site search results. It is not uncommon for shoppers to enter a phrase such as “digital camera” and be overwhelmed by the results since most site search engines are programmed to show items that include the keyword regardless of relevance.
By programming the search engine to rank results based on specific criteria, such as best sellers or highest rated by customers, or even a combination of those factors, retailers can deliver results that are not only more relevant, but which convert much higher than a site with poor search technology or a site whose product pages and navigation aren’t metrics based.
“Retailers should put a lot more intelligence behind how and what metrics are used to rank their site search results,” says Sanjay Arora, CEO and founder of Nextopia Software Corp., provider of site search and navigation technology. “Employing the right combination of metrics to rank search results will result in increased conversion rates.”
Formulating the best metrics includes tracking shoppers’ search strings, what results they clicked on, and what they purchased. If enough shoppers searching for an iPod purchase the model with the highest rating in customer reviews and also purchase a docking station, the retailer would want to rank that iPod model high in the results and show the docking station in an area marked “People who searched for iPod ultimately bought…”
“The aim is to develop metrics that calculate what people search for and what they buy to deliver granular results that get the highest rate of conversion,” Arora says. “Retailers want to put the highest converting products in front of shoppers, not at the bottom of the results page.”
More than just product info
Further relevance can be added to search results by including results for product information videos, customer reviews or blogs about the product. These types of results are relevant since many consumers want as much information as possible about a product before they make the decision to purchase.
Videos and product reviews that turn up in search results can be marked with specific icons, such as a television, to denote the result will direct them to something other than a product page. Links to videos and customer reviews can also be broken out separately at the bottom of the page to make them easier to spot.
“Retailers are looking to do more with video, customer reviews and blogs on their site and incorporating them into site search results is a way to further leverage this information,” Ryan says. “Search results need to show more information than what is found on the product page.”
Personalization is another way to enrich search results. One technique that retailers often overlook is the use of geolocating the shopper through the shopper’s IP address, which can tell retailers where the shopper’s computer is. This information can be used to personalize search results, such as displaying a graphic with a coupon code for “all shirts on sale for Texans.” “It’s a way to give the search results a more personalized feel,” Arora says.
Another form of personalization is to program the search engine to automatically complete a suggested search string after the shopper has entered a few letters of a keyword. For example, a shopper searching for Fischer Worldcup skis at an online ski store and who has entered “fis” could be presented with a drop down list of the most popular search strings for those keywords, such as Fischer Worldcup RC4 skis or Fischer Worldcup SC skis with Flow Flex binding.
If the keywords shoppers enter are related to popular products, odds are highly favorable that the desired search string will appear in the list. An added benefit of this feature is that suggested search strings can link shoppers to specific product pages, as opposed to then having to scroll through results.
“About 20% of shoppers that are presented with a drop down list of site search terms will select an item from that list,” Ryan says. “Automatically fleshing out the search string not only helps shoppers complete what they are typing faster but also ensures they use the most appropriate language to find the products they are searching for.”
Search with merchandising can also be leveraged as a replacement for site navigation. Retailers can actually use site search results to display products from a certain category
For example, Nextopia, which has more than 600 clients, has worked with a retailer of golf equipment to allow shoppers that use site navigation to locate drivers through the equipment category to see the same type of results as a shopper that enters the term “driver” in the site search box. In both cases, the highest converting items will rank in descending order and shoppers can narrow the search by clicking on more refined attributes in the left margin. Search refinement can include descriptive tags such as price, brand, model and condition.