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Posts with learning search Tag

Site Search Isn’t Sexy, It Scores Sales

Posted by Tim CallanFebruary 25, 2015eCommerce, Site Search, User Experience

There’s no question. Site search isn’t sexy, but it doesn’t have to be, because the revenue it drives speaks for itself. Internet Retailer Senior Editor Thad Reuter said it best in his February article, Reading Shoppers’ Minds:

“Site search receives little in the way of celebrity-level attention in e-commerce… But with retailers typically reporting two or three times the amount of conversions for site search users, the stakes are obvious: Better site search can translate into more profits.” Period.

However, one question still remains: Which site search approach best connects shoppers with the products they’re most likely to buy, making shopping easier and retailers more profitable? Do online shoppers use natural language search, which interprets subjective terms to serve up search results? Or do the most relevant search results come from learning site search, which “learns” what specific search terms resonate most with consumers and – with SLI Learning SearchTM technology – reranks the order of search results based on the latest activity of users?

In e-commerce, there is some uncertainty around the demand for natural language search. North Face e-commerce manager, Charles Caison, told Internet Retailer, “At North Face, for instance, most shoppers search using terms that describe the product, not ambiguous phrases that require natural language processing to decode. It may be that we have been trained by Internet search engines for keyword searches rather than natural language searches.”

A new SLI study also supports Caison’s insight. To demonstrate site search user behavior today, SLI evaluated natural language terms, focusing on subjective search terms including “cheap,” “nice” and “cute” for a Fortune 100 retailer. As you can see in the chart below, out of 67,000 searches, the word “quality” was only used 3 times while “cheap” and “nice” had similar results. The findings reveal that subjective search terms are not yet commonly used among online shoppers.

Total searches performed ~67k
Searches containing “cheap” 11
Searches containing “quality” (high-quality) 3
Searches containing “nice” 0
Searches containing “cute” 42

 

Lakeshore Learning, an IR Top 500 company, also finds less use of natural language search from its shoppers. Lakeshore Vice President of E-commerce Sam Sarullo told Internet Retailer, “an analysis of the retailer’s top 1,000 searches revealed that consumers use an average of 1.8 words to search – a signal that consumers remain wedded to keyword search, and that natural language-type searches may not yet be intuitive. That said, I see return customers who are more familiar with our products using these natural language or long-tail searches.”

The beauty of Learning SearchTM is that if it detects shoppers’ use of longer search terms, it will “learn” and tweak its results to reflect that behavior. Learning Search continuously analyzes the terms and phrases that prove most popular and lead conversions.

Perhaps the best argument for the value of Learning Search is to let e-commerce companies’ results speak for themselves. Here are some of the results leading retailers have experienced using Learning Search:

  • Lakeshore Learning, an education supplies manufacturer: 30% increase in online sales
  • Boden, a British clothing retailer: 1.8x higher conversion rate using search
  • e.l.f. Cosmetics, an international cosmetics brand: 21% higher per-visit value using search
  • Marine Depot, world’s #1 supplier of aquarium supplies: 11% increase in revenue
  • SurfStitch, Australia’s #1 surf retailer: 30% improvement in page position for organic search

Some say “sex sells,” but in e-commerce, Learning Search sells more.

CSM of the Month: Mark Lawson on Analysys Mason

Posted by Mark LawsonJune 19, 2013Navigation, Newsletter, Site Search

This article is part of our monthly “CSM of the Month” feature, in which an SLI Systems Customer Success Manager discusses a current client example.

One of the more interesting projects I’ve been involved in recently is with Analysys Mason, a research and consulting firm who provide detailed articles to their global client base on all issues that relate to the telecoms, media and technology (TMT) sectors. While a large percentage of SLI’s customers are online retailers, we also work with publishing sites like Analysys Mason, the New England Journal of Medicine and Dilbert.com.

Analysys Mason is a great example of how SLI’s site search and navigation technology helps publishing sites improve the user experience and increase the number of page views per visitor. In fact, since implementing SLI they have seen a 21% increase in page views and a 24% increase in unique page views. The average time on site has also increased.

One of the reasons for these improvements is that SLI’s page load times are much faster than Analysys Mason’s previous search. This allows users to more quickly find the articles they’re looking for and leads to an overall better user experience.

Analysys Mason has a vast Knowledge Centre of research articles it has prepared. When I first started working with Analysys Mason, one of their unique needs was to show each user a different set of results based on their specific subscription IDs. This allowed them to have different tiers of subscribers – those with a free account who have more limited access to research, and those paid subscribers who have full access. Now that SLI brings back the correct results for each user based on their login credentials, Analysys Mason is able to make the tiered subscription model work for them.

In the below screen shot, you can see how the Knowledge Centre appears to those who are not logged in. In the left-hand column, the radio buttons under the Access section allow you to refine results based on free or paid content. In the results section, articles that are limited to logged in users display the note Subscription Required.

screenshot_knowledgecenter

Analysys Mason also uses SLI’s synonyms tool for search, as it has helped them to expand their vocabulary without having to edit the content database. As an example, a search for ‘MEA’ will pull up results for Middle East and Africa, even if the acronym MEA does not show up in the article title or summary.

By tracking the search terms used on its site through SLI, Analysys Mason is also able to pinpoint specific trends in searches. These analytics allow them to improve upon results for poor search phrases, as well as to know what research papers people are looking for.

Analysys Mason is also very pleased with the search suggestions that automatically appear under each product. This feature is powered by SLI’s Learning Search technology, which directs a user to a related set of results if they can’t find the article they are looking for straight away.

Anyone who has searched for articles on a publishing site knows the frustration of finding nonrelevant results, as well as the satisfaction of finding exactly what you were looking for. I’m happy to work with Analysys Mason to ensure that their customers have a great search experience and spend more and more time on their site.

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