Tag Archive for: EasyAsk

by

You’re Betting Your eCommerce Business on . . . SOLR ??!!

What’s behind your eCommerce search box? You’re not going to like the answer

As an eRetailer, one of the most critical functions on your website is your search box.  This is where your shoppers go to find things they want to buy.  The truth is that, deep down; you know it just doesn’t work very well.  Most eRetailers think that “search” is just “search” and that all search tools are just about the same.  They expect that their search has some navigation, basic spell correction, and maybe type-ahead.  If that’s all search offers, then what’s the difference, really? Read More

by

Automatic Spell Correction in eCommerce Search Saves you Time and Money

The last thing any visitor wants to see when they perform a search on an eCommerce Site is a page that says “No Results”. As we indicated in our recent whitepaper, Increase Customer Conversion by Boosting Product Findability, misspellings and using different tenses is a very common occurrence by eCommerce shoppers.

To make your site tolerant of misspellings and the like, you have two options: Either manually enter all the various misspellings and whatnot into your search engine, which will take you God-knows-how-long… Or, the better approach, use an eCommerce search engine that offers Automatic Spell Correction and stemming against terms in your product catalog.

This gives you out-of-the-box tolerance of these visitor errors, enabling them to find the right products and keeping them on your site as opposed to going to your competitors.

Watch this one-minute video and see how Coldwater Creek uses EasyAsk’s automatic spell correction to convert more visitors into customers.

by

Intelligent Search: What Google’s New “Semantic Search” Means for Search on your e-Commerce Site

BY EasyAsk CEO Craig Bassin

Google has recently announced that it is adding more “semantic search” techniques into its otherwise largely keyword search. This means matching on the meaning of words, rather than just the occurrence of words. Since nearly all of your customers also use Google, their expectations for search are conditioned by Google. Over time, there is a trickle-down in the expectation that shoppers have of search, based largely on their experience on Google.

Therefore, it’s a reasonable question to ask: “What changes should I make in search at my commerce site to keep pace with customer expectations?” Beyond keeping pace with expectations, there is another even more important reason to invest in semantic search on your site — increased conversion rate. Analysis of Neilsen netRatings conversion rate studies across similar e-commerce sites has not only confirmed the impact of natural language semantic search, it has actually measured it!

What is Semantic Search?
The literal definition of semantic search is searching on meaning rather than searching on words. Google is now knocking at the door of semantic search by associating word groups as concepts. If some people search on “beach sandals” and other people search on “beach flip-flops”, while both groups click to show interest in the same item set, then the concept “sandal” and “flip-flop” may be related. The distillation of words into concepts is one part of the greater field of Natural Language Processing (NLP). Searching on concepts in their various forms delivers more complete results and is more tolerant of user search variations. As you have seen, semantic search is quite valuable – but there is more power available when you go deeper using more NLP techniques.

A semantic search with deeper NLP (let’s call this Natural Language Search, or NLS) support brings even more converting power to a commerce site. Lets look at these two commerce searches, “return policy” and “sweaters under $100”. Searching all your product descriptions for the words “return” and “policy” will clearly lead to ridiculous results. Clearly, the intent of this search is to display your policy on returns – treating this as a phrase and recognizing its special nature are important to the shopper, and easy with NLS.

Similarly, treating “under $100” as a keyword search will yield undesirable results. The intent of the user is to restrict the products based on price. Recognizing that “$100” is not a word, but rather a price requires something smarter than a keyword search. This occurs in other forms when the user wants to express a range restriction, not just on price, but any other numerical product attribute such as length, weight or wattage.

Units of measure commonly stump keyword search engines. For example, keyword searching for “12 volt 24 amp motor” will unfortunately return all motors with 12 or a 24 anywhere in the description. Thus, both 24 volt 12 amp motors as well as 24 watt .5 amp motors with a 12″ shaft will be shown! If your site gets lots of dimensional/size searches, the capabilities of NLS is absolutely critical. A semantic search with NLP is aware of units of measure, such as “volt”, “v” or “amp”, “A”. This unit of measure awareness automatically creates a phrase around “12 volt”, and to include searches on variations like “12V” or “12 V”. When a shopper searches for “Nike size 10”, NLS will recognize that “size” is an attribute with numeric values & therefore select the products with “size=10”. These capabilities impact countless unique searches that would otherwise stump almost all search engines.

These examples illustrate how easy it is for dumb keyword searches to yield embarrassing results. Have you ever searched a site only to see hundreds of irrelevant results? This not only reflects poorly on your brand, but can actually cause you to lose customers! Nearly all of us have had the experience of getting such poor results from a search on a commerce site. We get frustrated and leave the site altogether to buy from another site. This illustrates how improving search can improve conversion rate.

In order to measure the correlation between semantic search and conversion rate, we used Nielsen netRatings to compare the conversion rates of sites that were similar except for their use of semantic search. We compared sites for catalog companies and non-catalog companies separately. In both groups, the sites using semantic NLP search had about 20% higher conversion rate than the sites using keyword search. Of course, there are many other phenomena that impact conversion rate, but these would generally balance out across all the groups. Furthermore, the 20% improvement is consistent with the uplift we see when customers switch from keyword search to semantic search. Details of the Nielsen study are available on request.

Google is moving the world towards semantic search. Eventually user expectations will demand it from your commerce site as well. Switch sooner rather than later – you’re leaving money on the table every day until you make the switch!

by

EasyAsk Partners with Explore Consulting to Help Fusion Beads – a NetSuite E-Commerce Site – to Improve Search and Navigation

Partnership offers e-retailing customers, including those of Fusion Beads, improved shopping experience

EasyAsk, the leading provider of natural language solutions and technology, and Explore Consulting, a professional services company that provides innovative technology solutions for managing business data and a cost-effective approach to completely outsourced IT in the cloud, today announced a partnership to deliver natural language e-commerce solutions to retailers using the NetSuite e-commerce platform. Additionally, the companies announced a successful deployment at Fusion Beads (www.fusionbeads.com), an online store offering a wide selection of products and information to the beading community.

“The Fusion Bead deployment is a good example of what the Explore Consulting and EasyAsk partnership is aimed at providing,” says Steve Jones, CEO of Explore Consulting. “The partnership offers all types of e-commerce retailers the most advanced search and navigation and intuitive merchandising tools – cost-effectively and very quickly – especially on the NetSuite platform.”

EasyAsk’s NetSuite integration works from within the NetSuite pages, ensuring that page content is search engine friendly and utilizes the item records in NetSuite accounts to maintain centralization of data. Item attributes are configured in NetSuite and the EasyAsk Business Studio is used to configure search and navigation rules based on the attributes a merchandiser wants to use. EasyAsk is similarly tightly integrated with Magento, as well as other popular e-commerce platforms.

After selecting NetSuite as a new e-commerce platform, Fusion Beads turned to Explore Consulting and EasyAsk because they wanted to make it easier for their customers to navigate the wide range of products offered through their website – more than 50,000 items. Not only does Fusion Beads offer a lot of products, but they also catalog a tremendous amount of product and project data to ensure their customers are getting what they need. With the EasyAsk solution, Fusion Beads can now configure down to the item level the product attributes that should be used for search and navigation from over 600 custom item fields they currently use.

“We turned to NetSuite when the Fusion Beads Website became too large to maintain manually,” said Gunilla Eriksson, Director of Online Operations at Fusion Beads. “Additionally, we needed EasyAsk to help us manage search and navigation with our large product catalog and to display, in parallel, relevant projects ideas to our customers. Now shoppers can own their own search and view projects and products in one page. People love it and we love it. It works so much easier.”

“EasyAsk is very excited about the Explore Consulting partnership and the value we are adding at Fusion Beads,” said Marc Schnabolk, VP of Sales and Business Development at EasyAsk. “Explore will help us deliver the EasyAsk eCommerce search and merchandising solutions throughout the NetSuite user-base – both on-premise or as a service (SaaS). We are offering unique capabilities, including intuitive natural language search, relaxation, spell correction, integrated faceted navigation, easy to use merchandising tools and advanced analytics. EasyAsk and Explore Consulting are perfectly aligned in their vision to help Internet retailers achieve industry-leading conversion rates that dramatically increase e-commerce revenue.”

About Explore Consulting
Based in Bellevue, Wash., Explore Consulting was founded in 2001 and is a professional services company dedicated to providing innovative and cost-effective solutions for their customers’ database and IT systems needs. With a heavy focus on SaaS web-based business systems like NetSuite (NYSE: N) and Amazon Webstore, Explore has developed industry-leading PC and mobile platforms for seamless data integration in the Cloud. Additionally, Explore develops custom solutions ranging from eCommerce web stores that are fully integrated to back-office systems to highly specialized business applications written in Microsoft’s .Net and SQL platforms. Explore was recently ranked among Inc. Magazine’s fastest growing companies for four straight years as well as the Puget Sound Business Journal’s 100 Fastest Growing Private Companies three years running. Explore Consulting is the largest NetSuite Solution Provider and reseller in the Northwestern United States and was recently named as 2011 NetSuite Partner of the Year, Americas. For more information, visit www.exploreconsulting.com.

About EasyAsk
EasyAsk is radically changing the speed and ease of how people find information through the company’s ground-breaking natural language search software. EasyAsk software products go far beyond traditional search, allowing users to simply ask questions in plain English and receive highly tuned results on demand. The EasyAsk eCommerce Edition uses this unique technology to deliver industry-leading website search, navigation and merchandising solutions that boosts online revenue through increased conversion rates, better customer experience and agile merchandising. EasyAsk Quiri & Business Edition revolutionize enterprise decision-making, moving beyond traditional business intelligence solutions with easy, low-cost deployment and a unique natural language interface that extends access to information anywhere in the organization.

Based in Burlington, Massachusetts, EasyAsk has long been a leader in natural language information analysis and delivery software. Customers such as Coldwater Creek, Lands End, Lillian Vernon, Aramark, TruValue, Siemens, Hartford Hospital, Ceridian, JoAnn Fabrics and Harbor Freight Tools rely on the EasyAsk software products to run their business and e-commerce operations daily.

by

Benefits of Semantic Natural Language Search for E-Commerce

BY EasyAsk CEO Craig Bassin

How this paradigm shift will change Web and mobile e-commerce forever

Advancement in communication and technology over the last two decades has been dramatic, and the way people consume information has evolved in parallel. Not long ago, people turned to libraries, dictionaries, reference journals, books, phone books and printed newspapers for insight, but now they simply turn to “The Web.” Answering complex questions used to take hours or days – if we could figure out how to answer them at all. Now we are accustom to executing Internet searches in seconds.

ACCURACY, however, is the issue.

The next step is to provide the correct response on the very first page. To take this next step, we’ll consider some words and phrases that were once outside of mainstream vocabulary, more commonly used in academic and research circles at MIT and Stanford labs – things like Natural Language Processing (NLP) and Semantic Search (per Wikipedia: semantic search uses semantics, or the science of meaning in language, to produce highly relevant search results. In most cases, the goal is to deliver the information queried by a user rather than have a user sort through a list of loosely related keyword results.). Search will not evolve without these important concepts because even with all the great digital information available today, it still takes too long for people to find exactly what they’re searching for – whether on the Internet, on their phone, in an e-commerce store, or in a corporate applications like CRM and Business Intelligence.

It is interesting to think about where we started with search boxes – Yahoo, Excite, Netscape, to name but a few, and most recently Google, have all taught us to search using “keywords.” We know that search engines can’t understand the way we speak or think, so we had to adapt our behavior to make use of the services they provide. When we hit the search button, we hope that the algorithms, machines and logic in some distant server farm send us back a bunch of links that we can comb through to find what we are looking for. Search engines essentially provide us a starting point – lists of results – but we still have to manually navigate the final mile. We get streams of results in seconds, but it takes considerably longer to find the right thing, or often we get frustrated and stop looking. Google has learned from user interactions and are now developing semantic capabilities, and WolframAlpha takes it further by computing answers from a knowledge base of curated, structured data but still today ‘search results’ are simply a starting point to begin looking for answers.

Also, semantic search is a great step in the right direction, but it doesn’t have a full understanding of all possible responses. That’s where natural language processing completes the loop, understanding both the searcher’s intent and a deep understanding of the data to deliver the best possible response. Essentially, Semantic search provides understanding of the intent, or context, of the search. Natural Language provides knowledge both of intent AND content.

For the first time, you can have better technology than the search engine giants – who have certainly spotted this trend and are moving in the semantic direction. Recently Google shared its Knowledge Map plans. Jack Menzel, product management director at Google, in a very articulate video, questioned: “Wouldn’t it be amazing if Google could understand that the words that you use when you are doing a search, well they aren’t just words, they refer to real things in the world. That a building is a building, and an animal is an animal and that they are not just random strings of characters, and if we could understand that those words are talking about those real world things, than we could do a better job of getting you the content you want off the web…”

Google is obviously a large company and has the time and resources to integrate changes in stages, especially considering that their revenue model is still based on keyword advertising. You and the e-commerce industry do not have that luxury – we need to act now to improve the Web e-commerce search experience and to accommodate the growing number of mobile e-commerce shoppers.

Given where we are today, understanding the intent of what is being searched for has become a competitive advantage – especially when deployed in e-commerce environments. Understanding intent even helps when shoppers enter only a few keywords, because each single word carries so much value. Natural Language Processing (NLP) use techniques like relevancy, association, disambiguation and many more to understand what a shopper is actually looking for, and can deliver the most relevant options from your product catalog.

Again, semantic search can understand the searcher’s intent, but NLP understands their intent and all possible results, then processes requests and delivers the best possible results. This is an important distinction, especially for e-commerce sites, which need to present the most relevant items, even when search requests don’t match up nicely with what is in your product catalog.

Some general e-commerce industry statistics suggest that 20% of searches are now long-tail searches. A long-tail search is a more descriptive phrase that contains three or more words. It often contains a main concept, which are one or two words in length. For example, “London Olympic t-shirt under $20,” the main concept would be Olympic and the other terms can help us identify the most relevant item with the additional details. Now we can look at t-shirts from the 2012 Olympics in London and not t-shirts from 2008 in Beijing. Cost is yet another filter, but again intent is important. Keyword search will return items with ‘Olympic, t-shirt’, ‘under’ or ‘$20’ (potentially t-shirt underwear) while the searcher intent is to find any shirts under $20.

As an e-commerce retailer, you have to address long-tail searches, otherwise you will miss out on a key source of revenue and likely degrade existing traffic.

Hopefully you are beginning to see some of the benefits semantic natural language search can provide Web-based e-commerce, but more importantly you need to consider how this will support your growth into mobile e-commerce.

Since the iPhone was launched, that small screen has become an important window into the world for most users. Androids and others followed suit and smart phones have become a common entry point into e-commerce. Analysts from research firm Gartner Inc. say the shift from e-commerce to m-commerce will reach something of a tipping point by 2015. According to Gartner’s analysts, mobile applications and social media will account for 50 percent of Web sales by then. Additionally, Gartner said that e-commerce merchants will start offering “context-aware, mobile-based application capabilities that can be accessed via a browser or installed as an application on a phone” at that point. “E-commerce organizations will need to scale up their operations to handle the increased visitation loads resulting from customers not having to wait until they are in front of a PC to obtain answers to questions or place orders,” said Gene Alvarez, research vice president at Gartner, in a statement.
Additionally, because of Siri, Nuance Dragon, Google Voice Search and others, speech is now an integral way we interact with these little devices. As people become more conversational with these devices, the search terms will naturally become more descriptive. Again, with limited screen size and long-tail searches, natural language search functionality will not just be a nice feature; it will be mandatory if you want to provide the most relevant result quickly and efficiently on mobile devices. Imagine connecting to your favorite e-commerce site, hitting the microphone on your smartphone and SPEAKING, ‘ladies blue blouses under $35’ and immediately seeing your results. That’s taking e-commerce mobile.

Natural Language and Semantic Search are concepts you need to become familiar with in the next few months. If you learn how to integrate them properly, you’ll be able to provide your shoppers the right information at the right time to improve conversion rates and drive revenue. Regardless if you do or don’t, your competitors will. So… Where do YOU think your shoppers will turn the next time they pull out their iPhone?

by

CPC Strategy E-Commerce News – How Do You Increase On-Site Conversion Rates? Enter Site Search Experts EasyAsk

Posted by  on September 20, 2012 in Ecommerce

With online traffic increasing in cost each year, retailers need to work on optimizing the conversion rates of the visitors that reach their site. There’s many ways to do this, and one of the most effective is implementing new site search technology to help consumers find the right product faster.
EasyAsk is a company that does just that. Their CEO Craig Bassin was nice enough to answer a few questions about the product for our audience.

Define EasyAsk in 140 characters or less:

EasyAsk, a Gartner Cool Vendor for 2012, is the leading provider of natural language semantic technology and solutions.

EasyAsk eCommerce provides intelligent search, navigation and merchandising tools to all sizes of eRetailers. Our customers enjoy industry-leading conversion rates because EasyAsk’s Natural Language search helps their customers more easily find what they are looking for on your site and merchandisers are empowered to drive sales with the right changes and promotions.

What is your target market? Please be as specific as possible.

Over 350 e-commerce sites already rely on EasyAsk’s natural language solutions.  EasyAsk delivers its solutions as on-premise software and SaaS to all types and sizes of B2B and B2C e-commerce companies.

EasyAsk eCommerce manages sites with as few at 500 SKU’s to as many as 10 million+, so we can grow with our clients as their business grows.  Most merchants quickly realize that keyword search functionality embedded in e-commerce platforms provide less-than-stellar shopping experiences.

We get a large number of calls from small to mid-sized e-commerce companies looking to fix poor search box results due to limited platform search capabilities – like SOLR, or other keyword based technologies.

Merchandisers may often lead the selection process too, demanding intuitive tools to better control their business, aiming to rely less on technical teams to translate their merchandising and promotional strategies.

What’s your pricing structure look like? Do merchants have to make long-term commitments to use your products / services?

We find that in most cases, EasyAsk deployments pay for themselves in the first 6 to 12 months, so the pricing structure is always positive, and we created a very flexible pricing structure to support a wide rage of budgets. EasyAsk customers should expect revenues to increase, due to improved customer conversion. Many have seen revenues grow from 20% to, in once case, 100% in the first year.

EasyAsk eCommerce SaaS starts at $999 a month and on-premise deployments start at $35,000. Subscription licenses (SaaS) have commitments of as little as one year, and on-premise licenses are perpetual, requiring only industry-standard annual maintenance.

What differentiates you from other companies that provide similar products / services?

EasyAsk is the leading natural language search engine in the marketplace.

The evolution in search is to extend beyond the limitations of keyword search.  Keyword search only matches words – there is no understanding of the intent or context of the search.

The industry is acknowledging keyword search deficiencies, and in fact even Google is now implementing a new semantic model that provides some understanding of what the searcher is looking for.

EasyAsk leads the industry in providing an even stronger model that not only understands the intent of the search, but also the content of the site.  This provides a perfect combination resulting in the right products displayed on the first page every time and also eliminates the dreaded ‘no results’ page.

Traditionally we compete with keyword search providers, which don’t measure up when it comes to understanding shopper intent.  We also compete a bit with in-house development – some e-commerce sites are built with a patchwork of open source code.

It takes a lot of technical savvy to keep these sites together and functioning.  In all cases, once we plug in EasyAsk, we dramatically improve search, navigation and merchandising control, resulting in increased conversion and higher revenues.

For your shoppers who continue to search with keywords, EasyAsk’s natural language solution even improves keyword search.  For example, a search for “dresses” or a search for a “shirt” will be different than a search for a “dress shirt”.

EasyAsk’s advanced linguistics automatically recognizes that a dress shirt is a different product concept and not the intersection of “dress” and “shirt” as would happen with the keyword search technologies in the market today.

What’s next for EasyAsk?

Everyone’s talking about mobile.  But very few companies are really thinking about how the mobile shopping experience differs from one designed for the desktop, laptop and tablet.

The fact is that it needs to be VERY different, and designed for a 3”x2” screen.  The user interface needs to be optimized for the smartphone. If your shoppers could speak to their smartphone, as they would a sales person in a store, and get accurate results, then you’ll convert that shopper into a buyer.

We’ve developed some really cool, cutting-edge mobile solutions, both for e-commerce and inside the enterprise.  It’s similar to the Apple Siri model, blending voice recognition with natural language.

This gives you the ability to touch your microphone button and ask for exactly what you want.  EasyAsk takes it from there and delivers the right result to your smartphone.  Shoppers have little patience when it comes to navigating lists on a 3-inch screen.

Voice-enabled natural language search is an ideal way to get the right products in front of shoppers with minimal end-user effort. We already provide this capability to most of our e-commerce customers today.  Nearly all Androids and all iPhone 4s are voice-enabled, and our natural language engine on the backend understands shopper intent – providing the best shopping experience for mobile shoppers today, period.

We also just launched a Siri-like solution for the enterprise called Quiri.  It gives workers easy access to the information they need to perform their jobs.  You can watch a quick video demo here (http://www.youtube.com/watch?v=XLhQn-Zx7D8 ).

Research we commissioned suggests US organizations could save more than $800 million a day by deploying this type of voice-enabled natural language technology.  For more on the benefits and how people are accessing information today, take a look at some of our research highlights here (http://www.youtube.com/watch?v=4ZkS7JK-mtE )

Where can merchants learn more?

We provide a lot of product and topical information on our Website.  The best source is probably other merchants – we have a variety of case studies and articles on our Website and we host a series of Webinars where our customers tell their stories in their own words.  Readers can check on our Website for upcoming events and can also go directly to our e-commerce solutions center athttp://www.easyask.com/solutions/e-commerce/.

For those merchants that want a quick look at our e-commerce solutions, they can go tohttp://www.easyask.com/products/ or give us a call at 1-800-452-8200.

For the articel as it appears in CPC Strategy News Blog, go here.

by

SemanticWeb – EasyAsk Helps DollarDays Boost Sales and Web Presence

EasyAsk reports that their client DollarDays has marked several milestones this back-to-school season thanks in part to EasyAsk’s natural language semantic search. The article states, “In 11 short years, Dollar Days is celebrating several milestones, including doubling the number of SKUs it offers to more than 225,000 and the number of suppliers to more than 500. Traffic on the DollarDays.com site has increased significantly, as have the number of memberships. All of this translates into revenue growth for DollarDays, even in a business environment where competitors are shrinking or going out of business.”

The article continues, “DollarDays CEO Marc Joseph attributes DollarDays’ continued success to many key variables, including a growing number of price-sensitive shoppers, dominant marketing as seen in the company’s back-to-school programs and an overall exceptional customer experience, led by strong site search, merchandising and analytic capabilities. ‘As the volume of traffic and the total number of items increases, the more important it is to present the right items to the visitor as quickly as possible,’ says Joseph. DollarDays originally used the open source search product, Solr as part of its open source e-commerce software stack. Solr is an open source search platform from the Apache Lucene project.”

For the full article, click here.

by

DollarDays Delivers a Solid Back-to-School Season with EasyAsk Semantic Search

Move from Open Source Solr, to EasyAsk Improved Search, Navigation and Merchandising – Driving Business Forward

EasyAsk, the leading provider of natural language semantic technologies, and DollarDays International, the largest by-the-case online store for small businesses shared details of DollarDays recent Back-to-School season success.

In 11 short years, Dollar Days is celebrating several milestones, including doubling the number of SKUs it offers to more than 225,000 and the number of suppliers to more than 500. Traffic on the DollarDays.com site has increased significantly, as have the number of memberships. All of this translates into revenue growth for DollarDays, even in a business environment where competitors are shrinking or going out of business.

DollarDays CEO Marc Joseph attributes DollarDays’ continued success to many key variables, including a growing number of price-sensitive shoppers, dominant marketing as seen in the company’s back-to-school programs and an overall exceptional customer experience, led by strong site search, merchandising and analytic capabilities.

“As the volume of traffic and the total number of items increases, the more important it is to present the right items to the visitor as quickly as possible,” says Joseph.

DollarDays originally used the open source search product, Solr as part of its open source e-commerce software stack. Solr is an open source search platform from the Apache Lucene project.

Business Reasons DollarDays Upgraded to EasyAsk from Solr
• Highly descriptive search – Because of their explosive product catalogue growth, DollarDays needed to give shoppers more search functionality, and the ability to enter more detailed descriptions in the search box.
• Faceted navigation – most navigation systems define static categories. EasyAsk natural language automatically generates additional layers of product definitions that greatly improve faceted navigation.
• Agile merchandising – Merchandisers can leverage EasyAsk eCommerce to create banner ads, promotions and rapidly identify and adapt as shopper trends develop.
• Manageability – the scope of managing search terms over a product catalogue of 225,000 SKUs can be overwhelming. EasyAsk offers intuitive graphical tools and analytics to make the job easier.

“EasyAsk search dramatically reduced the time for customers to find products and get to that all important checkout stage,” said Joseph. “As our number of items and seasonal merchandising needs grew, EasyAsk’s superior faceted search enabled our shoppers to more explicitly explore items across multiple dimensions. We offer a number of niche products, and once the visitors get to our site, we need to make it easy to find the exact product they want. EasyAsk helps us do that.”

Kevin Ryan, VP of merchandising at DollarDays said, “wholesale sites are generally behind consumer sites when it comes to usability. Many sites only offer basic search and simple navigation by category. Imagine scrolling through 5000 different products in the same category, such as toys to find the one you’re looking for. People eventually get frustrated and leave. That is what sets us apart – we are way ahead of the competition.”

DollarDays recently redesigned its homepage (www.dollardays.com), leveraging EasyAsk’s analytics, natural language merchandising and faceted navigation to better guide visitors and present high priority items for the season in much less space. DollarDays also uses EasyAsk analytics to discover and actively promote the top items its customers are looking for at any given time. An example can be found in its “School Charity Drive” page (http://dollardays.com/easysearch.aspx?pg=1&q=bts2012) where EasyAsk Analytics identifies the 500 most popular items from last year, and promotes these in a blackboard-style category grid.

Joseph is an active contributor to the Huffington Post on economic and business issues. According to Joseph, “Despite the fact that many US consumers believe we are still in a recession, DollarDays is well into our best back-to-school season yet, which is the biggest season for our company. EasyAsk is a big part of our success.”

About EasyAsk
EasyAsk is radically changing the speed and ease of how people find information through the company’s ground-breaking natural language search software. EasyAsk has long been a leader in natural language information analysis and delivery software and its customers include Coldwater Creek, Lands End, Lillian Vernon, Aramark, TruValue, Siemens, Hartford Hospital, Ceridian, JoAnn Fabrics and Harbor Freight Tools. For more information, go to www.easyask.com.

by

Gartner E-Commerce Search Best Practices Part 2

In my last blog post, I discussed the recent Gartner report “Best Practices in Strategically Combining Search, Content Analytics and E-Commerce.” One of the most important e-commerce search best practices that analysts Whit Andrews and Gene Alvarez emphasize is the ability to “Offer effective definition-matching and handling of ambiguity in Query terms.” Let’s take a closer look at what this means, and how it applies to your search environment.

Effective Definition Matching

The Gartner reports talks about how a truly effective e-commerce search environment must understand the “language variations that are specific to what’s being sold and the audience to whom it’s being sold.” This really boils down to two items a search engine must be able to do:

  1. For each term in a search string, understand what that value represents – an attribute, product name, product category, etc. – and allow each column to have different relevancies.
  2. The ability to process search strings of different complexities as entire entities and understand how the individual terms relate in order to return the most accurate results.

This is the essence of natural language.  A natural language engine will process a complete search phrase, break it down linguistically and understand the full meaning of the request – NOT just what individual terms mean.  In this way, a natural language engine such as EasyAsk can fully support the specific “language of the site” and allow visitors to “speak” to the site in that language via the search engine.

With natural language processing, you can be assured that not only will simple searches – “blue shirts” – be processed effective, but so will complex ones – “women’s blue short sleeve shirts under $50.”  You can fulfill this e-commerce search best practice with the most effective definition matching possible.

Ambiguity

Ambiguity can come in many different forms.  It can come from mistakes or typos.  It can come from simple language variations such as different tenses.  Or it can come from a visitor’s lack of knowledge of the products – asking for “purple blouses” when none are available on the site.  To help you fulfill this aspect of the Gartner best practices, your search engine needs to give you the following:

  • Spell correction – your search engine needs to provide automatic spell correction.  Anticipating and pre-coding every potential misspelling of each term on your Website is a time consuming task. Who wants to do that?
  • Stemming – Your search engine needs to automatically support the different tenses, plurals and other variances of terms.  Once again, why should you need to have the time consuming task of entering every potential variance of each term?
  • Relaxation – this concept allows the search engine to drop part of a search term if no specific products exist in order to make sure some products are returned.  Seeing some products is always better than seeing NO products.  With relaxation, a search for “black levi jeans” will still return Levi jeans, even if there are none in black.  You search engine needs to have automatic support for this capability.

All of these characteristics will help you virtually eliminate the dreaded “no results” page and dramatically enhance the customer experience by always returning products to the visitor, even when there is some degree of ambiguity.

Further Flexibility

What if your “site language” is more complex than standard terms?  What if your site has a number of acronyms and industry terms?  What if you have cryptic model numbers that customers need to use to find parts or products?

To fulfill this last requirement, your search engine needs to make it easy to add synonyms, custom search terms and rules.  Once again this is where natural language engines help you implement best practices.

With natural language, you easily specify additional search terms and rules in – well, natural language.  You simply type in terms of any level of complexity and associate those with the existing terms or products in your catalog by simply pointing and clicking.

Learn More

To read more on these capabilities, please download our white paper, “The ABCs of E-Commerce Search: A Guide to Essential E-Commerce Search Features.”  In Part 3 of our blog post series, we’ll look at best practices in Search Analytics and Merchandising.

by

Gartner Best Practices in E-Commerce Search – Part 1

July is “Best Practices” month here at EasyAsk – where we describe good search, navigation and merchandising techniques that can help you convert more customers.  As you and your teams ramp up for busy back-to-school and holiday seasons, we want to help you convert more visitors into sales.  Over the course of this month, our team will show different best practices in search, navigation and merchandising and how they can impact customer experience.

While EasyAsk has many lessons to share, we always like to recognize best practices from independent firms, especially when they align with our vision. Gartner, a preeminent research firm, recently released a report called “Best Practices in Strategically Combining Search, Content Analytics and E-Commerce“, written by Whit Andrews and Gene Alvarez – two of the brightest minds in e-commerce and search.

Among the findings in this report, the Gartner analysts clearly stated the value of search, navigation and merchandising to an e-commerce environment:

  • Search is the means by which shoppers most nakedly reveal their needs and wants (as they themselves perceive them) to sellers.
  • Search is, therefore, a particularly powerful way to promote, relate and reveal products in a shopping experience.

The analysts went on from there to lay out two very important best practices in e-commerce search:

  1. Offer Effective Definition-Matching and Handling of Ambiguity in Query Terms
  2. Use Search and Content Analytics to Fulfill Shoppers’ Desires Through Merchandise, Related and Suggested Offers, and Advertising

These two best practices highlight the unique advantages natural language technology delivers in an e-commerce search environment.  Since natural language understands both the intent of the search and the content being searched, visitor searches are more accurately matched and the search engine seamlessly deals with ambiguity – misspellings, tenses, stemming and when to relax terms.  Natural language also understands the relationship between terms in a search to derive contextual meaning and further eliminates ambiguity.

In addition, the actionable analytics and natural language business rules in EasyAsk make it easy for your business people to better merchandise your site with context-driven offers, promotions and ads.

In the next two blog posts of this series, I will drill down into each of the two Gartner best practices we discussed above.  I will examine the best practices, detail how natural language fulfills the promise of these best practices and show customer sites where these practices are applied.

The most valuable best practices typically come from experts that have visibility into the widest spectrum of implementations – learning how smart people across the industry approach problems differently.  We’re always happy to confirm when EasyAsk best practices match those of top-tier research firms, such as Gartner.

Ready to see how EasyAsk's eCommerce solution can help you? Request a demo!