Tag Archive for: mobile

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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!

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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?

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Internet Retailer: Tool retailer lets mobile shoppers speak their searches

Travers Tools Company implements a voice search feature into its mobile site.

Consumers visiting the mobile site for Travers Tools Company Inc. searching for a specific drill bit now need only ask for it.

The retailer recently launched an updated m-commerce site that enables consumers to speak their site searches. The service, from site search provider EasyAsk, lets shoppers touch a microphone icon then say what they want into their smartphone to see a list of results.

“The industrial supply business is very competitive and what sets us apart is our industry knowledge and our ability to provide the right tools and parts for our customers,” says Bruce Zolot, president, Travers Tools. “EasyAsk search helps us ensure that our customers find what they are looking for quickly on our site and now just as easily on our mobile site. Shoppers can speak what they want into the search box and see what they want immediately.”

Shoppers can use their Apple Inc. iPhone 4S or a smartphone using Google Inc.’s Android operating system to speak their search queries. Consumers see a microphone icon next to the search box that prompts them to speak into their device.

“A consumer might be in a hardware store and see a tool they want,” an EasyAsk spokesman says. “Maybe they think it costs too much, or they want to see if they can get a better deal online. They pull out their Android or iPhone and go to Travers Tools and touch the search box microphone icon. They say ’Jet bandsaw‘ or ’Jet bandsaw over $1500.’ They can speak their search as they would describe it to a salesperson– the more info, the tighter the search results. The list is short and accurate, which is critical on smartphones with little screen space.”

EasyAsk uses what it calls natural language search—software and algorithms provided by EasyAsk that seek to understand what the consumer wants to buy and returns appropriate search results, the company says.

This natural language search engine can better understand the intent behind shopper requests than other search engines, EasyAsk says. “Try ’not stripe dress shirts under $80‘ for example,” the spokesman says. “Keyword-based search engines would return stripe shirts for $80 and possibly underwear and dresses. People can get around poor search on a desktop, but won’t on a mobile device.”

Travers Tool, No. 826 in Internet Retailer’s Second 500 Guide, already uses EasyAsk for its e-commerce site. The site search tool on the retailer’s desktop e-commerce site supports multiple search methods, such as the ability to view results within a category and narrow the results to specific items using a single results page, and also recognizes synonyms for search terms common to the metalworking industry. The results also reflect the current pricing and inventory amounts.

Travers began using the EasyAsk site search technology after consumers began telling the retailer they couldn’t find items on its e-commerce site as easily as they could in its print catalog. Given that the site offered a search box, those complaints represented a clear sign that that the search tool, which was supplied with its information management software, wasn’t working.

The EasyAsk system connects to Travers Tool’s back-office system that manages the flow of inventory and tracks product costs for the retailer’s more than 100,000 SKUs. This ensures that shoppers get up-to-date inventory and pricing information.

“Keyword-search back-ends won’t cut it,” says Craig Bassin, CEO of EasyAsk. “Even Google understands this. They’re in the process of evolving closer to natural language with semantic search. If your search box can’t understand the intent behind shoppers’ requests now, you’ll be irrelevant when that request comes from a mobile device. Mobile users can’t navigate as easily and will quickly abandon the site if it requires multiple searches. They either see it and get it, or move on.”

This article originally appeared in Internet Retailer: https://www.internetretailer.com/2012/06/14/tool-retailer-lets-mobile-shoppers-speak-their-searches

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EasyAsk Products – Excerpt from Sync-Up Interview on the Pulse Network

Sync-Up host Tyler Pyburn asks CEO Craig Bassin about EasyAsk’s products – EasyAsk eCommerce, Business Edition and Quiri.

 

 

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Travers Tool Mobile Site

EasyAsk customer, Travers Tool Company, has launched a new mobile commerce site. The mobile optimized site presents the search engine, category structure and products in a more friendly way for the smaller screen real estate of mobile devices.

The new mobile platform will be especially convenient for finding product attributes and specifications when a PC is not close by. Also, crews on construction sites, repair teams on the road, and others should find this new format especially convenient.

EasyAsk powers the search, navigation and merchandising for the new mobile site and has been used for years on the main Travers Tool Company e-commerce site, Travers.com. And best of all, the Travers.com mobile site is automatically “Siri-enabled” due to EasyAsk.

Go to the Travers site on your mobile phone (www.travers.com will recognize you are using a mobile browser and re-direct you to the mobile site).  On the home page, touch the search box, press the microphone button on your keypad and speak your request. Say, “solid carbide jobbers drill”, hit Go, and you will find the exact drill bits for that search. It works like a charm.

 

 

Also note how effectively Travers uses the screen real estate on the mobile site. It is very different from their main site and is optimized for FINDING PRODUCTS. The search box is prominent. Why? Because while search is important on an e-commerce site, search is CRITICAL on a mobile commerce site, as I spoke of in this blog post a few months back.

 

 

Travers Tool is an amazing organization. They continue to grow and take market share due to a strong focus on serving their customers, and the delivery of e-commerce services that outclass their competitors, including their new mobile commerce site.

The Travers mobile site it another indication on how simple it is for small and medium businesses to deliver competitive advantages using EasyAsk natural language search, navigation and merchandising.

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EasyAsk Named Cool Vendor

It is always great to be considered Cool.  But that is usually a personal distinction.  Now Cool is an attribute given to software vendors such as EasyAsk.

EasyAsk is proud to announce that we have been included in the list of “Cool Vendors” in the ‘Cool Vendors in Analytics and Business Intelligence, 2012’* report by Gartner, Inc.  We feel this is an accomplishment due to our products, our team, and most of all our customers.

As we look at our market position today, EasyAsk has dramatically expanded its solution footprint and customer reach in the past 12 months.  Direct sales to customers have grown.  We’ve forged new solution partnerships with IBM Big Insights and SugarCRM while expanding our partnerships with Infor and NetSuite.  We have also more than doubled the number of channel partners we work with, including our distribution partnership with BrainSell in the SugarCRM market.

Our eCommerce edition product continues to be the clear solution leader in e-commerce search, navigation and merchandising.  No other vendor can come close to performing the long-tail natural language searches that EasyAsk does, nor can any vendor make merchandising as easy to use as EasyAsk.

And our new Quiri product is revolutionizing the way people use mobile devices and mobile corporate applications.  Quiri is the only solution on the market that provides Siri-like voice-enabled natural language tools that work with your corporate data and applications.

Thank you, Gartner.  And a special thank you to our customers and partners.

 

*  Gartner “Cool Vendors in Analytics and Business Intelligence, 2012” by Bill Gassman, Douglas Laney, Andreas Bitterer, David Newman, Rita L. Sallam, James Richardson, 27 April 2012

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

 

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