Tag Archive for: Apple Siri

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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

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If Your Search Box Was a Personal Shopper, Would You Fire It?

 

In the world of online shopping, your site search box is like your personal shopper.  You know, like the ones who ask you, “How may I help you?” when you walk into a department store.

In the real world, if you’re asked that, you’re going to tell them how they can help you.  But in the eCommerce world, most of the sites you go to can’t help you the way a personal shopper can. Why?  Because of Keyword Search limitations, and the fact that most people don’t know what’s possible with their eCommerce Site Search.

In the early days of the Internet, way back in 1995, the Keyword attribute was popularized by search engines like AltaVista.  But even as early as 1997, which was 15 years ago, they discovered keyword search was unreliable.  But people still continue to use it!  Why?

Yahoo! and Google…

If you use a long-tailed search (i.e. “Women’s black long-sleeved dresses”), the chances of your search returning the right product, are very slim. And now you’re reduced to clicking through page after page to try and find what you want. Or, if you’re like me, you leave the site altogether.

Let’s flip it around and compare it to real life. What if you told a personal shopper that you wanted a “Women’s black long-sleeved dress,” and she returned with long-sleeve shirts, coats, jackets, short-sleeve dresses, strapless dresses, etc. You would look at her like she’s… how do I put this nicely?… AN IDIOT. Because you made it clear you what you wanted and she didn’t understand you.

You wouldn’t accept this in real life, so why are you accepting this with eCommerce websites? Because you’re used to it? That’s just ridiculous, especially when your eCommerce Site Search has the ability to understand the entire intent and context of your request.

If you’re using the right technology…

Natural Language/Semantic Search has been around for years, but has not gained steam until fairly recently with IBM Watson and Siri on the iPhone. It’s a SMARTER and FASTER search than Keyword, and can understand long-tail searches, price constraints, and synonyms.  Flip-flops, sandals, thongs, slippers are all the same thing, you know it, I know it, your search box should know it.

It’s time to stop accepting below-average as the norm. Upgrade your eCommerce Site Search to a Natural Language Engine. EasyAsk has done wonders with companies Large (Lands’ End) and small (Schuler Shoes).

Take a look for yourself and see what can be accomplished with the right Searchandising tool.

 

 

 

 

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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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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.

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EasyAsk Quiri – Interview Excerpt on Pulse Network Sync-Up">Voice Recognition & EasyAsk Quiri – Interview Excerpt on Pulse Network Sync-Up

EasyAsk CEO Craig Bassin talks about the differences between “voice-recognition” and “natural language search” – without understanding intent, you can’t accurately answer questions. Craig also notes that even Google is evolving from traditional keyword search.

 

 

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Siri-Cized Sites With Voice-Enabled Mobile Shopping? EasyAsk Customers Are Already There

The technological world seems to be making a shift. It began with those three days in February 2011, when IBM’s Watson computer competed on Jeopardy! (By the way, the natural language super-computer trounced the shows two biggest champions!) And culminated with Apple releasing Siri in their latest model of cell phone, the iPhone 4S on October 14th, 2011.

You can feel the buzz in the air, a change in the winds, that a paradigm-shift is coming. The ability to tell your electronics what to do.

So wouldn’t it make sense that this same technology could be used by everyday consumers to shop on their smart-phones? Isn’t it logical, that the next step will be the ability to use this natural language technology to search and purchase items on your favorite website? That this technology would improve user experience, retention and increase conversion rates? Wouldn’t you want your favorite sites to be Siri-cized?

Well, if you’re a client of EasyAsk, this power is already at your fingertips… err… voice-box.

EasyAsk-powered sites such as: Lands’ End, Harbor Freight Tools, J. Jill, True Value and Coldwater Creek, are already Siri-cized. Customers of these and other EasyAsk clients can use their iPhone 4S or Android to verbally search for their products on their mobile-sites. And thanks to the natural language engine that powers EasyAsk, they’ll find exactly what they are looking for.

Now, I hear the nay-sayers, griping about the times that Siri doesn’t work as well as they want. First of all, Siri is cutting-edge technology, so of course it’s still working out a few of the kinks. But here’s where EasyAsk differs. With Siri, the options are so varied, it’s difficult for the software to search through the entire Internet to find the right answer every time. With EasyAsk, the data needed is pulled from the company’s product catalogue. So, if you’re on Lands’ End, you’re going to be searching for items Lands’ End is known for having, like swimwear, shoes, luggage, etc. If you’re on Harbor Freight Tools, you’re going to search for items they’re known for having; air compressors, engines, toolboxes or various tools. EasyAsk understands the context of your request and retrieves the right product on the first page.

This isn’t the future; it’s the present. EasyAsk sites are and have been ahead of the game, because EasyAsk has been mastering Natural Language for over a decade. Feel free to find out more here.

So go ahead, grab your iPhone 4S or Android 2.1, jump on Lands’ End and get ready for summer by shopping for a new bathing suit or try True Value and order that new grill you’ve been waiting for. It’s as simple tapping the search box, tapping the microphone, and saying what you’re looking for.

Welcome to the future.

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