Tag Archive for: Google

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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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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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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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Google joining IBM, Apple and EasyAsk? Pigs fly! News at 11…

 

(Message from the CEO of EasyAsk, Craig Bassin)

Looks like this is the beginning of the end for keyword search.  You’ve probably seen a number of articles discussing Google’s shift to ‘semantic search’.  Anyone understand what that REALLY means?  First, the definition of ‘semantic search’ is an understanding of the ‘intent’, or meaning, of the search, rather than just matching the keywords.

Now why would the undisputed 800-pound gorilla of keyword search, change course at this late date?  Conventional wisdom says they were forced to take a hard look after Apple launched Siri.  The timing sure seems to reinforce the fact that they’ve been playing with semantic search for some time, but needed to make a marketing splash now.

So, why change?  Well, obviously it’s a BETTER way to search and they had to, or they wouldn’t have!  I mean, really, Google acknowledging the limitations of keyword search?

Quoting from Paul Demery’s recent article (to read it, click here) about Google’s adoption of semantic search in Internet Retailer, ‘“Semantic search should allow Google as well as other search engines to better understand the true user intent of a search query,” says Kevin Lee, CEO of search marketing firm Didit.

Also, quoting from the same article: “Every day, we’re improving our ability to give you the best answers to your questions as quickly as possible,” Amit Singhal, Google’s head of search technology, said in a blog post. “In doing so, we convert raw data into knowledge for millions of users around the world. But our ability to deliver this experience is a function of our understanding your question and also truly understanding all the data that’s out there. And right now, our understanding is pretty darn limited. Ask us for ‘the 10 deepest lakes in the U.S,’ and we’ll give you decent results based on those keywords, but not necessarily because we understand what depth is or what a lake is.”

Now, understanding ‘intent’ AND ‘content’ is something that is at the very core of who EasyAsk is and how EasyAsk searches.  It’s the idea that, in an e-commerce setting, you can search for ‘men’s dress shirts under $30’ or ‘ladies red pumps size 6’ and get EXACTLY what you’re looking for.  Natural language understands the semantics involved in the search.  We understand the ‘intent’ of the question, we understand the ‘content’ of the data.  In adopting a new ‘semantic’ architecture Google will start to understand the ‘intent’ piece as well.

Now, who else searches this way?  How about Microsoft’s Bing, IBM’s Watson, obviously Apple’s Siri.

Now which of these companies can help you improve your e-commerce site?

None of them.

OK, but what about the other e-commerce search providers.  You probably know a few of them.  Endeca, SLI, Adobe, SOLR.

No, no, no and no.  Strictly keyword search.  Old news. Yesterday’s tech.

So we want to be the first to welcome Google.  We like them, use them all the time for internet search, along with Bing.  But when it comes to e-commerce search, folks, EasyAsk is leading the way.  Let us show you how.

It’s what we do.

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