When eCommerce site search is working well, it is a dream for your customers; they can find what they’re looking for on the first try.  No need to endlessly click through your site’s categories and attributes.  Unfortunately, eCommerce search is too often scaring customers away.  At a time when years of eCommerce progress has been made in a matter of months, it’s even more important than ever that your site search is up to scratch.  We’ll look at six scary statistics and the ways that you can ensure your site search is not one of the frightening ones…

Scary Statistic #1

70% of eCommerce search implementations are unable to return relevant results,

requiring users to search using the exact same jargon as the site[1]

Yes, that’s right, nearly three-quarters of eCommerce site searches will only return the right products if the customers happen to use the right language.  That’s a lot of lost revenue when those customers become frustrated and abandon the site.

To ensure that your customers can find what they’re looking for, you need a Natural Language search solution.  Natural Language search solutions find different versions of the same terms so that pluralities and tenses can be managed.  For example, it wouldn’t make any difference if a customer used the term “mens”, “man”, “men” or “womens”, “women”, “ladies”.  An intelligent Natural Language search system will understand this automatically, without any input.

Scary Statistic #2

34% of eCommerce site searches don’t return useful results when users search for a model number or misspell just a single character in the product title[2]

This scary statistic raises 2 important issues:

1. Misspelling

A good spell correction system is not just about correcting, but about finding words that occur in the product data which most closely match what the user described.

With EasyAsk’s intuitive search system, your product data becomes the look-up dictionary, meaning that your customers don’t have to match the spelling of your products exactly.

2. Complex Product Numbers

Whilst most good search systems will find common misspellings, they lack the ability to deal effectively with part or model numbers.  Consumers who are taking the time to type in a part number are undoubtedly more ready to buy, so it is even more important that they are able to find what they are looking for.  This is a particular issue for B2B companies.

EasyAsk has the ability to index part and model numbers comprehensively, indexing all variations to ensure that users can find the product, even if they forget or mistype part of the number.

EasyAsk’s ‘Part Number Expander’

A ‘Part Number Expander’ is especially useful for complex part numbers that include a combination of letters, numbers, and other characters.  A user might forget whether characters were separated by a hyphen or a slash, or might omit letters from the end.

The Part Number Expander takes each part number and creates all the different versions of terms, inserting them into the searchable index so that if any of them are searched for, they will match to the product.  The code is broken up into parts and the separators are substituted in all combinations.

For example, if the part number is

123-HC/1345AB

the Part Number Expander would index:

123-HC-1345AB                                     123

123/HC/1345AB                                    123-HC

123/HC-1345AB                                    HC

123 HC 1345AB                         1345

…amongst many other combinations.

If a customer types a part/model number that is slightly different (for example, using spaces instead of hyphens) the correct product will still be found.

JLMWholesale.com demonstrates how Part Number Expander can avoid no results for customers:

The part number for this door handle is 1191-E-3 US32D.  If a customer replaces the hyphens with spaces and omits the last section of the part number, the exact product is still returned.

Scary Statistic #3

If people have a negative experience on mobile, they’re 62% less likely to purchase from you in the future[3]

A negative experience will stay with prospects longer than a positive one, so if you want your mobile customers to become regular, you’ll need to make sure you’re not putting them off with a poor user experience compared to your desktop site.

Does your site have a mobile responsive design, so that the text, images, and menus change according to the screen size?  Furthermore, as your site adapts to a mobile size, do you show relevant categories and attributes, as opposed to just the first ones from the desktop site.

Customers using a mobile eCommerce site are more likely to use voice input, and therefore different word choices and sentence structures when speaking.  Your search system needs to be able to cope with voice input and the long-tail queries that are more likely on mobile.

Scary Statistic #4

46% of e-commerce sites have a “No Results Page” implementation that is essentially a dead-end for users, offering no more than a generic set of search tips[4]

Generating a generic ‘Sorry, no results matched your search’ message could be disastrous.  How many shoppers would stay on your site and how many would go straight to your competitor?

There are better ways to use a ‘No Results’ page, but what if it was possible to avoid searches returning no results in the first place?

It may be that a simple spell correction rectifies a ‘No Results’ search, but it is also important to monitor what EasyAsk calls ‘relaxed’ searches.  A relaxed search is one where the search system has modified the search by intelligently dropping (or ‘relaxing’) a term or terms.

For example, if a customer searched for a ‘Men’s black lace jacket’ and there are no products that match this description, we would want the results to show ‘Men’s black jackets’, rather than ‘Men’s lace jackets’ or ‘black lace jackets’, having relaxed the term ‘lace’.  Some searches will inevitably need to be modified and in this example, we want our search system to recognize that the gender stated in the search query is more important than the fabric.

If a user’s search has been modified (such as by spell correcting or relaxation) it is important to display a message explaining the changes to the original search.  For example, a user may search for “purple leather couches” and see the following message:

This user could have searched for leather couches in the first instance and spent a long time scrolling through the pages of results looking for any in purple.  But by using messaging in this way, the user is informed immediately and is more likely to use the search system again.

So-called intelligent ‘No Results’ pages will suggest searches based on what a user asked for, but truly intelligent search systems will change the search to find relevant products based on what the user asked for, even though there may not be an exact match.

Scary Statistic #5

It’s 5 to 25 times more expensive to acquire a new customer than it is to retain an existing one[5]

A worrying number of businesses still don’t use merchandising tools such as cross-sells and up-sells effectively on their eCommerce sites.  These businesses are leaving money on the table.

EasyAsk’s search solution includes a comprehensive set of merchandising controls.  With 9 predefined promotion types, banners, and business rules, amongst other functions, the business user is in control of the products that are presented to the customer.

Scary Statistic #6

36% of autocomplete implementations on eCommerce websites do more harm than good[6]

Although basic autocomplete suggestions can be found on 82% of eCommerce sites, most sites do not take the opportunity to capitalize on merchandising while users are searching.

As a user types into a search box supported by EasyAsk, however, search suggestions and category suggestions will be displayed as well as the products themselves.

EasyAsk offers ‘Search as you Type’, or SAYT, because it means a whole lot more than just a list of suggested searches.  It means many possibilities for getting the right products in front of your customers.

SAYT progressively searches for and filters through text.  As a user types a query, suggestions, products, categories, and attributes are found and presented with each keystroke.  This allows a user to stop short of typing the entire word or phrase and find what they were looking for quicker.

Search suggestions as well as relevant and popular products, attributes, and categories can all be displayed in an easy to use interface.

Here is an example from EasyAsk customer personalizationmall.com:

The user is looking for a wedding gift and the letters ‘wedd’ have been typed into the search box on the desktop site so far.  The above drop-down panel is displayed without needing to execute the search.  Alongside the search suggestions in the right-hand column, a popular category to browse and 7 products are displayed, based on the first search prediction, ‘wedding’.  Scrolling through the search suggestions using the down and up arrows updates the real-time search and therefore the categories and products displayed.  Personalization Mall could have also configured their search so that it updates just by a mouse hover for a certain amount of time.

Typed characters are shown in bold in the list of suggestions, with the rest of the suggestion in normal type.  Often, autocomplete systems only show suggestions that begin with the typed characters, but we can see here that the suggestions can contain ‘wedd’ anywhere.

Presenting customers with the most relevant search, product, and category suggestions is essential.

Conclusion

When your site search is performing well, customers won’t be scared off, and your business won’t become one of the statistics above.

Getting the right products in front of the customer as quickly as possible shortens the path to conversion, keeping your customers and your bank balance happy.

Follow the tips and best practices in EasyAsk’s upcoming eGuide: “Preparing for the Holiday Season: A Guide for your Ecommerce Site” to ensure your customers find the right products the first time.

[1] https://baymard.com/blog/ecommerce-search-report-and-benchmark

[2] https://baymard.com/blog/ecommerce-search-report-and-benchmark

[3] https://www.thinkwithgoogle.com/intl/en-gb/advertising-channels/mobile/few-tips-speed-your-mobile-site-and-tools-test-it/

[4] https://baymard.com/ecommerce-search/benchmark/page-types/no-search-results-page

[5] https://hbr.org/2014/10/the-value-of-keeping-the-right-customers

[6] https://www.smashingmagazine.com/2014/08/the-current-state-of-e-commerce-search/

The post Six Scary Site Search Statistics appeared first on EasyAsk.

1.  AI-Instant Search

It’s a rapidly changing situation, but it’s safe to say that the global Coronavirus Pandemic has defined 2020.  Nobody could have foreseen the dramatic changes to their way of life people have experienced across the world.  Every non-essential merchant has been directly impacted by the pandemic and brick and mortar stores are only now gradually reopening.  These events have resulted in unprecedented changes to consumer behavior and most transactions now moving online.

The Search Box on eCommerce sites has always been important.  After all, searching is shopping in an eCommerce context.  With so many more people currently buying online, it is even more important than usual that if your business can provide what a shopper is looking for, you get it in front of them as soon as possible.

Presenting customers with the most relevant search, product, as well as category suggestions is essential.  But it is easy to get AI-Instant Search, or Autocomplete, so wrong that it actually has a negative impact on your shoppers.

36% of autocomplete implementations on eCommerce websites do more harm than good*

Although basic autocomplete suggestions can be found on 82% of eCommerce sites, most sites do not take the opportunity to capitalize on merchandising while users are searching.

Advanced AI-Instant Search returns correct results as a user types in the search box, refining with each keystroke, à la Google.  This allows a user to stop short of typing the entire word or phrase and find what they were looking for quicker.

With Instant Search saving users 2-5 seconds for every search, do they really expect to finish typing their search?  If this is the case, it’s essential that Instant Search works well.

Here’s how to make sure your Instant Search is effective:

1. Character Matching

Often, autocomplete systems only show suggestions that begin with the typed characters, but an effective AI-Instant Search will match on characters anywhere in the search query.

Here is an example from EasyAsk customer personalizationmall.com:

The user is looking for a wedding gift and the letters ‘wedd’ have been typed into the search box on the desktop site so far.  The above drop-down panel is displayed without needing to execute the search.  We can see here that the suggestions can contain ‘wedd’ anywhere.  Typed characters are shown in bold in the list of suggestions, with the rest of the suggestion in normal type.

2. Configure which searches are shown first

The most effective AI-Instant Search systems will show trending search suggestions as the user types.  But these suggestions can be supplemented with any other suggestions, as defined by the business user.  The data seeding the search can be configured to include anything.

It’s also a good idea to display the last searches that the user made, even before Instant Search kicks in.

3. Show top products and categories as well as search suggestions

Presenting customers with the most relevant search, product, and category suggestions is essential.

As a user types, not only can you show top search suggestions, but also the top products for that search.  The search is actually happening in the background and displayed in the pop-up box.  You could even show top brands or categories associated with that top search.

In the example above, the first three characters of the search for a sofa have been typed.  The top products related to ‘sofa’ are displayed, alongside the top searches and 2 possible categories.  The order that these suggestions are displayed is based on the frequency that they’ve been searched in the last period.

When customers are searching for products that don’t belong in an obvious category, displaying the categories in Instant Search is an effective way of getting the customer to the product quickly.

For certain businesses, the addition of suggested part numbers is also very useful.

4. Option for customers to add directly to cart

If a customer has a list and knows what they want to buy, it’s really important that the journey from search to purchase is as rapid as possible for them.  These customers should be able to type in a part number, see the product appear in the Instant Search pop-up, and add it straight to their cart.  They shouldn’t have to go through numerous search pages.

5. Code-free Layout

The most sophisticated AI-Instant Search systems use templates, making it very easy for the business user to change. EasyAsk provides multiple templates to choose from, or businesses can define their own.

Having a template-driven layout means that it’s easy for business users to decide how they want to lay out their Instant Search pop-up without the need for code.  The EasyAsk system is also optimized for mobile, making it responsive to all screen sizes.

Finding the right products, first time, every time.

EasyAsk’s AI-Instant Search is a very advanced system that is designed to put the right products in front of the user at the earliest opportunity.  Displaying product, search, and category suggestions to a user as soon as they start typing makes the most of a merchandising opportunity that is often missed.

Using AI-Instant Search to improve your eCommerce search is just one of the many features of EasyAsk’s intuitive search and merchandising solution.

Find out more here

[1] https://www.smashingmagazine.com/2014/08/the-current-state-of-e-commerce-search/

The post Covid-19 eCom Blog Series: The Importance of Search for eCommerce appeared first on EasyAsk.

When eCommerce site search is working well, it is a dream for your customers:  they can find what they’re looking for, the first time.  No need to endlessly click through your site’s categories and attributes.  Unfortunately, eCommerce search is too often scaring customers away.  We’ll look at six scary statistics and the ways that you can ensure your site search is not one of the frightening ones…

Scary Statistic #1

70% of eCommerce search implementations are unable to return relevant results,

requiring users to search using the exact same jargon as the site[1]

Yes, that’s right, nearly three-quarters of eCommerce site searches will only return the right products if the customers happen to use the right language.  That’s a lot of lost revenue when those customers become frustrated and abandon the site.

To ensure that your customers can find what they’re looking for, you need a Natural Language search solution.  Natural Language search solutions find different versions of the same terms, so that pluralities and tenses can be managed.  For example, it wouldn’t make any difference if a customer used the term “mens”, “man”, “men” or “womens”, “women”, “ladies”.  An intelligent Natural Language search system will understand this automatically, without any input.

Scary Statistic #2

34% of eCommerce site searches don’t return useful results when users search for

a model number or misspell just a single character in the product title[2]

This scary statistic raises 2 important issues:

1. Misspelling

A good spell correction system is not just about correcting, but about finding words that occur in the product data which most closely match what the user described.

With EasyAsk’s intuitive search system, your product data becomes the look-up dictionary, meaning that your customers don’t have to match the spelling of your products exactly.

2. Complex Product Numbers

While most good search systems will find common misspellings, they lack the ability to deal effectively with part or model numbers.  Consumers who are taking the time to type in a part number are undoubtedly more ready to buy, so it is even more important that they are able to find what they are looking for.

EasyAsk has the ability to index part and model numbers comprehensively, indexing all variations to ensure that users can find the product, even if they forget or mistype part of the number.

EasyAsk’s ‘Part Number Expander’

A ‘Part Number Expander’ is especially useful for complex part numbers that include a combination of letters, numbers and other characters.  A user might forget whether characters were separated by a hyphen or a slash, or might omit letters on the end.

The Part Number Expander takes each part number and creates all the different versions of terms and inserts them into the searchable index so that if any of them are searched for, they will match to the product.  The code is broken up into parts and the separators are substituted in all combinations.

For example, if the part number is

123-HC/1345AB

the Part Number Expander would index:

123-HC-1345AB                                     123

123/HC/1345AB                                    123-HC

123/HC-1345AB                                    HC

123 HC 1345AB                         1345

…among many other combinations.

If a customer types a part/model number that is slightly different (for example, using spaces instead of hyphens) the correct product will still be found.

Ecklerscorvette.com demonstrates how the Part Number Expander can avoid no results for customers:

The part number for this disc brake set is 25-261256-1.  If a customer replaces the hyphens with spaces, the exact product is still returned.

Scary Statistic #3

If people have a negative experience on mobile, they’re 62% less likely to purchase from you in the future[3]

A negative experience will stay with prospects longer than a positive one, so if you want your mobile customers to become regular, you’ll need to make sure you’re not putting them off with a poor user experience compared to your desktop site.

Does your site have a mobile responsive design, so that the text, images, and menus change according to the screen size?  Furthermore, as your site adapts to a mobile size, do you show relevant categories and attributes, as opposed to just the first ones from the desktop site.

Customers using a mobile eCommerce site are more likely to use voice input, and therefore different word choices and sentence structures when speaking.  Your search system needs to be able to cope with voice input and the long-tail queries that are more likely on mobile.

Scary Statistic #4

46% of eCommerce sites have a “No Results Page” implementation that is essentially a dead-end for users, offering no more than a generic set of search tips[4]

Generating a generic ‘Sorry, no results matched your search’ message could be disastrous.  How many shoppers would stay on your site and how many would go straight to your competitor?

There are better ways to use a ‘No Results’ page, but what if it was possible to avoid searches returning no results in the first place?

It may be that a simple spell correction rectifies a ‘No Results’ search, but it is also important to monitor what EasyAsk calls ‘relaxed’ searches.  A relaxed search is one where the search system has modified the search by intelligently dropping (or ‘relaxing’) a term or terms.

For example, if a customer searched for a ‘Men’s black lace jacket’ and there are no products that match this description, we would want the results to show ‘Men’s black jackets’, rather than ‘Men’s lace jackets’ or ‘black lace jackets’, having relaxed the term ‘lace’.  Some searches will inevitably need to be modified and in this example, we want our search system to recognize that the gender stated in the search query is more important than the fabric.

If a user’s search has been modified (such as by spell correcting or relaxation) it is important to display a message explaining the changes to the original search.  For example, a user may search for “purple leather couches” and see the following message:

This user could have searched for leather couches in the first instance and spent a long time scrolling through the pages of results looking for any in purple.  But by using messaging in this way, the user is informed immediately and is more likely to use the search system again.

So-called intelligent ‘No Results’ pages will suggest searches based on what a user asked for, but truly intelligent search systems will change the search to find relevant products based on what the user asked for, even though there may not be an exact match.

Scary Statistic #5

It’s 5 to 25 times more expensive to acquire a new customer than it is to retain an existing one[5]

A worrying number of businesses still don’t use merchandising tools such as cross-sells and up-sells effectively on their eCommerce sites.  These businesses are leaving money on the table.

EasyAsk’s search solution includes a comprehensive set of merchandising controls.  With 9 predefined promotion types, banners and business rules, amongst other functions, the business user is in control of the products that are presented to the customer.

Scary Statistic #6

36% of autocomplete implementations on eCommerce websites do more harm than good[6]

Although basic autocomplete suggestions can be found on 82% of eCommerce sites, most sites do not take the opportunity to capitalize on merchandising while users are searching.

As a user types into a search box supported by EasyAsk, however, search suggestions and category suggestions will be displayed as well as the products themselves.

EasyAsk offers ‘Search as you Type’, or SAYT, because it means a whole lot more than just a list of suggested searches.  It means many possibilities for getting the right products in front of your customers.

SAYT progressively searches for and filters through text.  As a user types a query, suggestions, products, categories, and attributes are found and presented with each keystroke.  This allows a user to stop short of typing the entire word or phrase and find what they were looking for quicker.

Search suggestions as well as relevant and popular products, attributes, and categories can all be displayed in an easy to use interface.

Here is an example from EasyAsk customer personalizationmall.com:

The user is looking for a wedding gift and the letters ‘wedd’ have been typed into the search box on the desktop site so far.  The above drop-down panel is displayed without needing to execute the search.  Alongside the search suggestions in the right-hand column, a popular category to browse and 7 products are displayed, based on the first search prediction, ‘wedding’.  Scrolling through the search suggestions using the down and up arrows updates the real-time search and therefore the categories and products displayed.  Personalization Mall could have also configured their search so that it updates just by a mouse hover for a certain amount of time.

Typed characters are shown in bold in the list of suggestions, with the rest of the suggestion in normal type.  Often, autocomplete systems only show suggestions that begin with the typed characters, but we can see here that the suggestions can contain ‘wedd’ anywhere.

Presenting customers with the most relevant search, product and category suggestions is essential.

Conclusion

When your site search is performing well, customers won’t be scared off, and your business won’t become one of the statistics above.

Getting the right products in front of the customer as quickly as possible shortens the path to conversion, keeping your customers and your bank balance happy.

Follow the tips and best practices in EasyAsk’s recently released eGuide: “Preparing for the Holiday Season: A Guide for your eCommerce Site” to ensure your customers find the right products the first time.

[1] https://baymard.com/blog/ecommerce-search-report-and-benchmark

[2] https://baymard.com/blog/ecommerce-search-report-and-benchmark

[3] https://www.thinkwithgoogle.com/intl/en-gb/advertising-channels/mobile/few-tips-speed-your-mobile-site-and-tools-test-it/

[4] https://baymard.com/ecommerce-search/benchmark/page-types/no-search-results-page

[5] https://hbr.org/2014/10/the-value-of-keeping-the-right-customers

[6] https://www.smashingmagazine.com/2014/08/the-current-state-of-e-commerce-search/

The post Six Scary Site Search Statistics appeared first on EasyAsk.

What is Conversational Commerce?

The term ‘Conversational Commerce’ is used to describe the connection between Sellers and Buyers through messaging and chat applications. Many people now like to use chat systems to accomplish different tasks, but until fairly recently, this kind of interaction has predominantly been used for accessing support, such as customer services. But what if online retailers could use Conversational Commerce to provide a better, more personalized user experience for their shoppers?

Gartner research shows that by 2020:

• 30% of digital commerce revenue growth will be attributable to artificial intelligence technologies, such as those that power conversational commerce.

• 5% of all digital commerce transactions will come from a smart machine, such as those that power conversational commerce.

As people become more accustomed to interacting in a conversational way, they will be increasingly likely to want to use the same conversational mode when finding products.

Mirroring the Store Experience

When a customer walks into a physical store, the sales associate can ask a series of questions to narrow down the choice and focus in on the right products for the customer. In a human context, the sales associate has the necessary knowledge about the products to filter down to a few products.

This is what retailers should be trying to achieve online with Conversational Commerce.

When shopping online, a Conversational Commerce system should intelligently suggest appropriate ways of limiting a set of products. You need to make sure that your system has the intelligence to ask your customer the right questions.

Intelligent Questions and Responses

Let’s compare the in-store experience to one that could be achieved via Conversational Commerce:

Store Sales Associate                                                             Conversational AI-powered Search Engine

Just like with the in-store experience, the Conversational Commerce engine asks questions in a logical order and uses the responses to intelligently suggest attributes to refine the search further.

However your customers wish to interact with you, they should have a similar experience. But the Conversational Commerce experience shown above is only possible with the support of powerful, intuitive technology. This kind of advanced interaction requires an AI-based engine that can understand what the next set of attributes (prompts for the user) should be.

Are You Ready?

With the research showing the pattern for Artificial Intelligence to be the biggest influence on eCommerce over the coming years, it is time to make sure that your search system will be able to keep up. Whether using text or voice input, your customers will be progressively accustomed to chat-based interactions and will expect this format when buying online. By adopting an intuitive AI-based search system that can cope with the demands of Conversational Commerce, you will be able to fast-track your customers to the right products every time.

The post What is Conversational Commerce and what does it mean for eCommerce? appeared first on EasyAsk.

Search is essential in eCommerce – it is the gateway. Search is how consumers express what they want and if they don’t find what they want, they can’t buy it. People who choose to search have a far better idea of what they are looking for than those who browse, and are therefore far more likely to make a purchase. This means that understanding the intent of the shopper, however it is worded, is essential to conversion in eCommerce.

This is increasingly important with the proliferation of voice and the adoption of Natural Language searching by the general public. Home Voice Assistants, such as Alexa and Google Home, which were initially used for music, have gone a lot further and are getting smarter. According to new data from Loup Ventures, all Voice Assistants tested had improved in terms of questions answered correctly, with Siri making the most improvement.

From Keywords to Natural Language

Do people generally use Natural Language Search? Most might say, ‘no, not really’. But the truth is that everyone uses AI/NL search everyday, provided you have a computer or Smartphone. Do you ever search on the Internet?   You’re using Google or Bing or maybe Yahoo. All are AI/NL search engines and are incredibly smart. In 2011, Google was hit by a torpedo with the words ‘SIRI’ on it. Google immediately acquired an AI/NL search company and threw out years of keyword search technology: instantly obsolete.

Now people are becoming used to using Natural Language to talk to their smart home devices, but how do they interact with onsite search?

It’s a huge shame, but unfortunately people have become accustomed to the fact that eCommerce Search Engines can’t usually handle queries with more than one or two words, as most of them use obsolete keyword search. Even when using voice search, they assume that they need to think carefully about what the Search Engine is likely to understand, search, then probably rephrase.

But thanks to Home Voice Assistants, when users pick up their phones to use voice search, they’re increasingly likely to speak using Natural Language as opposed to keywords. When people speak, they naturally throw in extra words so an intuitive Natural Language Engine is needed to understand these longer-tail queries.

The beauty of having a true Natural Language Engine is that the customer can be understood as if they were talking to a Sales Associate. By leveraging Natural Language processing, the burden is on the Search Engine, not on the person talking.

If a customer walked into a North Face store, they might say to a sales associate, “I’m looking for a new waterproof jacket for my wife please.” Using these same words in a voice search on thenorthface.com brings back the following results:

The Search Engine has returned 18 highly relevant results.

Similarly, if a customer walked into a Timberland store, they might ask the Sales Associate, “Do you have any ladies field boots please?” In a voice search on timberland.com, exactly the right product is returned immediately:

Both Timberland and The North Face use EasyAsk to power their search. Their online customers can use voice search to describe exactly what they’re looking for as if they were in a store. These major brands have experienced dramatic revenue boosts between 37-70%.

EasyAsk’s search engine understands these types of queries. Will your Search Engine fail as more people search in this way, or will you be ready for the future because your Search Engine understands how people speak? Using a Natural Language Search Engine allows even small businesses to compete with the search quality of Amazon. You don’t need repetitive shopping behavior data to deliver fantastic results. Natural Language levels the playing field.

Encouraging your users to use voice search (perhaps by adding a microphone icon in the search bar) will mean that they provide more information about what they’re looking for. This in turn will mean that your users will see exactly the right results on the first page. Less time spent finding what they’re looking for results in a higher chance of conversion and higher revenue for your business.

The norm for voice interactions is changing. The future starts now.

“EasyAsk understands exactly what your customers are looking for. Delivering the right results, the first time. Everytime.”

Craig Bassin, CEO EasyAsk

The post Using AI-based Natural Language to improve eCommerce appeared first on EasyAsk.

The Price is Right

Pricing is a critical component of a B2B eCommerce site. There’s nothing more disastrous than a customer seeing the wrong price for a product. The emphasis should be on accuracy and processing speed.

It is common for B2B prices to be individualized based on factors such as contract, purchasing frequency, and volume. Sometimes bulk prices are displayed, grouped according to the number bought.

There are 2 main pricing situations that your search system will need to cater for. We will explore them and discover how best they can be handled:

1.    Price Groups

Rather than allocating individual prices for every customer, some businesses have levels or groups of prices, e.g. Level ‘A’ to ‘E’. Depending on the group level allocated to the customer, they’ll see one of a number of prices. In these situations, if the customer is identified, the search system can index all prices and decide whether to pass back, for example, the Level ‘A’, Level ‘B’ price. This situation works well when there are up to about 10 price levels.

2.    Dynamic Pricing

In this situation, every customer has negotiated prices, based on volume or contract etc. and the search system can’t know the price in advance. There are several ways in which a search system can handle dynamic pricing:

The search system indexes a standard price, and a message is displayed alongside the product on the search results page along the lines of:

“This is the standard price. For your pricing, view the product details.”

When the customer accesses the product details screen, the price for that particular customer is calculated and displayed. The advantage of this method is that price attribute filters, such as price sliders or selectors, can be displayed on the search results page, giving users the option to filter results based on the standard prices.

For each page of results, the ecommerce system calculates and retrieves the prices for the products that are going to be displayed on that page. Most sites only show one page at a time, approximately 10-12 products. Once the search system has passed back the product IDs, it can calculate the prices based on pricing rules, which can then be shown on the product results page. The search system uses a pricing engine to pass back appropriate prices. The disadvantage of this method is that any price attributes on the search results page become invalid.

An advanced, flexible search system can call a pricing engine as part of its process. This means that it can retrieve exact pricing before the attributes are calculated, passing back the correct pricing for each customer. This method allows for totally dynamic pricing. For every product in the results, a price is needed, which does mean that page load time can be affected. For on-premise B2B customers, this overhead would be reduced because the pricing engine will be running on the same internal network, or even the same server that the search system is running on.

Multiple Options

When displaying search results, there is sometimes the need for the price to be more than a single number. Sometimes a set of prices according to volume is required. The search system will need to be able to pass all prices back, perhaps displaying them in a table showing quantity vs price. Does your search system have the ability to pass back multiple prices?

Flexibility is the Answer

Every B2B business has differing needs, and it is essential that search systems are flexible to reflect this. EasyAsk can index multiple prices, calling out to a pricing engine if required, and pass back pricing structures in the results, as opposed to just a simple price. It may be that a business has a set of thresholds for discounts, or individualized pricing based on customer ID. EasyAsk adapts to all circumstances. This isn’t the case for all search systems.

Why Choose EasyAsk?

EasyAsk offers the only site search and merchandising tool designed exclusively for the rigors and challenges of B2B eCommerce. EasyAsk can be configured for any platform, either commercial or built in-house.

EasyAsk has long served the B2B customer segment and over 200 B2B distributors have chosen us to power their B2B eCommerce sites, including: Aramark, Demco, Kaman Industries, Tacoma Screw, and Crown Packaging.

The post B2B Series Challenge 4: Dynamic Pricing appeared first on EasyAsk.

According to Forrester, B2B eCommerce in the U.S. will hit $1.2 trillion by 2021, seeing a Compound Annual Growth Rate (CAGR) of 7.4% over the next four years. It is therefore essential that B2B businesses optimize the experience for their customers online. B2B sites have typically been known as less usable, but it is time for them to catch up with B2C and make it really easy for customers to do business. B2B eCommerce has unique complexities, which present unique challenges and therefore require a unique set of best practices. We will explore these challenges in our B2B blog series and offer advice and solutions to ensure that your B2B site delivers a superior experience.

Customer-Specific Catalogs

Providing customer-specific catalogs is a unique search requirement for B2B companies and can present unique challenges when it comes to eCommerce. But if it is done well, the personalized experience for your B2B customers will certainly pay dividends.

There are 4 possible situations that a B2B company may need to cater for:

1. The company has products that all customers can see and buy.
2. Certain customers are only authorized to buy from a particular range or category of products. When the customer searches, it is important that they can only view the products that are available for them to buy.
3. Similarly, the availability of products may be based on location. Customers in the North-East might only see products that are stocked in the North-East warehouse. Location of the stock also limits which products a customer should see.
4. There may be custom products produced by a company that are only available to one particular customer. For example, coffee companies need branded cups, so it is important that those custom products are in the supplier’s catalog, but cannot be purchased by anyone else.

Differing needs

Within a typical B2C system, the search system would search the entire catalog and show results, but in the above situations, the catalog indexing process needs to define who can buy which products so that the search system is able to present products in the results correctly. This can become very complex, which is why out-of-the-box search systems can’t handle it. EasyAsk provides a custom implementation for each customer so that any of the challenges described above can be handled.

A paper products manufacturer became an EasyAsk customer and now has certain products in their catalog that are marked with customer IDs, while other products are marked as being global. Their coffee store customer buys branded cups, so when they log in the customer ID is passed to EasyAsk, who pass back only the right products.

The implementation of customer-specific catalogs varies completely between B2B customers, so it isn’t possible to just use defined rules; the flexibility to support all different circumstances is necessary.

B2B Personalization

Being able to search and see personalized results based on pre-negotiated terms is imperative for your B2B customers. They should never see a product that isn’t available for them to buy. Your search system should be aware of product availability for any given customer. Is your search system up to this?

EasyAsk is up to the challenge

EasyAsk offers the only site search and merchandising tool designed exclusively for the rigors and challenges of B2B eCommerce. EasyAsk can be configured for any platform, either commercial or built in-house.

EasyAsk has long served the B2B customer segment and over 200 B2B distributors have chosen us to power their B2B eCommerce sites, including: Aramark, Demco, Kaman Industries, Tacoma Screw, and Crown Packaging.

The post B2B Series Challenge 3: Customer-Specific Catalogs appeared first on EasyAsk.

Photo by Bruce Mars on Unsplash

Typeahead… autocomplete… incremental search: many attempts have been made in recent years to speed up shopper’s searches. At EasyAsk, we offer ‘Search As You Type’, or SAYT (pronounced Say-it), because it means a whole lot more than just a list of suggested searches. It means many possibilities for getting the right products in front of your customers.

SAYT progressively searches for and filters through text. As a user types a query, suggestions, products, categories, and attributes are found and presented with each keystroke. This allows a user to stop short of typing the entire word or phrase and find what they were looking for quicker.

Don’t forget, a majority of searchers still make their purchases on a desktop, as this chart from December 2017 shows:

Most search software will show search suggestions, and many now display products. But does your search provider include price grouping or category and attribute options as part of their SAYT?

Far smarter than traditional ‘type-ahead’, EasyAsk’s Search As You Type functionality dynamically returns relevant products as the shopper types their query. Search suggestions as well as relevant and popular products, attributes, and categories can all be displayed in an easy to use interface. Let’s take EasyAsk customer personalizationmall.com as an example:

The user is looking for an anniversary gift and the letters “ann” have been typed into the search. The above drop-down panel is displayed without needing to execute the search. Alongside the search suggestions in the right-hand column, a popular category to browse, and 7 products are displayed, based on the first search prediction, “anniversary”. Scrolling through the search suggestions using the down and up arrows updates the real-time search and therefore the categories and products displayed. Personalization Mall could have also configured their search so that it updates just by a mouse hover for a certain amount of time.

Typed characters are shown in bold in the list of suggestions, with the rest of the suggestion in normal type. It is good practice to highlight matching characters to the user in this way. Often, auto-complete systems only show suggestions that begin with the typed characters, but we can see here that the suggestions can contain “ann” anywhere.

Presenting customers with the most relevant search, product and category suggestions is essential. Consequently, getting the right products in front of the customer as quickly as possible shortens the path to conversion.

What next?

A novel approach to SAYT is personalized SAYT. It is possible to use a customer’s search history for that site to find suggestions for the first few characters typed, then for subsequent characters to display suggestions based on the most popular searches overall.

Another EasyAsk customer, Timberland, opted to configure their site search in this way. Timberland stored each of their customer’s searches in a cookie on their browser, so that when a customer started typing a search, they would see suggestions based on their personal most popular searches. After two or three characters had been typed, Timberland’s site would call EasyAsk to retrieve the most popular searches for all customers.

This is just one example of the flexibility and variety that EasyAsk can deliver in terms of customization. Another useful feature is the ability to pre-populate the suggestions file with part numbers, so that when the user starts to type in a part number, the remainder will be auto-filled.

Consumer expectations are changing. How often do they actually expect to finish typing a search? Increasing numbers of users are programmed to look for autocomplete, so businesses should understand how important, yet simple, SAYT can be.

“From the point of view of interface engineering, the advantages of incremental searching are so numerous, and the advantages of delimited searches so few, that I can see almost no occasions when a delimited search would be preferred.” – Jef Raskin, The Humane Interface

The post Search As You Type: Keeping lazy searchers happy appeared first on EasyAsk.

Conversion rates for mobile commerce on smartphones is only one-third the rate on traditional desktops. While many e-commerce firms have launched mobile sites that are well designed for the display aspects of the device, they lack additional usability features for a truly engaging mobile shopping experience.

To gain competitive advantage and improve customer conversion, mobile commerce sites can take advantage of mobile search powered by voice and natural language to deliver a more engaging mobile shopping experience. Watch our video to see how EasyAsk gives your customers the freedom of speech to purchase faster and more often.

The post Improving Mobile Commerce Conversion Rates appeared first on EasyAsk.