Key components of AI/Natural Language include:

• Natural Language Understanding (NLU): This involves the ability of a computer system to comprehend and interpret the meaning of text or speech. It includes tasks such as part-of-speech tagging, named entity recognition, sentiment analysis, and semantic parsing.
• Natural Language Generation (NLG): This aspect deals with the generation of human-like text or speech based on a given input. NLG is used in applications like chatbots, content creation, and automated report generation.
• Natural Language Query (NLQ): This technology provides the ability to access data, in almost any structure, create dictionaries that extend link synonyms from content within the data structure and allow for ad hoc Q&A naturally. 
• Machine Translation: This involves the conversion of text from one language to another. Systems like Google Translate are examples of machine translation applications.
• Speech Recognition: This is the process of converting spoken language into written text. Applications like Siri, Google Assistant, and speech-to-text software utilize this technology.
• Dialog Systems and Chatbots: These systems engage in conversations with users, either through text or speech, and aim to provide relevant and helpful responses. They are used in customer service, virtual assistants, and more.
• Sentiment Analysis: This involves determining the sentiment or emotion expressed in a piece of text. It’s commonly used for tasks like social media monitoring and customer feedback analysis.
• Text Summarization: This involves generating concise and coherent summaries of longer pieces of text. It’s used in tasks like summarizing news articles or research papers.
• Question Answering: This involves providing accurate answers to questions posed in natural language. Systems like IBM’s Watson are examples of question-answering applications.
• Language Modeling: This is a fundamental task in NLP where a model is trained to predict the next word in a sentence given the context of the preceding words. This is the basis for many advanced NLP applications.

NLP has a wide range of applications, including but not limited to:

• Customer service chatbots
• eCommerce search, recommendations, and personalization
• Language translation services
• Sentiment analysis for social media monitoring
• Medical record analysis for healthcare
• Personalized content recommendation
• Automatic text summarization for news articles
• Speech-to-text and text-to-speech systems
• Virtual assistants like Siri, Alexa, and Google Assistant

Overall, NLP is a crucial aspect of AI that enables machines to interact with humans in a more natural and intuitive way, opening up a wide range of possibilities for automation and enhanced user experiences. And this is what separates EasyAsk from our competitors. EasyAsk is a true AI/Natural Language search, run by a true Natural Language Processing engine.

The post AI/Natural Language & Mastering It to Launch Your eCom Site appeared first on EasyAsk.

• Speech Recognition: AI/Natural Language driven speech recognition technology converts spoken language into written text. This is the foundational step for enabling mobile voice commerce. It allows users to interact with their devices and applications using their voice.
• Intent Recognition: NLP algorithms are used to understand the intent behind a user’s input. This helps the system comprehend what the user is trying to achieve. For instance, if a user says, “Order a large pepperoni pizza,” the AI should recognize the intent to place a pizza order.
• Context Understanding: NLP models are capable of maintaining context within a conversation. This is essential for providing coherent responses and understanding follow-up questions or statements. It helps in creating a more natural and engaging conversation.
• Personalization and User Profiling: AI-powered systems can learn from user interactions to provide personalized experiences. They can remember preferences, order history, and other relevant information to enhance the customer’s experience.
• Product Recommendations: Using machine learning algorithms, the system can analyze a user’s preferences and behavior to make relevant product recommendations. For example, if a user frequently orders vegetarian dishes, the system can suggest vegetarian options first.
• Order Management and Tracking: AI can facilitate the entire transaction process, from order placement to payment processing. It can also provide updates on the status of the order and estimated delivery times.
• Natural Language Generation (NLG): NLG is a technology that allows the system to generate human-like responses. This is crucial for creating a conversational and engaging experience for users.
• Multi-language Support: NLP models can be trained to understand and respond in multiple languages, enabling a broader user base to engage in conversational commerce.
• Voice Authentication and Security: AI can be used for voice biometrics to authenticate users. This adds an extra layer of security to mobile voice commerce applications.
• Customer Support and Assistance: AI-powered chatbots and voice assistants can provide instant support, answer queries, and guide users through the purchasing process. This can significantly enhance customer satisfaction.
• Feedback and Improvement: AI can analyze user feedback to improve the conversational experience over time. It can learn from mistakes and adapt to user preferences.

By incorporating AI and NLP into mobile voice conversational commerce, e-retailers can create more intuitive, efficient, and personalized experiences for their customers, ultimately driving higher conversion rates, significantly higher revenue, and customer satisfaction.

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But what are we actually talking about? What is the breakthrough here and what does that mean for you?  

ChatGPT is now the latest tectonic shift in A.I. functionality and truly is that breakthrough. Why?  Because OpenAI has achieved the breakthrough in User Experience.  They didn’t create it, but they did kind of perfect it.  It’s called ad hoc query and the concept has been around since the early 1980s when the relational database boom began (as well as my career, btw). We used to promote ad hoc query at Oracle and it was very real, provided you could speak SQL, or use one of the graphic tools that generated the appropriate SQL. 

Fast forward to the next step in creating the perfect UX. 2011 – Apple launched the iPhone 4s with Siri integrated. For the very first time, millions of us could access the perfect mobile user experience. Hit a button, ask a question, get the answer. Again, ad hoc query, but now Mobile and Voice enabled. 

The very first time I tried this, I recognized THIS was the future. This was the way business applications would be architected, this was the way we would all shop on eCommerce platforms: intelligent, intuitive, interactive. It’s actually what we do here at EasyAsk and Gartner gave us their ‘Cool Vendor’ award for this… but it took another decade for it to be rediscovered and mainstreamed. ChatGPT did that, so ‘thank you’, OpenAI. Combining an Artificial Intelligence/Natural Language query engine with Large Language Models generating comprehensive content for seemingly endless Q&A: Generative A.I.

Like Siri, then OK Google, ChatGPT has the unenviable task of having to ‘index the universe’. So, a common concern is, “is this answer 100% accurate?”. You’ll notice that Chat now qualifies the answer with “to the best of my understanding” or something close. To be clear, this is not a criticism. The tech is fantastic. It’s just always going to be an issue, what content is the answer based upon? They’ve done an amazing job bringing forth a transformative technology and instantly launched the concept of ‘ad hoc query’ forward. We should all be grateful. It IS the perfect User Experience. 

So where do we take this going forward? We, like OpenAI believe in the power of Artificial Intelligence and Natural Language mapped to various business applications and vertical market solutions. The future is very bright to transform the User Experience for Business Intelligence and Analytics, CRM, Medical records, eCommerce and so much more. Congratulations and thank you to OpenAI for paving the road here. I believe it will quickly become a freeway! Off we go. 

The post Artificial Intelligence for Business 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 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/

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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.

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 store has been directly impacted by the pandemic and stores are only now gradually starting to reopen.  These events have resulted in unprecedented changes to consumer behavior and most transactions now moving online.

Customers have been forced from their daily routines, which included visiting a brick-and-mortar store.  They have been buying what they need online.  Data from a new Capgemini Research Institute report shows that 59% of consumers worldwide had high levels of interaction with physical stores before COVID-19, but now only 24% expect to return to that level.  This is a tectonic shift in consumer shopping habits and is here to stay.  Shoppers will certainly return to brick-and-mortar stores over time, but the more intuitive and happy eCommerce shoppers are, the more likely they are to continue to use eCommerce channels.  Unless companies can quickly adapt to changing circumstances, Amazon will be the new habit for those who couldn’t buy elsewhere.  The next challenge for e-retailers is to provide a superior shopping experience, on par with Amazon.

Search on eCommerce sites has always been important.  After all, searching is shopping in an eCommerce context.  With so many more people currently using eCommerce, 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.  If a shopper uses your search box, they have an idea of what they’re looking for, so you need to make sure they find it, fast.  These shoppers don’t want to waste time repeating searches or navigating through your site.  Your search box is your best Salesperson, especially in this season.

In this blog series, we will be exploring how your business can move, grow, and thrive online.  If there were ever a time to make sure that your customers can buy from you wherever they are, using any device (phone, PC, or tablet), it is surely now.

We will be exploring in more detail the following elements of good search over the coming months:

AI Natural Language Search

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.

We will explore how an AI/Natural Language search solution will ensure that your customers can find what they’re looking for, utilizing intelligent linguistic algorithms, synonym recognition, part number expansion, and more.

Instant Search

Presenting customers with the most relevant search, product, and category suggestions is essential.  But it is easy to get 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[2]

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 Search-As-You-Type (SAYT) returns correct results as you’re typing in the search box, refining as you continue to enhance, à la Google.  We will explore how to maximize the SAYT experience for your users.

Business Rules

We will demonstrate how you, the business user, can be in control of the products that are presented to your customers.  For example, using simple natural language rules to promote your own brand, to promote another brand during a campaign, or to ‘bury’ products which are low inventory.

Mobile

In a mobile environment, particularly with the proliferation of voice search, we have no idea how a user is going to search.  People don’t speak in keywords, they speak in sentences.

If people have a negative experience on mobile,

they’re 62% less likely to purchase from you in the future[3]

We’ll show you how to make sure you’re not putting off your customers with a poor user experience compared to your desktop site.

Personalization

Personalization is a valuable and effective part of the shopping experience.  But personalization must always be just that – a part of the shopping experience, not the shopping experience.  Personalization is at its best when it is used in the context of the right set of products to choose from – the most relevant products.  We’ll explore how to make personalization more powerful through great search.

No Results Pages

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.  But what if you could define and control products, categories, and messaging to display and therefore retain otherwise lost customers?

Conversational Commerce

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.  We will be showing how 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.

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

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

[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

The post COVID-19 eCom Blog Series: Why your Search Box is your best Salesperson appeared first on EasyAsk.

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. Many non-essential stores have been directly impacted by the pandemic and forced to close until further notice. These events have resulted in unprecedented changes to consumer behavior and many more transactions moving online.

Customers have been forced to change their daily routines, which included visiting a brick-and-mortar store. Now they buy what they need online. Whether this change in shopping habits is temporary, or whether customers will revert back to shopping in physical stores will all depend on the eCommerce experience that companies provide.

Unless companies can quickly adapt to changing circumstances, Amazon will be the new habit for those who couldn’t buy elsewhere.  It can be deduced therefore, that companies who are resistant to change will come out the other side of the crisis with less money than they had… or even without any business at all.

What is the data saying about eCommerce and Covid-19?

At EasyAsk, we have observed the impact of the Coronavirus on our customers.  Data from our customers shows that in March, many businesses were more or less in paralysis in the wake of the initial lockdown measures.  From April, however, it is an improving picture when it comes to online orders.  Most likely this is due to the initial shock subsiding, and people beginning to realize this was the ‘new normal’ so they could start spending again. One of our customers’ data demonstrates this trend.

Compared to the same period in 2019, the amount of traffic to the eCommerce site in March 2020 was down by 23%.  In April 2020, however, the amount of traffic was up by 19% compared to April 2019.

The same customer recorded even more impressive results concerning revenue.  In March 2020, revenue was down by 7.83% compared to March 2019, however, revenue for April 2020 was up by 100% from last year.

Is the shift towards eCommerce a surprise?

The truth is, Covid-19 has only accelerated changes to eCommerce that were already well in motion.

Brick-and-mortar operations have been feeling the effects of the shift towards eCommerce long before the effects of the pandemic.  For those companies who do little or no business online, this will be a very hard time to bounce back from.  Those who do 20-30% of their business online will be facing the disastrous prospect of losing most of their revenue if they don’t increase their online presence immediately.

Search on eCommerce sites has always been important.  After all, searching is shopping in an eCommerce context.  In April it was even more important, and if companies are to retain the new customers acquired during the lockdown, site search will be even more critical.

Over the coming months, we will be exploring how your business can move, grow, and thrive online.  If there were ever a time to make sure that your customers can buy from you wherever they are, using any device (phone, PC, or tablet), it is surely now.

The post COVID-19: When has eCommerce ever mattered more? appeared first on EasyAsk.

The Infor Storefront marketplace has been left in chaos with many customers very unsure of the future of Storefront, others even searching for a new platform.

As EasyAsk has always been the core engine powering Storefront, we’ve been working directly with increasing numbers of Storefront customers.  We have found there is a lot of room for improvement.

Additionally, almost all Storefront customers’ UX is obsolete and visually stuck in an outdated ‘aol.com’ time warp.

The September TUG webinar, focussed on the future of Storefront and how EasyAsk and mStorefront could significantly and immediately enhance a Storefront user’s experience.  Read the summary or watch the full recording.

At the November 12^th TUG webinar, we took a deeper dive into the capabilities and enhancements that you can expect from the partnership between EasyAsk and mStorefront.  With advanced Search, Analytics and Merchandising, as well as a thoroughly enhanced, responsive, modern and user-friendly front-end, plus a Mobile Smartphone UX, you can take your significant Storefront investment forward into the next decade.

We have created a Roadmap showing what you can expect from EasyAsk and mStorefront in 2020:

• A fresh, responsive design for your Storefront site, which will work equally well on all devices

• Enhanced scanner functionality

An internal sales team would be able to scan products to retrieve product information for customer orders, etc..  mStorefront now allows scanning via Bluetooth-enabled devices and smartphones.

• Single Sign-On Extension

The ability for mStorefront to integrate with any Security Assertion Markup Language (SAML) based service will allow for logging users into the application based on their sessions in another context.

This is beneficial for account managers that need to utilize different applications including mStorefront to service their customer base.

• Continuous UI/UX enhancements

mStorefront creates a consistent brand across your content website and your customers’ shopping experience.  Your customers will feel like they’re underneath one roof, and no matter what platform they’re viewing from, they’ll see the same

branding and design.

• Integration with Content Management System (CMS)

This is a fully-fledged solution where mStorefront can integrate with Drupal CMS and give users the ability to control pre-determined content, create new content pages, enable blogs, as well as control headers, images, and other sections of a company’s main marketing site.  If your customers are shopping/browsing or navigating from page-to-page, they will always feel like they are on one integrated, responsive site.

• Enhanced Google Analytics

The following Google Analytics extensions will be added:

• Enhanced Google Analytics: giving you visibility of how customers interact with mStorefront, including understanding customers’ shopping behavior, product performance, among others.
• User session tracking: giving you visibility of how particular users shop the site and allowing you to analyze the signed-in user experience.
• Tag manager: giving you the ability to add and update your own tags for conversion tracking, site analytics, remarketing, and more.
• Ecommerce Analytics: tracking orders including order values, ordered products and more.

New EasyAsk features:

• Landing pages

An EasyAsk landing page is a set of products that the merchandising team wants to show customers, which are typically referenced by a specific URL. This URL could be referenced in email marketing or on another part of the site.

A landing page will contain products as well as banners and other content.  In EasyAsk Studio, it is possible to define which products and other content should be displayed on a new landing page very easily using natural language.

• Banners

A banner is visual content that can be triggered to be shown on predefined areas of any screen.  A banner might be an image, a video, a slider – or enter html into the definition to display anything required.  Banners can be triggered by a number of situations, such as:

• By the presence of a set of products. For example, if 50% or more of the products that a customer is looking at are tools, then you could show a banner for a tool brand that you’re currently promoting
• If a user views a certain set of products, or uses a certain category, you want to put a visual element at the top of that subcategory page
• By certain terminology used in a search. For example, if a customer uses the term ‘tool’, a banner could be displayed for a tool brand that you’re promoting

Combinations of these triggers allow any situation to be catered for.  The business user has comprehensive control. Banners can have a variety of associated actions, such as:

• Go to a URL
• Go to a product category or subcategory
• Do an attribute selection, e.g. brand = xyz, optionally qualified with a category
• Do a product search, optionally qualified with a category selection. For example, run a search for oil, but only within pump products
• No action – the banner is simply for information or aesthetics

• Messaging on EasyAsk driven Product Results Pages

Messaging on product results pages is used when users search and EasyAsk changes that search in some way in order to get better results.  It is an opportunity to show alternative products or searches when the original search may not find anything and to inform customers why this has happened.

Messaging can be used in the following instances:

• Spell correction, for example:

“sofaa” returned no results, so we’re showing you results for “sofa” instead.

• Out of stock products, for example:

“Gracey Recliner” returned no results, so we’re showing you results for “leather recliner” instead. The Gracey recliner is currently unavailable.

• Products not in the catalogue, for example:

Sorry, we don’t stock Canon, but Nikon are an excellent alternative.

• Part of the customer’s search has been relaxed, for example:

Sorry, we don’t have purple leather couches, but here are the leather couches we do have.

Messaging on product result pages is straightforward to set up and configure within EasyAsk Studio.  It allows merchandisers to drive a better shopping experience for their customers without relying on programmers to ‘code’ in order to explain to the searcher what they are seeing.  This can significantly reduce bounce rates.

• ‘No Results’ page content

EasyAsk allows you to control which suggested product sets and what messaging is displayed.  The ‘No Results page might contain one or more of the following:

• Show alternative products. This is an opportunity to promote specific products or groups of products.  You might display top sellers or campaign-related products, for example, summer specials.  Here is an example of promoted products from pmall.com:

• Make some search suggestions. The possibilities here for using the No Results page are numerous.  You could make some search suggestions that will return results using some of the words from the original search or suggest that the customer removes one or more filters from their search.  You could display the top trending searches made on the site (clickable).

• Invite the shopper to further action. Suggest that the shopper browses the site by category and direct them to where on the page they can do this.  You might display some clickable popular categories. Here is an example from timberland.com:

If you stock numerous brands, you might suggest popular brands or featured designers, or even just list all available brands.  It is also possible to display a ‘Still can’t find what you’re looking for?’ section, giving the opportunity for a chatbot to step in or providing a telephone number or email address.  The following pop-up was triggered from the No Results page, once again on timberland.com:

All of the above options for your ‘No Results’ page can be easily defined and controlled within EasyAsk Studio.

• Merchandising slots

A merchandising slot is a part of a screen, often on the home page, where merchandisers want to highlight certain products or sets of products, for example, own brand specials or this week’s offers. These product groupings can be defined using EasyAsk natural language rules and are completely dynamic.  For example, if a company had own-brand specials and had a rule that defines a merchandising slot to show these products, then any new own-brand products would automatically be included. This functionality is rule-based rather than product-based.

Alternatively, it is possible to specify a set of product IDs stipulated by the marketing team to be shown in a merchandising slot.  There are no limits to the number of supported merchandising slots; the front-end design dictates how much can be shown.

• Enhanced Search As You Type (SAYT)

SAYT is a very advanced autocomplete/type-ahead system that is designed to put the right products in front of the user at the earliest opportunity.  The latest EasyAsk SAYT system uses templates, making it very easy to change.  It includes features such as the ability to change how many products and suggested searches are displayed and whether to show relevant attributes.  EasyAsk provides multiple templates to choose from, or your business can define their own.

The above drop-down panel is displayed on pmall.com as a user begins to type their search.

We’d love to show you how we can easily transform your dated Storefront site into a cutting edge B2B eCommerce site without tying up valuable resources and potentially a $300,000+ investment by you to get there – get in touch with us to find out more.

The post 2020 Storefront Roadmap: How EasyAsk and mStorefront are working together to take your B2B business into the next decade 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.

The EasyAsk team recently visited the Windy City to be a part of IRCE at RetailX. This year’s event merged three shows into one, with the Internet Retailer Conference and Exhibition (IRCE) holding its 15^th annual event. RetailX attracted 20,000 attendees and more than 1,200 exhibiting brands, with EasyAsk proud to be counted among them.

We were able to impress visitors to the EasyAsk booth by demonstrating how outstanding EasyAsk’s Search and Navigation solution is. In case you missed the show, here is what one of the EasyAsk team could have shown you:

The North Face use EasyAsk to power their search so it’s a great example of some of the functionality. This voice search contains references to gender, price and color, as well as redundant words, such as ‘I’m looking for’. EasyAsk has the ability to cope with all of this information and returns the following results:

The EasyAsk engine has understood that ‘wife’ is a synonym for ‘womens’ and brings back only red, waterproof, ladies jackets priced less than $200. Although each of the 11 results are available in different colors, the thumbnail picture presented in the results is always in the red tone.

Contrast this successful search to the same search using Amazon.com:

Amazon’s engine cannot cope with the complexities of this query and the top suggested searches are for ‘I’m red waterproof’ and ‘I’m looking waterproof’.

It is clear that EasyAsk’s understanding of natural language is far superior to that of the eCommerce giant, Amazon. We think this is why the IRCE attendees were so impressed…

It’s worth taking a closer look when it comes to search and merchandising solutions. We’d love to show you further how EasyAsk out-performs Amazon and competes with Google. We can help you help your customers to find the right products, first time.

More information about IRCE can be found at www.irce.com

Take a closer look at EasyAsk’s search and merchandising solutions at www.easyask.com

The post IRCE @ RetailX 2019: How EasyAsk impressed prospective customers appeared first on EasyAsk.