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AI/Natural Language & Mastering It to Launch Your eCom Site

Natural Language Processing (NLP) is a subfield of Artificial Intelligence (AI) that focuses on the interaction between computers and human language. AI/Natural Language encompasses the development of algorithms and models that enable machines to understand, interpret, generate, and respond to human language in a way that is both meaningful and contextually appropriate.

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.

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AI/Natural Language: Conversational, Mobile Voice UX for eCommerce

AI/Natural Language Processing (NLP) plays a crucial role in enabling mobile voice conversational commerce and can greatly enhance the user experience. AI/Natural Language technology leverages the capabilities of artificial intelligence to understand, process, and respond to human language in a way that mimics human conversation. Here’s how Artificial Intelligence and NLP contribute to mobile voice conversational commerce, enabling one-touch perfect search, and driving significantly more revenue:

  • 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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Artificial Intelligence for Business

Artificial Intelligence… it’s here, it’s there, it’s… (to quote Ted Lasso) every —-ing where!

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. 

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Six Scary Site Search Statistics

and how to make sure your customers don’t run away screaming

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… Read More

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Covid-19 eCom Blog Series: The Importance of Search for eCommerce

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*

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COVID-19 eCom Blog Series: Why your Search Box is your best Salesperson

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 Read More

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COVID-19: When has eCommerce ever mattered more?

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. Read More

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

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.

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EasyAsk and mStorefront: a leading edge B2B solution

At recent TUG sessions, we’ve seen that Infor placed Storefront into an extended maintenance mode. Michael Watkins at Quality Pool Supply (a Storefront user) estimates the cost of replacing Storefront at $350-500K, but the great news is that there really is an alternative, and therefore a future for Storefront.

Last month, EasyAsk ran a live webinar entitled “The Future of Storefront: EasyAsk and mStorefront Alliance”, alongside Jonathan Kronberg, CEO at TriGroup.  If you missed it, you can read the summary of the webinar content below – or you can watch the full recording here.

 

Craig Bassin, CEO at EasyAsk, began by outlining the current situation facing Storefront customers and how best to move forward.

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Six Scary Site Search Statistics

and how to make sure your customers don’t run away screaming

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.

Read More

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