Author Archive for: Matt

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.

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.

A recent piece by Allison Enright for Internet Retailer shares a discovery by Rakuten Inc.  Their discovery states that “U.S. consumers cite price most often as the prime factor in choosing to make a purchase online, according to an online survey of more than 5,300 consumers in a dozen countries. 75% of U.S. respondents rank price as the most important factor, while the global average stands at 61%.  The survey included responses from consumers in the United Kingdom, Germany, Austria, France, Spain, the United States, Brazil, Taiwan, Japan, Indonesia, Thailand and Malaysia. Rakuten, which is based in Japan, operates marketplaces in all those countries. It is the second-largest eCommerce company in Asia, according to Internet Retailer’s Asia 500.”

With it being fairly obvious that price is so important, offering a discounted price should be the ultimate money maker… as long as your customers know you are offering discounted items.  So I sat down with Ben Rudnick, Director of Field Technical Services at EasyAsk, to discuss how a retailer could use EasyAsk to entice buyers through promotions and business rules.

Here is what he had to say:

“This price sensitivity can be used to drive sales through targeted email campaigns, sorting product results and more with EasyAsk.  For example, for a price conscious customer who buys Tools, a set of products could be selected such as “Tools on sale with discount over 60%” and with a single link from within the email, the site product search could deliver those products, sorted by decreasing discount percentage.  With EasyAsk a single campaign landing page can serve many email campaigns for the future.  The products are selected for each campaign within the EasyAsk’s Natural Language tools.  For each email campaign the link can point to the same landing page, passing the EasyAsk campaign selection as part of the search. In addition the request passed to EasyAsk could also sort by your choice of: price, margin, discount percentage, price sensitivity score and more.”

EasyAsk is more than just eCommerce Site Search and Navigation.  It’s Natural Language engine puts the power in the hands of the Merchandisers, and the examples Ben mentioned are just a few of the many ways that EasyAsk can help your eCommerce Site do its job to the best of its abilities.  Come see what else we can help you accomplish.  Visit our website or give us a call at 781-402-5641.

Today’s blog is a video i discovered thanks to MultiChannel Merchant, where their Senior Content Manager, Tim Parry talks to CommerceV3 founders Nathan Focht and Blake Ellis about recent eCommerce trends, and some changes that have been made in the last five years.  In this video, they discuss eCommerce site usability, homepage issues, mobile issues and much more.

Enjoy!

These issues they bring up, whether it be usability, eCommerce Site Search problems, issues with mobile, homepage issues, content issues, whatever they may be, we at EasyAsk can help make sure your website does its job to the best of its abilities.  Let us show you how.  Visit our website or give us a call at 781-402-5641.

Shopping cart abandonment is one of the most popular occurrences when it comes to eCommerce.  Nearly 72 percent of eCommerce shoppers add items to their cart but never complete their purchase.  In this second part of a two-part infographic created by SeeWhy, you’ll see how the behavior of eCommerce shoppers, whether they be new shoppers or returning customers.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Nutshell:

Ninety-nine percent of new customers will not buy from your eCommerce site on their first visit.  Of those new customers who abandon their cart, one quarter of them will not return.  The percentage of returning customers who abandon their shopping cart is about 50-50 on who returns to buy and who does not.  The average time delay between a customers first visit and them buying from your site is about 20 minutes.  And 72 percent of visitors will make a purchase in the first 12 hours.  As far as understanding cart abandonment in a 28-day period, one-time abandoners have an 18 percent chance of making a purchase, serial abandoners have a 48 percent chance of making a purchase, and Recent Goal Abandoners (meaning they’ve already made a purchase before) have a 57 percent chance of making a purchase.  Abandonment rates are higher among those with lower totals in their shopping cart.

This is just more fuel for you, the eCommerce Merchant, to use in your defense against shopping cart abandonment.  The more you know, the more you can do to help increase your conversion rates and average order sizes.  To learn more about what else you can do to increase your conversion rates and average order sizes, visit our website or give us a call at 781-402-5641.

This week’s infographic brings tips on your shopping cart for your eCommerce Site.  The shopping cart, being the final step in the conversion from window-shopper to buyer, doesn’t ever really make the sale, but it sure can brake it.  To avoid losing the sale in the final steps, take heed to this infographic by Demac Media.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The most commonly used ideas for the Shopping Cart are:

No more than 5 pages to complete the check-out process. The sweet spot for input fields is between 21-28. Prominent features to use are multiple shipping options, express check-out, guest check-out, gift cards, and promo codes/coupons. Go with the standard of white background and black text for the majority of it, but adding some color for flare helps when it’s in the correct place. And the use of smarter technology helps to determine what credit card is used based on the first four numbers, and can automatically fill in city, state and country based on the zip code.

These are just a few tips to help convert your shoppers to buyers in the final stages of the sale process. To see what else EasyAsk can do to help convert your shoppers into buyers, visit our website or call us at 781-402-5641.