Blog Directory

Leading from the front is amazon when it opened an AI backed grocery store called Amazon Go. The store does not have any checkouts and this seems to be an attempt towards automation. The customers who use this app can have an entire shopping experience without waiting in long checkout queues. Their stores without checkout counters are designed to detect objects customers pick. The sensors work in co-ordination with image recognition and the amazon accounts are charged as soon as you exit the store. While Amazon Go is still recovering from tech glitches, the idea of automated shopping has created acceptability in consumer’s mind.

Neiman Marcus accelerates image search

This American department store has coupled image search that allows their customers to click pictures of items anywhere and match it to find if any similar product is available in their inventory. It was an excellent approach to enable customer engagement. Besides this Snap, Find, Shop feature, they have used AR in their store that allows shoppers to compare different outfits in a 360 degree view of themselves.

Disney adds magic to SKU organization

Not surprisingly, Disney is one of those few brands that have integrated Artificial intelligence to organize product SKUs and are on their way to create Artificial neural networks. They have launched an ecommerce site, shopDisney that employs AI and machine learning to organize product categorization and site searches for the user. They get relevant product recommendations that are tailored for a wider audience.

Paypal stuns frauds

Paypal is one of those brands that are interested in defeating bad guys at the con using artificial intelligence. After several scams targeted Paypal users, they have decided to detect fraud and manage possible risk with 3 types of modern machine learning algorithms. The system identifies purchase patterns by studying thousands of purchases in the past with fraudulent nature. The idea is to identify the difference between a genuine purchase or that from a list of stolen accounts. As ecommerce continues to grow, the issue of theft will continue to linger but Paypal is a working example for retail brands concerned about data security and theft.

StarBucks barista goes mainstream

Not far behind in the league of brands that experiment with emerging tech is Starbucks. This time, they intend to imbed AI backed voice activated apps from the likes of Siri. The virtual assistant will be a mobile device companion called My Starbucks Barista. It will allow user to place an order by simply tapping a button and talking to the virtual barista. While the order is prepared in the nearby store, you can pick up your drink without waiting in long queues.

Lowe’s sci-fi geek

The famous home improvement retailer brand known Lowe’s has been testing store mapping robots called LoweBots in some of their locations. They are walking sales guides equipped with natural language processing that allows them to process and respond to general queries such as “where is hardware section?” They also have built-in sensors to detect people standing idle and inquire them if they would require help.

Sephora launches beauty advice chatbot

Sephora is home to elaborate range of cosmetics and beauty products and the online shoppers are often intimidated by the idea of product search. For instance, a typical product search query could give about 200 results but Sephora experimented with chatbot giving beauty advice and product suggestions to ease their purchase decision. It’s an incredible sales tactic using AI that seems innovative and garners better engagement.

Macy’s quick answer bots

Macy’s also appears to be ahead of the curve since they adopted Microsoft’s AI to optimize shopping experience and solve customer issues across all channels. The virtual agent answers the general FAQs and make suggestions but if they are unable to give any further answers than the customers are transferred to Live agent for further assistance thereby making the customer experience swift.

In fact, more shoppers enjoy their interaction with chatbots that can address their queries and make recommendations. At the same time, entrepreneurs and startups are searching for competitive chatbots to integrate in their business for better engagement and customer retention. Here’s how these bots can be categorized.

Chatbot evolution: Breaking down the generations

Generation 1: bots answering FAQ

Generation 2: read my mind bots

Generation 3: Ai driven sophisticated interaction

Generation 4: advanced voice/image recognition

Role in conversational commerce

When e-commerce became a sensation, every brand wanted to make sure they catch up to the idea. Eventually, they were also the first to experiment with chatbots. Apple’s Siri, Amazon’s Alexa and Google Assistant soon became the virtual assistants that revolutionized the way consumers interact with brands.

Some interesting and revolutionary ideas came forth as brands joined the bandwagon. They have added their bit of creativity in both operational nature and naming of the bots. Take a look at some of past year’s chatbots:

Dr. Craig Brown 

Dr. Craig Brown is Tech & Business Consultant and a Big Data experts. He is the CEO of STEM Resource Partners and works diligently to increase the use of natural everyday language in technical fields to help facilitate the conversation between Tech companies and professionals. He is also a mentor and the author of the book “Untapped Potential – The Supreme Partnership of Self”. On his website, he shares articles that range from Internet of Things to Machine Learning and Big Data.

Rebecca Fiebrink

Rebecca Friebrink is a professor at Goldsmiths, University of London in the UK. She is contributing to the world of AI by developing new technologies to support human-machine interactions. She has developed a software for motion sensing namely the Wekinator, that uses supervised learning algorithms to create new instruments and systems that can respond swiftly to actions. She presented the Wekinator software at the Music Tech Festival in 2015 in London.

Gary Marcus 

Gary is the founder of Geometric Intelligence who have also been the director of Uber AI labs. As a Professor of Psychology and Neural Science at NYU, he has published extensively in fields ranging from human and animal behavior to neuroscience, genetics, and artificial intelligence, often in leading journals such as Science and Nature.

Adam Coates

Adam has served as the Director of the Silicon Valley AI Lab for giant Chinese conglomerate Baidu. He started at Stanford, where he focused on machine learning, perception and vision. He was a Technical leader for application of deep learning to computer vision problems in autonomous driving which was part of his post-doctoral research.

Angelica Lim

She is a Canadian computer scientist with a Ph.D. in AI and emotions. She was part of the project for SoftBank Robotics’ Pepper robot. She is known to understand the importance of communication and has worked on robots and artificial intelligence for over 10 years, and is currently interested in signal processing, machine learning and developmental robotics for intelligent systems, particularly in the field of emotions.

Alec Radford

Alec is a Machine learning developer and researcher at OpenAI, an artificial intelligence non-profit supported by Tesla founder Elon Musk. He is also the co-founder of Indico.io, a company that sells a software product for extracting meaningful insights from data such as text and images. Connect with him on LinkedIn.

Adelyn Zhou

Adelyn Zhou is a technology leader serving in AI and bots. She has been recognized as one of the top 30 people to follow in AI, top 10 people in bots, and top 50 people in growth. She has experience at Nextdoor, Eventbrite and Amazon and has been a leader in the largest bot community of 23,000 members.

Joanna Bryson 

Joanna is a computer scientist at the University of Bath, and an affiliate at the Princeton Center for Information Technology. She has expertise in designing intelligent systems into working AI systems to help understand natural intelligence.

Well, those were some of the top minds keeping us informed about the world of AI. Are you ready to transform your lives to accommodate post-AI revolution? Share with us your thoughts and more avenues uncovered by this massive shift in technology.

We all know how long waiting checkout queues make grocery shopping the most tedious task. But we will not have to wait long for retail stores to adapt to the AI-driven autonomous checkout. Amazon Go is already on its way to launch a new kind of grocery store where no checkout is required. They’re calling it the “Just Walk out” shopping experience for which you need their app on your phone, pick items from their store while the system upgrades its inventory and your virtual cart. A similar prototype is being tested by Standard Cognition that employs a network of cameras to monitor the action of the shopper and then couple machine vision and deep learning to display the items in your virtual cart on your smartphone app (underway).

In order to fit the definition of a “convenience store”, the retail biggies are under pressure to create a better shopping experience and autonomous checkout is their ray of hope. The idea appears promising but is not yet free of glitches.

What’s a virtual cart?

The virtual cart happens to be the software interface for the retail stores planning to limit or recede checkout counters. When you pick up items from a similar store, the sensors recognize the items and add them to your cart against which you will be charged from your account as you walk out of the door. To get a better picture of virtual cart, here’s a glimpse of Amazon Go.

While Amazon Go allows the shopper to scan and enter the store before they begin to shop, the Walmart Scan and Go uses a different approach. At Walmart its more of a self-checkout option where you can scan your items right from your phone and pay via the app.

Fascinating isn’t it!

But so far you will need an employee to verify the receipt on your mobile device. It will take some time before the idea of autonomous checkout gets fully operational. Meanwhile, the futuristic application of AI in retail is rigorously tested. Here are some big questions that caught our attention.

Big questions

Since the AI feature uses cameras, can it keep up with multiple items withdrawn from the aisle when the surrounding space is heavily crowded?

What happens when someone picks an item but places it back at a different position?

Can the system identify damage to the products while mishandling?

Is it really convenience shopping if we need different apps for each store?

So, what do you guys think? Are you excited about the idea of AI backed retail stores? Let us know by sharing your thoughts in the comments section.

It’s a universal fact that all visitors are impatient and slow loading times can be death blow to an otherwise well-design e-commerce website. Preferably, the website should not have too many landing pages and their loading time should not be more than a few seconds. So while designing and coding for the web-pages, page load duration should be kept in mind.

Create a page structure

Most e-commerce web layouts get misleading when they fail to maintain a uniform page structure. When a visitor is navigating between pages, a uniform page layout will not let them get lost in design. For instance, use a similar header and side menu to be displayed on all pages. It keeps the users focused and they don’t have to worry about the change of design as they go deeper into website.

Create organized search

When e-stores maintain and display products in elaborate categories, it creates better search options for visitors. It’s frustrating for a customer to type a search query and receive “nothing found” as a response. The user does not have much patience to keep typing new phrases to get a response. They will not wait to understand how the system of the website works.

The don’ts of UXD in e-commerce site

Flood the page with ads

Too many ads on an e-commerce site is not going to help. In fact, over-crowding of ads will overshadow the actual content. An online shopper has a far less attention span and excessive ads will affect page load times and presents information that they are not looking for. Hence, ads should be kept to a minimum number on e-commerce sites.

Design that affects visitor’s ability to scan the page

As a general practice, most visitors like to scan through a website before visiting a particular page. They wish to observe the e-commerce site and get an idea about the web layout by checking the visual cues such as pictures, headings, CTAs and general content placement. If a website has a complicated design, it will take longer for visitors to have a quick look.

Use too many CTAs competing for attention

First off, an ecommerce site needs to limit the number of Call-to-actions that can be displayed in one page. also, if the site has unrelated content and lacks visual hierarchy, then it will end up confusing the visitor. A page with CTA should limit flashy images and other distracting headings or irrelevant pop-ups. When several things compete for user’s attention, chances are they will end up skipping the CTA you intended them to land up on.

Under-estimate the power of images

Marketers can produce the most lyrical description for a product but if it’s missing the face, then all you are doing is making empty claims. As an online shopper, I have had a fair share of bad images or incorrect images for various product listings in various online stores. Never under-estimate the power of quality images in e-commerce, for they can certainly make or break your deal.