“1) Improved product search for misspelt words
- On average, 25% of all ecommerce search queries are misspelt, and the modern shoppers won’t take the blame for typing the wrong command
- Zalando decided to tackle this problem using deep learning. With the help of machine learning, Zalando can now parse 300,000 products in two seconds and deliver on-point product suggestions despite inaccuracies.
2) Voice shopping experience guided by AI
- Customers in the UK and US can also call Asos’ Enki Chatbot using the Google Assistant app or Google Home Speaker to browse the 85,000 products on the website and cherry-pick personalised suggestions.
3) Camera-powered visual search
- Boohoo, an apparel brand targeting image-oriented Millennial and Gen Z consumers, clearly took note. The company recently partnered with Syte – a startup offering image recognition technology for retailers – to add visual search functionality to their mobile website. The Camera Button added to the search bar, allows users to upload their pictures and discover the most visually similar products in stock. Shoppers are then presented with a selection of relevant products, additionally populated with even more similar styles and “Shop the Look” curated picks.
- BooHoo also reported a 135% increase in pages viewed per session and a 12% increase in average order value”
- “Just a few days after VentureBeat reported that Pinterest chief technology officer (CTO) Vanja Josifovski was jumping ship for Airbnb, the game of musical chairs is continuing with news that Pinterest has hired Walmart CTO Jeremy King as its new head of engineering.
- The announcement comes less than 24 hours after an internal memo revealed that King was leaving Walmart after nearly eight years at the company. Most recently, King served as EVP and CTO for Walmart U.S., where he spearheaded the company’s ecommerce technology efforts.
- Pinterest is, of course, an entirely different kind of business from Walmart — but there are enough similarities to make King a good fit for the role. The San Francisco-based company has evolved a great deal over the past decade, transitioning from being an online social pinboard of sorts to become more of a “visual discovery engine” that leans heavily on computer vision and artificial intelligence. A big part of its current business is making it easier for people to buy things that they see online and in the real world.”
“The world’s largest retailer is using Jetblack, a money-losing personal-shopping service, to develop artificial intelligence to compete with e-commerce giant Amazon”
“Among the thought leaders sharing their intelligence were:
- Michelle Boockoff-Bajdek, CMO of IBM Watson,
We caught up with all three business leaders after their presentations to talk about today’s real-world applications of AI.”
- Ricky Ray Butler, CEO of BEN (Branded Entertainment Network)
- Phil Schraeder, president and COO of ad exchange GumGum.
- “Using Internet of Things (IoT) technology, connected devices and artificial intelligence (AI), the company is on a quest to turn cruise ships into “smart cities at sea.”
- The Ocean Medallion—“the most extensive experiential Internet of Things that’s ever been done,” according to Padgett—relies on 7,000 sensors placed throughout the multiple-decked ship. There are hundreds of miles of cables on the ship that support the technology. Every stateroom door and staff mobile device is also a sensor to enable the Internet of Things experience. Each passenger’s name is carved into a Medallion that’s connected to them, tracks their movements throughout the ship and works in conjunction with Ocean Compass, the app and service that displays personalized recommendations for every passenger on 4,000 digital interaction points from 55-inch high-res screens distributed throughout every area of the ship.”
I was up at 2:00 am this morning, Spring Break…no idea why, and since I was awake decided to work on my March Madness basketball bracket.
While researching free-throw percentages, defensive efficiency and strength of schedule I was excited to find a new tool marketed by Google Cloud.
At first glance it’s an interesting way to create/customize an algorithm for SMEs (subject matter experts) without requiring assistance from engineers or data scientists.
There must have been an issue with the tool because I kept receiving this “Technical Foul” message.
However, I wanted to share because it’s a very interesting use-case for how an engineer and data scientist can create a tool for thousands of people to create their own algorithm without ever writing a single line of code.
Here’s a post on the topic from Alison Wagonfeld – Chief Marketing Officer, Google Cloud.
“In connection with this year’s March Madness tournament, we’re extending our NCAA campaign to developers everywhere with training that enables anyone with an interest in basketball and data analytics to dive in. More and more developers want to use Google Cloud, and we are ready to meet that demand. (In fact, a recent study by Indeed found that Google Cloud skills are the fastest cloud skills growing in demand.)
We’ve published a new series of Qwiklabs training to teach you how to use BigQuery to analyze NCAA basketball data with SQL and build a machine learning model to make your own predictions. At Google Cloud Next on April 9-11 (right after the Final Four), we’ll be hosting two bootcamps (Sunday and Monday) that use NCAA data to show you how to build a data science environment covering ingest, exploration, training, evaluation, deployment, and prediction. We’re co-hosting a predictive modeling competition with Kaggle that lets data scientists show their chops (and compete to win $10,000!). And we’ve published a technical blog post and a whitepaper to give you a deeper look under the hood.”
“Nandan Sheth, Head of Global Digital Commerce at First Data stated, “Nearly $15 billion in ecommerce revenue is missed annually, because merchants haven’t had a reliable authorization optimization strategy,” “With our new Authorization Optimization solution, we’re providing our enterprise clients with powerful back-end support, fueled by industry-leading data intelligence,” he added.”
“Even Barbie has had a smart makeover. The Hello Barbie toy uses natural language processing and machine learning (both subsets of AI) to listen and respond to a child. Inside Barbie’s necklace is a microphone that records what the child says and transmits it to a server for analysis. Then, choosing from 8,000 dialogue options, the system chooses the most appropriate response for Barbie to say. All this happens in under a second.”
- “Yet with SAP’s 2018 Digital Transformation Executive Study finding just 3 per cent of retailers have completed digital transformation projects, most of which focused on efficiency and cost cutting, there’s clearly still a long way to go before brands successfully harness digital for more disruptive innovation in the retail experience.
- Again, however, only a small percentage of data is being used by retailers in decision making. While these organisations tend to collect as much data as they can, squirrelling away for future use, they’re still not able to ascertain its significance, Schneider agreed.
- An example is Adidas in Russia, which used existing cameras plus RFID readers and RFID tags on garments and products to improve real-time inventory accuracy in its physical store from 60 per cent to 99 per cent. Adidas is now looking to rollout the approach globally.”
“Adobe Sensei, our AI and ML technology, is purpose-built for digital experiences and focuses on three intelligence domains: creative, content and experience. Today, it is powering dozens of features across all of Adobe’s products, but I am most excited about what is coming next. For example, we are working to infuse AI into new mediums like augmented reality (AR).”