IBM Partners With Visa To Make Its Waston IoT Platform Commerce-Ready

What Happened
IBM will equip its Watson IoT platform with Visa’s token technology to allow trusted connected devices to complete online orders for users within preconfigured permissions. This partnership will allow IBM to integrate Visa’s token service, which assigns a unique digital identifier to information found on payment cards, with connected devices that are plugged into IBM’s cloud infrastructure. The end result is a lot like Amazon’s Dash Replenishment Service (DRS), only replacing the need for a physical push to trigger the purchases with automation enabled by IBM’s cloud computing and Watson’s A.I. smarts.

What Brands Need To Do
While this partnership hasn’t developed any consumer-facing product yet, both companies see new business models emerging from the inspection of IoT and ecommerce. For example, a retailer can leverage this platform to manage their in-store stocks and optimizing the restocking process. CPG brands, on the other hand, could explore the possibility of leveraging this new platform to bring auto-replenishing packages into consumers’ homes. As A.I.-powered solutions start to percolate into a wide range of devices and platforms, brands will need to pay attention to the new possibility in automation and personalization they are set to unleash across industries.


Source: ZDNet

Cathay Pacific Gifts Loyalty Members With Personalized Artwork Based On Travel Data

What Happened
Cathay Pacific is sending its loyalty program members a unique birthday gift – a piece of contemporary artwork created by a special algorithm based on their travel data. Working with McCann Worldgroup, the airline is presenting members of its Marco Polo club a mini-site that visualizes their travel in the past year into a abstract painting, which also comes with built-in options for people to easily share their personalized “artmaps” via social media.

What Brands Need To Do
This serves as a new example of how brands can find interesting ways to utilize the customer data they collect for marketing purposes other than retargeting. By employing a low-level artificial intelligence – in this case, a computer algorithm that generates artwork based on travel data – Cathay Pacific is able to transform data into something personal and share-worthy to its most valued customers.

As marketers continue to explore the possibility that machine learning and AI bring to marketing by powering conversational services and next-level personalizations. brands need to start identifying the kind of unique dataset that they own and feed it into machine learning services to either learn more about their customers or deliver a more personalized customer experience.


Source: Creativity Online


Google And Ivyrevel Developing App That Design Dresses Based On Personal Data

What Happened
Google is teaming up with Ivyrevel, an online-only women’s fashion brand backed by H&M, to develop an Android app that can design a dress for you based on your contextual and activity data, such as location, weather, and physical activity.

Dubbed “Data Dress,” the app will analyze the personal data input, including their activity data once the users opt in. Specifically, the app will use the Google’s Snapshot API to monitor the person’s daily activities, including things like where they went, where they eat dinner or hang out, how often they work out, and so on, for a week and come up with a dress design that best fits their lifestyle. Users will be able to buy the personalized dress directly from the app if they like what they see.

What Brands Need To Do
This app presents an interesting case of how brands can leverage machine learning to offer personalized products and services. For brands, especially those in fashion and retail, it is important to recognize the possibility that AI-powered solutions unleash, which very much relies on the kind of customer data that brands can supply. Therefore, brands should start thinking about what kind of customer data they can feed into machine learning services to gain consumer insights and supplement their targeting and personalization effort, as well as coming up with a clear value exchange they can offer consumers for that data.


Source: TechCrunch


Header image courtesy of Ivyrevel

H&R Block Enlists IBM’s Watson To Help With Preparing Tax Returns

What Happened
IBM’s supercomputer Watson can now add “tax accountant” to its expanding resume, as the company formed a partnership with tax preparation service H&R Block to apply Watson’s cognitive computing power to helping people maximize their tax returns. The two companies created a merged Block-Watson system that uses Watson to analyze the notes that tax preparers put in based on their conversations with clients and suggest possible tax solutions in real time. H&R Blcok says the AI-powered system will serve as many as 11 million clients who visit its offices during this tax season, which the tax preparation company also created a Super Bowl ad to promote.

What Brands Need To Do
This is a new example of brands plugging AI and machine learning solutions into their services to enhance customer experience. Last month at CES 2017, we saw many brands, such as Carnival Cruise and Under Armour, that incorporate AI in one way or another. From the fast development in autonomous cars to smaller home gadgets, artificial intelligence of varying degrees is being integrated to a wide range of products to enable smart automation and personalization solutions. For brands offering services and experiences, the implementation of AI-powered solutions is set to unleash a new kind of customer experiences that they will need to adapt.


Source: MarTech Today

Toyota Taps IBM’s Watson To Generate Ad Scripts

What Happened
Toyota is the latest brand to use IBM’s machine learning program Watson to aid its marketing campaign. To promote its Rav4 Crossover SUV model, the auto brand worked with agency Saatchi & Saatchi Los Angeles to create an interesting digital video campaign built around the idea of encouraging people to crossover and try something new. They supplied Watson with the world’s top 1,000 activities — such as biking, dancing, and cooking — and asked Watson to pair two activities that are rarely associated. The agency then used the Watson-generated pairings to create 300 unique videos, which are being targeted at users on Facebook and Instagram based on the activities they already enjoy doing. For example, a Pilate-lover will see a video spot that suggests they try cosplaying while a kick-boxing enthusiasts may get bird-watching.

What Brands Need To Do
This is a fun, if a bit trite, application of machine learning in marketing campaigns. It provides the agency with some interesting pairings to use for their creatives and, perhaps more importantly, gives the campaign an intriguing, powered-by-A.I. hook. As we pointed out in our CES trend recap, machine learning and artificial intelligence will start to make a strong impact in marketing by powering conversational services and next-level personalizations. Brands need to start identifying the kind of unique dataset that they own and feed it into machine learning services to either learn more about their customers or deliver a more personalized customer experience.


Source: AdAge


Pinterest To Optimize Recommended Pins With Deep Learning

What Happened
Pinterest has started using deep learning to improve the relevance of its Recommended Pins, which shows up when a Pinterest user pins an image to their boards to suggest visually similar posts that they may be interested in as well. This is built upon Pinterest’s existing use of machine learning in visual search, a feature the site first started testing in 2015 and later expanded to more users last summer.

What Brands Need To Do
The use of deep learning — which generally means training artificial neural networks on existing data and teaching them to interpret new data — is something that is emerging as a key industry trend in consumer tech. From the fast development in autonomous cars to AI-powered home gadgets like Amazon’s Echo lineup, artificial intelligence of varying degrees is being integrated to a wide range of products to enable smart automation and personalization solutions. For brands, this means it is time to identify the customer data you leverage to create or partner with tech provider to develop AI-powered, personalized customer experiences.


Source: VentureBeat

CES 2017 Day 1: NVIDIA Applies AI Computing To Gaming, Smart Home, And Self-Driving Cars

NVIDIA CEO Jen-Hsun Huang took the stage at the 50th CES to deliver an opening keynote address that showcased the remarkable advances NVIDIA has made in visual and AI computing, as well as how the chip-making company aims to apply them to a wide range of domains, including gaming, connected TV, smart home, and self-driving cars. Here are the three most important products Huang introduced during his keynote:

GeForce Now for On-Demand Gaming
Competitive gaming has grown into a huge global media phenomenon that attracts huge numbers of viewers worldwide. In fact, Huang called it “the biggest sports event in the world,” citing that there are now 100 million MOBA game players and over 325 million eSports spectators.

With that much consumer attention to capitalize on, NVIDIA is opening up its video game streaming service GeForce Now, previously only available via its own Shield gaming console, and bringing it to PC and Mac to reach more potential players. Using NVIDIA cloud computing powers, PC and Mac devices will be able to run the type of graphically intensive video games it can’t handle locally. The service is set to launch in March and will be priced in a tiered, on-demand manner starting at $25 for 20 hours of play.


For brands, this expansion of GeForce reinforces the growing prominence of the gaming and eSports industry. In the past few years, the competitive gaming industry has quickly grown into a media opportunity that brands should not ignore. Some early-adopting brands, such as Coca-Cola and Snickers, have been sponsoring eSports events to reach its young, male-skewing audience. As media companies race to capture the vast eSports audience, brands, especially those seeking global recognition, should consider leveraging the massive reach of eSports events via sponsorships and ads.

NVIDIA Spot for A Google Assistant-Powered Smart Home
One of the most evident trends we have identified at this year’s CES is how quickly voice assistants led by Amazon’s Alexa have taken over the smart home space as the de-facto interface that facilitates users interactions on those IoT home devices. Now NVIDIA is adding to this trend by introducing Spot, a small connected mic that you can attach to the wall and bring Google Assistant into every corner of your home. NVIDIA Spot, which is set to launch later this year, connects to its new Shield console over Wi-Fi and transfer the voice command back to it for processing. With a few of them strategically placed throughout the house, summoning Google Assistant at home would become a truly ambient experience that seemingly operates without the confines of a hardware device, akin to the way Ironman talks to his digital butler Jarvis in the movies.


With voice-activated assistants quickly conquering the home space and bringing AI-powered voice-activation to mainstream consumers. This means it is time for brands to start exploring how incorporating conversational interfaces may help improve the customer experience, for they offer a way in for those brands to reach consumers at home and connect with them in a more intimate, relaxed context. Therefore, brand marketers, especially those in the CPG, food, and lifestyle categories, need to pay close attention to the developments in the smart home space and start exploring possible partnerships.

Xavier and AI Co-Pilot Show NVIDIA’s Self-Driving Ambitions
At the beginning of his keynote, Huang noted that “GPU-powered deep learning is driving the ability for computers to perceive the world.” Later he added that “AI is the solution to the self-driving cars” when introducing Xavier, NVIDIA’s AI computer for self-driving cars. In addition to this powerful compact processing unit that will power its autonomous car being developed in partnership with Audi, NVIDIA also demoed an interesting “AI Co-pilot” mode, which uses computer vision, machine learning, and natural language processing to turn the self-driving AI software into an all-seeing, all-sensing co-pilot that can alert the drivers of the road conditions they may have missed or not in eyesight via spoken suggestions.

screen-shot-2017-01-04-at-10-24-46-pmThis wave of self-driving innovation is set to bring a seismic change to the auto and transportation industries. And that shakeup is coming at a quicker pace with each announcement like the ones NVIDIA just made. For auto brands, it represents great challenges to adapt to, but also enormous opportunities to redefine the future of driving. For every other brand, the eventual arrival of self-driving cars will free up a significant amount of time spent on driving and transform cars into the next battleground for consumer attention, something that brand marketers need to keep an eye out for.

Uber Acquires Geometric Intelligence To Form An In-House AI Team

What Happened
Uber has acquired a New York-based startup Geometric Intelligence to launch its own in-house research team that focuses on artificial intelligence development, according to The New York Times. This move not only reaffirms Uber’s dedication to improve its algorithms for more efficient routing and ride-sharing, but also signals the company’s growing ambition in developing autonomous vehicles and driverless solutions, to which sophisticated AI and machine learning tools will be crucial.

Why Brands Should Care
As conversational interfaces and cloud-based solutions rise to prominence, AI and machine learning are quickly becoming a hot topic among the tech and ad industries, especially in regard to how they would transform the way we analyze data and extract insights. Already, we are seeing companies like IBM and Oracle integrating their respective machine learning-powered solutions into marketing products, promising profound impact on consumer expectations and brand-consumer interactions.

This is a topic we will be diving into in details in our upcoming Outlook 2017 report. Please check back in early January to read more of our take on this hot industry trend.


Source: The New York Times

Samba TV Acquires Machine Learning Software

Samba TV has acquired Filmaster, a startup based in Warsaw, Poland composed mostly of Data Scientists and developers or Artificial Intelligence software. Described as a service that offers content recommendations using “its own proprietary artificial intelligence and machine learning algorithms”, Filmaster will help boost Samba’s “capabilities in content recommendations and marketing automation”, per Samba TV’s press release.

As the world’s leading provider of Smart TV applications, Samba TV will soon begin incorporating Filmaster’s technology in its software so as to improve the relevance of cross-screen advertising, as Samba TV’s platform is monetized by brand sponsorships. Back in April, the Lab led our parent company Interpublic Group to invest in Samba TV, and we are excited to see what this acquisition may bring for them.

Header image courtesy of Samba TV

How To Be As Good At Targeted Recommendation As Amazon

Read original story on: Wired

Last week, Amazon quietly launched a new service aimed at opening its own AI technology, which its mighty recommendation engine is built on, to all businesses to use. The new service, known as the Amazon Machine Learning Service, is designed to help developers easily integrate targeted recommendation engines based on data and machine learning into their own websites and apps. As part its ever-growing suite of AWS cloud computing services, Amazon continues to claim Internet infrastructures, one piece at a time.