Retailers are using artificial intelligence to enhance the customer experience and also run their own back-end operations more efficiently.
McDonald’s waited until it could produce an AI-driven app that provides customers with personalized deals based on their purchasing history. In other words, McDonald’s bet on quality over quantity. This, of course, is just one of the ways that AI presents opportunities and challenges alike in regards to martech.
As we’ve previously noted, as AI adoption increases, brands are searching for a competitive edge. McDonald’s is no exception to this, and a look at how the company is using AI is instructive as to the opportunities AI presents for other firms.
Communicating with brands on social media has become the norm for consumers. Surveys show that roughly half of all consumers who engage with brands on social media are reaching out about customer care concerns, and more than 65% of social media users across all platforms expect brands to respond, regardless of whether the initial outreach was via private messages or public posts.
Those expectations have only heightened over the past six months, and many brands have had to pivot their customer support and engagement priorities on the fly.
In this episode of Location Weekly, the Location-Based Marketing Association covers Walmart partnering to let people buy groceries through Yahoo Mail, Iceland’s Airport using sensors and AI to streamline passenger flow, a project between Trident and Instagram that can get you to the Grammy’s, and MUJI taking their products to the mountains.
In this article, we will discuss the ways artificial intelligence is changing marketing and why this marks a positive change. This article will also discuss how metadata can be more revealing than event data itself when collected and analyzed in aggregate, and why making all this data functional is the main strength of AI technology.
My personal experience getting sick during the pandemic also got me thinking about how easy it is to spread the virus just by moving around and how important it is to abide by government guidance to stay at home or at least limit your movements. As someone who works in the location data industry, I have an appreciation for the mass movement of people, and staying at home and limiting contact with other people is the right thing to do right now.
I also had the chance to think about how location data could be used to help hospitals, governments, and businesses combat the spread of the virus.
“Ambient computing” is actually a catch-all term for several new technologies. These include Internet of Things (IoT) devices, AI-driven devices, and cloud storage solutions that allow previously impossible amounts of data to be stored and processed.
The advantage of looking at these technologies under one term, though, is that it allows us to see the future of marketing more holistically. And that’s what we’ll look at in this article.
I’m fresh from a couple of days wandering the halls of the Consumer Electronics Show, affectionately known as CES — the annual conference that descends upon Las Vegas in January and proffers the latest in technological solutions to improve every aspect of our daily lives. This is my first time attending the world’s biggest technology conference, where 4,500 companies this year are vying for the attention of 180,000 attendees, according to my Uber driver.
As I made my way through the crowds at the massive Las Vegas Convention Center and other conference venues, I tried to get a sense of the common themes defining consumer innovation as we begin a new decade.
The end of the decade marks a challenging time for marketers as they attempt to envision the next 10 years. At the turn of the 2010s, no one could have envisioned the advanced AI-powered marketing and campaign automation tools that are available today.
Despite access to smart technology, modern marketers still must balance multiple factors to create business value for all stakeholders, including eliminating boring, ineffective ads, grappling with the automation myth, embracing the data privacy age, and maintaining ethical AI practices.
The devices around us are getting smarter. From the consumer’s perspective, that means refrigerators are sending notifications when the milk is running low, and thermostats are turning down the temperature when there’s no movement in the house. Businesses are relying on the data generated by connected devices to improve algorithms and make their existing products even smarter, but collecting and managing large volumes of data is creating a new set of challenges.
Globally, the IoT market is expected to reach $212 billion by the end of this year. With the worldwide number of IoT-connected devices projected to top 43 billion by 2023, the challenges associated with managing large amounts of data in real-time are growing at a rapid pace.
What if e-commerce retailers could use technology to replicate the role of the in-store sales associate, providing people at home with the type of personal attention that really drives sales?
Technology vendors are working feverishly to make that a reality. Using artificial intelligence and voice assistants, like Amazon’s Alexa, Google Home, and Siri, online retailers are beginning to imagine a world where shoppers can ask their voice companions for recommendations on product fit or gift suggestions in specific price ranges. There may even be a time, not too far in the future, when shoppers can get personal feedback during try-ons inside their own closets, thanks to “smart” mirrors and other virtual reality technology.
Organizations investing billions in enterprise software realized the obvious: that easier-to-use technology was not only more scalable internally, but that it delivered better ROI. Accessible platforms could be optimized faster and were “stickier” across teams. This gave way to the consumerization movement in IT and enterprise.
As we head into 2019, the enterprise’s consumerization is well established. Yet when it comes to AI, which will see over $235 billion in investment by 2025, this idea of consumer-like UI has largely fallen by the wayside.
That has to change.
The new 5G standard for phones is just starting to make a splash. There’s a lot to do in the development department and lots of equipment installations necessary before everyone can enjoy 5G hyper speeds.
While there are some predictions on the transition from the current 4G LTE dominance to 5G, nobody really knows how long it will take. But what happens once it does and 5G is the new standard?
Here are five most likely to happen scenarios that await us in the near future.
Despite promises that they would do better, platforms like YouTube, Facebook, and others are still struggling with the issue. Brands don’t want their ads appearing alongside extremist content and hate speech, but flagging every piece of content that could be considered inappropriate is not an easy task.
The challenge has opened the door for a new industry of “authenticators,” which use technology to help brands avoid inappropriate content online. Using artificial intelligence and machine learning, these technology providers are usually able to evaluate the quality of an ad impression in real-time and help their brand clients avoid anything that could be considered inappropriate. Or at least, that’s what the goal is.
The fact that this was an open practice that at least some consumers simply did not understand they were either opting into or automatically participating in points to calls for greater transparency and regulation. Google says it “fell short” of its “high standards” on the issue, but legislation like Europe’s GDPR, CCPA, and legislation in some 10 other US states indicates those standards may be imposed on tech companies by government agencies going forward.
Recently, a number of high-profile tech firms have been uncovered permitting human employees to access private conversations consumers believed were only processed by AI.
Google Assistant, Siri, Cortana, and Amazon’s Alexa have all been placed in the limelight, and now Facebook has also come under fire for letting human employees access sensitive personal conversations for transcription purposes.
In the case of AI assistants, private conversations are primarily harvested from consumers who own and use their devices directly. However, there is an emerging body of evidence that these technologies are also harvesting secondary persons’ conversations — completely unknown to those individuals.
Walmart, Walgreens, and Sephora are all using artificial intelligence technology to improve the retail experience. While the majority of use cases for AI in retail have focused on enhancing the shopping experience for customers, forward-thinking analytics firms are innovating and developing new uses for their existing AI technology.
The analytics firm Fractal Analytics is pushing forward in the retail space with its own solution that relies on AI to forecast the cost of retail store remodels, as well as determine the ROI from large-scale renovation projects. Although Fractal works solely with Fortune 500 companies, the solutions it is developing could be adopted more broadly throughout the retail space.
While just over half of Americans have listened to them, podcasts are finding new audiences every day. U.S. advertisers spent $479 million on podcast ads in 2018, up 53% year-over-year; that figure is expected to hit $1 billion in 2021. And those people who do listen to podcasts listen to them a LOT. Podcasts are the number one audio source by time of consumption among podcast listeners, and weekly listeners consume an average seven podcasts per week, according to Edison Research.
Podcast advertising is rapidly evolving, as are podcasts themselves. It’s no wonder, then, that advertisers could use help identifying the right podcasts for their products and connecting with podcast audiences. Here’s what you need to know about podcasts and their audiences to find the right home for your podcast advertisements.
It’s becoming clear that we’re headed toward a new vision for our devices: the Phone as a Service (PaaS). Yes, sounds crazy, but look at the parallels between your phone and how/why other “X”s have become services:
X-as-a-service (XaaS) is delivery of X directly via the internet, eliminating the need to use and manage multiple and independent solutions on locally hosted devices, right? So, PaaS is the delivery of personalized media via the phone, eliminating the need to use and manage multiple and independent, locally hosted apps. We’re already seeing that happen.
At the beginning of the year, we like to take time and speculate on which data science trends will make the biggest splash in the year. Now that we’re entering the second half of 2019, it is a good time to take a look at our initial assumptions regarding these trends and re-evaluate each one’s impact on the industry.