Things Not Strings: Google’s New Hotel Profiles Exemplify Its Approach to Entities
Google’s Knowledge Graph ambitions are expanding to include obviating heavy reliance on secondary sources like Wikipedia and being able instead to classify and cross-reference information as a native, self-sustaining activity on web pages themselves. That’s what makes a recent patent filing different from the evidence of the Knowledge Graph we’ve already seen in the wild.
While this more ambitious way of surfacing information about entities is not yet standard, in researching Google’s new interface for hotels, I think I’m seeing evidence of a real-world example.
Heard on the Street, Episode 23: Google, AI, 5G and Marketing Champagne
What do Google’s AI-fueled search results, 5G, and marketing champagne all have in common? They’re the central topics of a roundtable discussion on the latest episode of Street Fight’s podcast, Heard on the Street.
As we do quarterly, this is a bonus episode that puts aside our typical interview format and instead invites the leading thinkers from the Street Fight newsroom and executive ranks to discuss news and insights that are top of mind.
Human Judgment, Automation, and the Future of Ad Tech
For now, I propose two major concerns—two challenges, even, for further thought—surrounding AI for the ad tech industry. The first is that the datafication of human experience that has allowed for precise ad targeting needs to be radically reconsidered, not just in terms of what can be done to obtain the consent of consumers for data collection, as the rising privacy movement has called tech companies to consider, but also in terms of what is lost and what is truly gained when the attributes of real people are transformed into consumer data. The second is that the human-machine hybrid decision-making model, while surely the best available in a hypothetical set that also includes human-only and machine-only models, will have to grapple with the bias and poor decisions of the humans who program the machines that will take on the task of regulating large platforms at scale.
AI Technology is Getting within Reach for Small Restaurants
Rodion Yeroshek: The majority of restaurant businesses, especially the small ones, remain slow adopters and non-adopters of AI technology. People may think that the introduction of AI in small restaurant operations is nothing more than jumping on the bandwagon. However, research on the impact of AI on the world economy by McKinsey Global Institute warns the naysayers. The research predicts that by 2030 active adopters of AI technologies could double their cash flow, while non-adopters could lose up to 20% of theirs. This is a hint for restaurant managers who plan to stay in business for the next 10-15 years that it’s time they embrace AI tools or prepare to lose a big part of their market share for good.
7 Delivery Trends You Should Know in 2019
Greater customer expectations and technological advancements are driving big changes in delivery. What’s more, the delivery experience has emerged as a differentiating factor for customers when choosing one retailer over another. eCommerce retailers that operate solely online and omnichannel retailers that offer a physical and digital presence are both beginning to expand their delivery options to meet customer demand. Here are seven trends that will define retail delivery during 2019.
5 Platforms Using AI to Analyze Customer Reviews
Beyond the star ratings lies a wealth of information. Sentiment and opinions can be used to shape the way brands develop their highest-selling products. Given the volume of reviews posted each day, however, it would be impossible for most major brands to analyze every customer reaction individually. Instead, a growing number of brands are utilizing artificial intelligence (AI) technology to extract and analyze the sentiment from product reviews. Here are five examples of platforms that offer this type of AI technology for analyzing customer feedback posted online.
The Future of AI Is Here: Reflections on IBM Think
Damian Rollison: Among hundreds of sessions, exhibits, and demos, one theme came through clearly at IBM Think this month in San Francisco: for large enterprises especially, the AI-driven future for which we’ve been told to prepare is already here. In fact, enterprise companies are using IBM’s Watson technologies today to address a myriad of challenges inherent in the scale of those businesses.
Adjust Leverages AI to Neutralize Ad Fraud
Advertisers and brands are expected to lose an estimated $50 billion as a result of ad fraud by 2025, with one of the most problematic types of ad fraud involving bots designed to mimic human behaviors. Using bots, fraudsters can imitate clicks and engagement KPIs on ad campaigns, wreaking havoc for mobile ad vendors and the advertisers that work with them. So what’s the solution? Firms like Unbotify are pioneering a new approach to bot detection and digital fraud prevention using artificial intelligence and machine learning. Unbotify’s solution analyzes human behavior patterns within websites’ and mobile apps’ user flows in order to differentiate between bots and humans.
Data Science as a Solution: conDati Opens Doors for Digital Retailers
The pitch is that today’s marketers with omnichannel inspirations need a machine learning-driven platform that will not only assess the success of campaigns across several media but also point them toward paths for future success. That’s an expensive technical infrastructure to create in-house, and conDati’s betting its solution is worth the spend.
How Brands Are Using AI to Fight Back Against Dark Marketing
According to some estimates, as many as 85% of Facebook ads and 60% of YouTube ads are hidden from public view. The practice is even more common on Twitter, where an estimated 90% of ads are hidden. What does that mean, exactly? Rather than posting their messages publicly, major brands are creating social media posts or sponsored content that is only shown to targeted audiences. Unlike organic or boosted posts, these targeted ads don’t show up on the company’s timelines or all of their followers’ feeds.
Google’s Soft-Power Approach to Super Bowl Ads
When it came to the Super Bowl, Google opted not to put the spotlight on flashy new products but rather to emphasize the good it can do for the world at a time when it’s “don’t be evil” slogan of yore has become prime material for parody. During the big game, ads for products as seemingly disparate as Pringles, tax software, and beer pointed to a present haunted by tech’s infiltration of domestic life and machines’ superiority to humans.
Voice Search Readiness in 2019 and Beyond
Bernadette Coleman: 2019 is here. While the focus in recent weeks has been predictions on the digital marketing trends that are expected to emerge this year, I would argue that one of the most important measures brands need to take in 2019 is to implement a full-scale voice search readiness strategy, if they have not already.
Standard Cognition Democratizes the Cashierless Model, Providing Solution for Traditional Stores
Standard Cognition offers a product called Standard Checkout that retrofits cashier-based grocery stores into cashierless systems. Unlike the new cashierless Amazon Go, Standard Cognition is not a grocery chain itself, but instead a solution for chains that compete with Amazon Go, co-founder and COO Michael Suswal told Street Fight.
Despite AI Advances, Consumers Crave Human Interactions
Using the latest artificial intelligence technology, brands are finding new ways to streamline and automate the customer experience. But a new report shows that type of streamlined experience might be the exact opposite of what consumers actually want when they interact with their favorite brands.
How AI Can Help CPGs Meet Millennial and Gen-Z Expectations
Last year, almost half of Amazon’s private-label sales were in consumer-packaged goods. Pre-Amazon, legacy CPGs once would’ve been the beneficiary of that demand. CPGs have struggled to evolve with younger consumer preferences. Here’s what I mean, along with ways AI can help them improve.
AI Is No Magic Bullet for Policing Hateful Content
The task Facebook must take up as it attempts to police hateful content is one inseparable from political values, human judgment, and the interpretation of statements that need to be parsed by well-trained eyes and bright minds with a stomach for horror to boot. While machines will play an indispensable role in content moderation on a platform of Facebook’s scale, they will be far from sufficient. That’s because monitoring hate speech touches on nothing less than some of humanistic inquiry’s age-old questions: the debatable violence, status of truth, and foundations of meaning in language.