Rage against the machine, data privacy legislation, leaked search secrets for marketers, retail media ad spend
June has been a fascinating month for industry innovation, discussion around AI continues on, this time with a lens on privacy. Read on for a glimpse into some of the hottest trends backed by insights and from top-tier publications like The Atlantic, The Hill, Fast Company, AdExchanger, Ad Age, and Digiday and research from Forrester and eMarketer.
No, not the iconic rock band from the ‘90s. This rage is coming from humans and aimed squarely at GenAI. While marketing and advertising agencies are excited about AI, Forrester Research highlights significant obstacles: lack of expertise, skills, or training required to implement GenAI, coupled with cultural resistance, is holding many back. There is widespread fear of GenAI making employees jobs obsolete, a concern that echoes across various industries. Job displacement is a legitimate concern, particularly given the turbulence of the last five years between the pandemic, working from home, a forced return to work (for many), and now technological advances that are, once again, stirring a sense of instability.
However, the significance of AI and its economic implications are huge – 77% of agency leaders stated they “believe that GenAI is a disruptor and nearly a third call GenAI a major disruption that will change their business forever.” Forrester recommends that there needs to be an investment in essential AI literacy to give employees a confidence boost and thwart intimidation. With proper training, employees can feel secure, and AI can be leveraged to its fullest, introducing efficiencies while still letting creatives be creative.
US lawmakers are pushing for federal data privacy law, but the legislation faces criticism from businesses and privacy advocates. On June 27, The Hill reported that The House Energy and Commerce Committee canceled a planned markup, delivering a setback to the proposed privacy bill due to major pushback from Republican leadership.
“The bill was a long-awaited proposal for privacy advocates, who say they are concerned about the lack of federal privacy rules. While some states have passed their own data privacy laws, the U.S. government has fallen behind other countries in setting rules in place in an increasingly digital world.”
Preceding this decision, in early June, TechCrunch wrote, “for AI to really succeed, we need to protect private data.” The article claims that the current iteration of AI, or AI 1.0, lacks personalization, which must change for AI to become useful. However, that isn’t without a major stipulation: trust. “For AI to understand us, it must have data about us, and before we allow that, we must have trust. Trust is the most important factor blocking the progress of this industry today.”
The article continues with a call for regulation and protection: “We can build trust with regulation that protects private data and promotes transparency. Unfortunately, this is not the regulation that Washington has proposed so far.
As much as we want data privacy to be simple, it’s not. While most agree on the necessity of regulation moving forward, the exact framework remains uncertain.
However, in the EU, data privacy laws have been met with less resistance. The EU General Data Protection Regulation (GDPR) is described as “the toughest privacy and security law in the world.” Data Axle operates within the guidelines set within, so while the US is moving a bit more slowly, companies still have the autonomy to implement their own data privacy policies that create a space for trust.
“Being able to share information about a group of people without compromising any individual person’s privacy kinda sounds like a form of wizardry,” wrote AdExchanger’s Allison Schiff. And she’s right. But what is differential privacy and how does it work?
Differential privacy is a mathematically rigorous framework for releasing statistical information about datasets while protecting the privacy of individual data subjects. So, marketers, advertisers, and content creators get the perks of data-driven insights and analytics, without infringing on privacy, and audiences can share data without fear of future targeting and divulging information they otherwise wouldn’t want shared. It seems like a win-win.
Of course, like any technology, there are tradeoffs. “Adding more statistical noise or randomness to a data set means the privacy guarantee is stronger, but the output will likely be less accurate, and vice versa. The ratio depends on your risk tolerance level, what you’re trying to achieve and the sensitivity of the data set in question.”
That said, it is a practical and promising solution to privacy, and it provides a relatively balanced solution for marketers and consumers.
Earlier this month, Ad Age reported that “more than 2,000 recently leaked Google documents gave everyone a look behind the SEO curtain.” Of these, some debunked common SEO beliefs and others affirmed them.
Don’t want to read the full article? Here they are:
In a nutshell, “while there are differing opinions on key takeaways from the leaks, everyone seems to agree: Experimentation is one time-tested SEO optimization best practice that still applies. Test out new approaches, monitor how they impact your site performance and pivot accordingly.”
According to Digiday, “retail media is marketers’ third-most used marketing channel.” Further, eMarketer reports that, “retail media search ad spend will reach $33.86 billion this year, and more than double by 2028 when it will hit $76.83 billion.” It also notes that, over the same period, “traditional search ad spending growth will decline, slowing to 0.9% in 2028.”
Retail media is seemingly where it’s at. Harvard Business Review looks at its growth, noting “major retailers are today, most notably Amazon, are creating and operating their own advertising platforms — and they’re making millions doing it.” They further stated, “few retailers anticipated 10 years ago that advertising would become a huge growth driver for them, but Amazon’s success has goaded them into action. Retailers as varied as Dick’s Sporting Goods, Home Depot, Instacart, Lowe’s, Macy’s, Ulta, and Walmart now all own and operate retail media platforms. In 2023, Walmart earned $3.4 billion from retail advertising, and Target and Instacart both earned more than $1 billion.”
It’s a lucrative program to pursue, but it’s not without its challenges. Most notably, the article states that organizational tensions and the retailer-manufacturer relationship is tricky. Additionally, there is an issue of transparency. “Brands cannot see which impressions they are buying, the margins the retailer is earning, or the attribution algorithm that is used to measure performance.” As a result, some brands have refused to participate until ad-detection software is integrated into a retail media platform.
Lastly, there’s the issue of bargaining power. “In the short term, retailers need appealing content from major brands to gain traction for their media platforms. However, once a platform reaches scale, bargaining power tends to shift in favor of the retailer. If retail media makes customers more loyal, retailers will no longer depend upon brands to attract customers.”
Moving forward, retailers and manufacturers will need to develop distinctive approaches that consider both the benefits and challenges to retail media and find operational and technological solutions that cater to their unique needs.
We have some exciting news to share and even more to come next month! To get the latest, visit our website, follow us on social, or reach out! As always, we invite you to sign up for our newsletter and get the latest news directly in your inbox!
Data Axle Expands Enterprise Team to Deliver Next-Generation Marketing Solutions: On June 25, we announced the expansion of our enterprise solutions team. Since its start in 1972, Data Axle has prided itself on its commitment to its clients. This team will build upon that core value, leveraging its deep industry knowledge and expertise and taking a client-first approach to every aspect of the business and its solutions during a time of pronounced and strategic company growth. Additionally, the group will be focused on executing the vision set earlier this year by Data Axle Chief Executive Officer Andrew Frawley and includes additional investments in its next-generation data management application, Audience360™, as well as infusing AI across company solutions.
Courtney is a seasoned communications and public relations professional with 17+ years of experience working in both the public and private sectors in diverse leadership roles. As Data Axle’s Senior Public Relations Manager, she is intently focused on elevating the company’s media relations presence and increasing brand loyalty and awareness through landing coverage in top-tier media outlets.