Instagram has updated the grid on all user profiles -- similar to TikTok’s home feed -- altering one of the social-media platform’s original aesthetic features.

Thumbnail images now have a more vertically aligned look, compared to the square image display users have been accustomed to for the past 15 years.

Instagram launched its grid update on the same day TikTok sent announcements to its 170 million users in the U.S. explaining that its service is temporarily unavailable due to a law banning the app in the region. 

Social-media platforms have been preparing for this possibility for months and Instagram is no exception. Over the past week, the Meta-owned app has been working hard to set itself up as the main alternative to TikTok, extending its short-form video feature Reels to three minutes in length (a move also made by YouTube), and launching a new mobile video editing tool, which features “a full suite of creative tools.”

According to Instagram head Adam Mosseri, the shift to a more vertical grid aligns with how people are using the app, and is the first step in further altering users’ grids. 

“We started with the tall grid because most photos and videos that are uploaded to Instagram at this point are vertical and rectangles do a better job showing off those photos and videos,” Mosseri wrote on Threads. “That said, I know some of you spend a lot of time tweaking your grids and this blew all of that up, so we’re going to improve the ability to customize those thumbnails to make it easier to get back to a place you’re happy with.”

In addition, Instagram is planning to move highlights into the grid in a way that doesn’t disturb users’ aesthetic construction, while also making it possible for users to post directly to their grid as to avoid the home feed entirely.

“In order to maintain creator control we’re building a tool so you can re-order your entire grid and make it whatever you want,” Mosseri explains, effectively fulfilling one of the most requested app features to date. 

While some of these features have been in the works for months, they are all likely a response to the U.S. federal government’s earliest concerns over potential national security risks posed by TikTok’s alleged connection to the Chinese government.  

However, as competing social media companies continue to launch TikTok-ified updates to their platforms, hoping to persuade mass user migration, TikTok has already begun restoring service for U.S. users following a series of back-and-forth statements between the company and president-elect Donald Trump. 

AT&T is returning as the presenting sponsor for the College Football Playoff (CFP) National Championship Game in Atlanta, and it has a big party planned ahead of the big game.

The wireless brand is staging a series of experiential activations, including an “AT&T Playoff Playlist Live” concert series at State Farm Arena in Atlanta headlined by rapper Lil Wayne and singer/songwriter Camila Cabello.

AT&T will also host “Playoff Fan Central”  a “curated, immersive experience,” according to the brand. Playoff Fan Central will include an “immersive passing game” placing fans in the quarterback position, and an AI photo both allowing them to join their chosen team and create digital trading cards. NCAA legends such as former Notre Dame quarterback Brady Quinn Colorado Buffaloes star quarterback  Shedeur Sanders will appear IRL.

The CFP National Championship Game Presented by AT&T will be played between the Notre Dame Fighting Irish and Ohio State Buckeyes on  Jan. 20, at Atlanta’s Mercedes-Benz Stadium.

AT&T has partnered with the venue since its 2017 opening, including on the introduction of hands-free biometric ticketing and concessions. The company provides the in-building cellular network for the stadium, which has a capacity of around 75,000.

Broadcast of the game on Monday will include “Connected Cams presented by AT&T,” which will provide close-up views of highlights during the game.

AT&T’s experiential campaign for the CFP National Championship Game follows the launch of the“AT&T Guarantee” campaign during the Orange Bowl game on Jan. 9.

Giving a big push to its fast-growing streaming TV platform, Fox Corp.’s Fox Television Network will simulcast the Super Bowl next month with Tubi -- hoping to boost promotion into more everyday viewing of the service.

And yes, Tubi, a FAST channel (free ad-supported streaming TV) platform, will be offered free to consumers.

In addition, Tubi will offer much pre-Super Bowl programming starting on the Friday before the effort, January 28, on Tubi’s NFL Channel.

On Super Bowl day itself, February 9, Fox Sports will offer a pre-game show “Tubi Red Carpet at the Super Bowl LIX”, starting at 3:30 p.m.

For years, broadcast-centric media companies like Fox Corp. have used the Super Bowl to promote key prime time or special events -- especially those on the rise.

Tubi is one of its upcoming big revenue drivers, where company executives have been estimating advertising revenue to exceed $1 billion.

The Super Bowl’s massive near 120 million average minute viewers provide a once-a-year major marketing boost for a TV-based media company -- during the game itself with on-air promotion, as well as programming content that follows the NFL game.

Last year, CBS’ season premiere episode, “Tracker” pulled in 18.4 million viewers, according to Nielsen. The all-time viewing record is held by NBC’s “Friends," airing a special one-hour episode in 1996 which pulled in 52.9 million viewers.

The second-highest total was in 2001 for CBS’s “Survivor: The Australian Outback,” a season premiere at 45.4 million; and CBS’s "Undercover Boss” season premiere scored 38.7 million in 2010.

In 2011, NBC’s “Super Bowl XLVI” became available for the first time on the NFL website (NFL.com) and NBC’s website (NBCSports.com) through Verizon’s NFL Mobile app.

In February 2022, NBC simulcast the game for the first time with its new streaming platform, Peacock, for “Super Bowl LVI”. In February 2024, CBS Television Network simulcast “Super Bowl LVIII” with its streamer Paramount+, and kids cable network Nickelodeon.

In the past legacy media companies like NBCUniversal, Paramount and Warner Bros. Discovery have regularly used on-air promotion messages to tout all kinds of owned-theatrical movies (and that of competing movie studios content), TV prime-time shows and other media business.

How will future legacy TV networks use the biggest annual TV show of the year to glean even more promotional value -- as well as some $400 million in advertising revenue for all Super Bowl day programming?

It’s left to see where the next level of integrated marketing efforts will go from here -- more connected TV programming, maybe better engagement efforts for its products?

Look for TV networks to run up the score.

Character AI ,a neural language chatbot service that generates human-like text responses, has named David Brinker as senior vice president of partnerships. 

Brinker will be tasked with building the company’s partnerships with media and entertainment companies, tech firms, platforms and creators. 

Previously, Brinker served as vice president of content partnerships, business, and operations at Snap Inc.

Prior to that, Brinker served News Corp. in a variety of roles, including senior vice president and global head of business & corporate development president of the New York Post. He also was the senior vice president of operations and business development for The Daily, a News Corp. mobile publication.

In 2024, AI washed over marketing organizations like a tsunami. 

The opportunities of AI and the ensuing logistical, customer service and existential nightmares are falling squarely on the shoulders of marketers dealing with technology and data. Rather than revolutionizing their jobs, it’s simply upending them, creating stress and uncertainty.

Everywhere AI goes, it delivers good, bad and ugly results. Here’s how it’s been working so far in the three most common use cases:

Personalization and Customer Experience

The Good: AI analysis and generative AI content generation are working together to give people more relevant customer experiences. Brands can personalize emails, offers, website and mobile app experiences with copy and content based on past behavior, preferences and other data.

The Bad: AI hasn’t made it easier for advertisers to know enough about consumers to get personalization right. The process relies on accurate and complete data, still a work in progress for many companies.

The Ugly: Less tested and potentially dangerous AI solutions like chatbots are being unleashed without enough oversight, creating potential for horrific customer interactions.

The Bottom Line: The dream of a truly personalized, relevant customer experience is still elusive. While AI helps create more specific messaging and content, it’s still early days, and it still relies on good data.

Creative Optimization and Content Generation

The Good: Generative AI is being used as a brainstorming companion, to create mood boards and topic ideas. A marketer strapped for time can have generative AI transform a blog post into a series of social media posts, translate a press release into 10 languages, and reformat creatives to fit requirements for every social media platform in seconds. That’s cool.

The Bad: Someone needs to decide what content still needs human oversight, editing and approval, which can be time-consuming and expensive, taking some of the coolness out of having hundreds of pieces of auto-generated anything.

The Ugly: Advertisers relying too heavily on generative AI risk tarnishing their brand with robotic copy, weird images or worse. 

The Bottom Line: Saving time is awesome, but maintaining an authentic connection with customers needs to matter more than time savings or creating different versions of content.

Data Analysis, Targeting and Measurement 

The Good: AI, like deep learning, is helping marketers analyze data much more effectively. New campaign measurement approaches help marketers focus on metrics that really matter, like incremental lift. AI is also helping marketers identify new customer segments and find new places to market.

The Bad: Again, data quality matters, and it’s not always great. Analysts using AI analysis need to be true data scientists for insights to be trusted.

The Ugly: AI targeting and analysis is opaque and hard to trust. Many marketers have to take a leap of faith to alter their strategy based on a result.

The Bottom Line: Marketers should work with teams of data professionals and ensure data being used is representative, clean and timely.

Working Through AI Fatigue

Marketers didn’t really save much time using AI in 2024. Instead, they generated more content, used more ways to target customers, and got more headaches. After the initial AI hype, marketers are solidly in the frustration phase, which will be a big theme in 2025.

Working through this frustration and fatigue will be a big competitive differentiator. Marketers willing to do the heavy lifting of improving processes, shoring up data and continuing to test AI will start to see the transformative gains many were hoping for in 2024.

AppsFlyer has found a retail media partner.

The mobile marketing measurement and analytics company on Wednesday will announce a strategic partnership with Wolt, which focuses on local commerce, merchants and delivery services.

Wolt Ads, Wolt’s retail media solution, will use AppsFlyer's Data Collaboration Platform (DCP) to securely share first-party data with advertisers and partners.

Tami Harrigan, vice president of business development at AppsFlyer, told MediaPost that just because companies "'slap a 'privacy' or 'clean room' label on an offering doesn’t make it so."

Collaboration is not new, but with emerging regulations guided by technology this year, 2025 will be different.

Questions related to conflict of interest, incentives, and motivation will become much louder this year, compared with 2024, and more companies will find a way to become interoperable with others.

2025 will become the year of real collaboration between companies to “unlock the ecosystems” and “break the walls of their own gardens,” Harrigan said. “Clouds will swallow egos to collaborate, and vendors will build on top of one another.”

AppFlyer’s advanced measurement tools connect sales directly to campaigns, providing granular insights into performance. The company will support all of Wolt's 27 markets, with campaigns estimated to be in the thousands.

The collaboration has delivered results for Wolt’s clients.

A global ice cream brand created a segment of seasonal shoppers who purchased frozen desserts during the summer. They used their first-party purchase data and integrated into AppsFlyer’s DCP to identify this audience and launch a loyalty campaign.

This allowed the ice cream brand to create its own view of the data, as well as perform calculations on the data columns to design and adapt the products.

Another example is from a retailer that identified high-value customers who regularly bought premium products. 

By combining CRM data and app engagement insights through the platform, the retailer could target this audience with tailored offers. 

The data for these segments came directly from a brand’s first-party sources, including CRM systems, transaction data, and app behavior analytics, all securely processed within AppsFlyer’s privacy-first architecture and clean room.

The companies shared some stats from early tests. Internal data shows campaigns running on DCP achieved 400% return on ad spend and 32% ROAS uplift compared with those without DCP.  In addition, there was a 148% uplift in category share, driven by precise targeting and strategic insights, and an 86% increase in click-through rates (CTRs).

The most significant result was the 159% uplift in cart penetration rate compared with campaigns without DCP.

Harrigan explained that the audience segments are built through an easy-to-use platform interface that doesn’t require technical expertise.

Brands can define criteria such as purchase history, user behavior, or demographic attributes to form the basis of their audience segments. 

The platform ingests, processes, and analyzes first-party data to build these segments, providing marketers with precise groups that align with their campaign goals. 

Catalina Salazar, global head of Wolt Ads, believes that the partnership drove audience creation for its brand partners, as well as measurement of the media plan end-to-end across our in-app and off-app touchpoints.

The audience segments are built on the least amount of data possible. It helps to promote privacy by reducing the exchange of unnecessary or sensitive information.

There is much speculation about which professions AI will eliminate. Depending on which generative AI tool you ask, you will get a list of 10 to 30 criteria. Many of them are important only on the surface.

I believe that the top three considerations are:

• How easily and how effectively can a particular problem be solved with machine learning (ML) vs a human?

• What is the total addressable market (TAM) for the solution?

• How much training data is available, and how clean is it?  

The first two criteria determine the value-to-effort ratio — the main factor in product development and investing decisions. The training data is a necessary building block.  

When thinking about the first criterion, consider what is more natural for a machine vs. a human to do. As a land mammal, you will not out-swim a Great White shark. But, given the advantage of an opposable thumb, you can surely out-climb it in your natural habitat - the dry land.  

When talking about AI, most folks mention generative AI, large language models (LLMs), and self-driving cars.

Indeed, those technologies are impressive, and they are just getting started. However, while humans take speech and vision for granted, Natural language processing and computer vision are extremely difficult and unnatural problems for AI. 

If you have ever built a simple image classifier from scratch, you will know there is much to it.

Many calculations need to happen just to recognize image borders. Then, additional neural network layers combine borders into basic shapes, more complex shapes, objects, etc. Chat GPT and Tesla full self-driving cars are like sharks that, with investments of hundreds of billions of dollars, have been trained to compete with human rock climbers.  

 What helps justify the massive investments is virtually unlimited TAM.  

It helps that a lot of training data, such as publicly available text and images, exist. 

Programmatic campaign management is on the opposite side of the above criteria. Campaign optimization tasks are incredibly easy for machines to do. These are just calculations, after all - the computers’ natural domain. Estimating how each of the millions of mobile apps and web pages will perform for your new ad campaigns is just as easy for ML as for you to figure out how to lift your foot over a doorstep when you enter your house. 

Planners are entirely out of their element when attempting to compete with machines in campaign optimization.

Could a planner do the same calculations that ML does, for example, using Excel? If they knew the proper math, then yes. But it would take them months to do the same math that ML does in milliseconds. Humans are utterly outgunned in this competition. 

So why do planner jobs still exist?  

Three reasons:

1. Relatively limited TAM. The tasks are company-specific. There is no universal algorithm to solve all of the DSPs’ and agency trading desks’ optimization problems. One-size-fits-all solutions do not work. 

2. Fragmentation of data. Ad Tech companies guard their data–and for the right reason. Whereas LLMs can train on Wikipedia, the BookCorpus, and the billions of web pages they can crawl, each DSP algo trains only on the data generated by the ads shown by the DSP. 

3. Inertia and lack of knowledge. Despite the above difficulties, DSP ML solutions evolve rapidly. For now, media executives who also lack data science knowledge fail to recognize the obvious fact that the value that planners add becomes smaller and even negative. After all, to check someone else’s math, you need to know math. 

The time is not on your side. Open-source ML libraries and computing power are becoming rapidly better and cheaper. Even with a relatively low TAM, having a robust ML solution becomes more and more feasible for most ad tech companies. You will be replaced very soon -- unless you adapt. 

Play to Your Strengths and Become the Master of the Machines

A wise person once said: “AI will not replace you. A human using AI will.” 

During the dawn of the industrial revolution in early 19th century England, the members of the infamous Luddite movement correctly determined that steam-powered machines were becoming much more productive than human laborers in making textiles, metalworking, printing, and other tasks. They went about the upcoming threat much like many of today’s digital media professionals do: they continued with their manual labor. Many Luddites engaged in protests and even tried to destroy the machines.

Yet, some savvy folks recognized that instead of competing with the machines, it was more advantageous to be the one who enables the machines.

In today’s “dark factories,” a handful of humans oversee thousands of robots via a few monitors from a small, comfortable room. They rarely have to step onto the factory floor (hence, no lights are needed). These workers are well-paid and have far more rewarding careers than the manual textile weavers of the 1800s. In my opinion, planners must evolve into this type of role — and they must do so quickly. 

Here are some things you, the experienced planner, can do to succeed as a master of machines. Each of them involves playing to your strengths.

• Set Goals and Constraints. ML cannot do this step. You must understand what is important to your clients. This task is challenging, given the clients often do not know what they want. Based on this insight, you can define the goals and constraints for ML-driven optimization. This might sound simple, but I saw many seasoned media professionals getting confused at this step. Some do not even understand the difference between an optimization goal and a constraint. Lead by creating clarity on this.

• Define new model features. In ML, powerful model features are far more impactful than fancy complex algorithms. Defining model features requires domain expertise, something that you have. Many folks on the data science team come from different industries, or they are too busy learning their craft to develop the in-depth understanding of ad tech that you have. Anything can be a potentially great feature. Your company may be sitting on a goldmine of valuable 1st party data. You are in the best position to uncover the treasure.

• Identify flaws in the training data. ML is very good at finding patterns in data, but what if the data that you feed it is flawed in the first place? Worst yet, if training data differs from production data, the algorithms will fail. I have many examples where, by applying their subject matter expertise, planners found bugs in training data and helped us improve the algorithms dramatically. 

• Look for anything that makes no sense. “Common sense” does not exist in the ML world. It is a human notion. On multiple occasions, my planner colleagues were able to point to oddities in our ML systems’ performance. This feedback was invaluable in identifying flaws, finding edge cases, and enhancing the algorithms.

• Anticipate trends and unusual events. I bet your ML system doesn’t have many Black Fridays, Super Bowls, presidential elections, or other high impact events in its training data — as most algos rely on only 14-90 days of past performance data. However, you have lived through quite a few of these events so you can anticipate and prepare.

• Don't forget about the creative. DSP algos match the right users with the right creative at the right time and place. However, it can only operate within the choice of creative that you gave it. Work with the creative teams to develop as many concepts as possible — the greater the variety, the better. ML will then sort out the matching, but it can’t develop decent creative concepts (yet).

Learn their language: acquire the basic statistics literacy

If the above list looks more like a hybrid planner/engineer role to you, you are correct. You need to evolve into a bit of a hybrid.

A 17th-century farmer knew about seasons and crops. A 20th-century farmer also had to become a driver, mechanic, and even a bit of a chemist. A mid-21st-century farmer will be a robotics specialist first and foremost.  

As a planner, you must know a bit about statistics and the basics of ML. This will allow you to interact with the data scientists and avoid basic pitfalls, such as not calculating statistical significance or not applying Holm-Bonferroni correction when determining the alpha levels when multiple treatments compete.

If the preceding sentence sounds foreign to you, you have much to learn. There are many great free resources. Take advantage of them. 

Consumers not only like text messages, they want more of them, judging by the 2025 Mobile Consumer Insights Report from Vibes, the eighth in an annual series.  

For instance, 13% now want to receive text messages once a day, versus 6% last year. And 15% say they would welcome them every other day, compared with 7% in 2024.  

Twenty-one percent say they want to receive text messages a few times a week -- an increase from 17% last year. Perhaps more importantly, 31% want to get them only once a week, down from 42% in 2024.  

Why do they want from text messages? They seek:

• Incentives and loyalty programs — 64% 
• Exclusive content — 39% 
• Account/transaction-related updates — 38%
• Brand news — 32% 

Moreover, 44% sign up for text messages from firms they want to buy from. And 28% are more likely to purchase from companies that send them text messages. 

Despite that, consumers are protective of their privacy. They are willing to share these personal details with brands: 

• Email — 65%
• Birthday — 45% 
• Name — 44% 
• Shopping preferences — 40%
• Zip code — 35%
• Address — 13%
• Income — 9% 

How do they want this information used? They cite: 

• Offers based on birthday and purchase history — 56% 
• Reminders about unused relevant offers — 49%
• Offers based on location — 40% 
• Reminders of upcoming events — 40%

Meanwhile, consumers are warming up to digital wallets, and 55% say they could replace their physical wallets with them.  

Among shoppers, 60% now use their digital wallets for storing items other than their credit card -- up from 55% last year. 

But be careful: 25% of consumers “view messages that arrive too early or too late as irritating or spammy,” the study notes. 

Industry Dive surveyed 1,005 consumers for Vibes during a two-week period in October/November 2024. 

On the heels of the demise of Venu Sports, DirecTV is launching a skinny sports-focused TV network package called MySports, with an initial price tag of $49.99 a month.

The streaming package of 40 sports and broadcast TV channels will be initially be offered in 24 markets -- including major markets in New York, Los Angeles, Chicago, Philadelphia and San Francisco-Oakland.

Consumers do not need a satellite subscription for the package. The bundle of networks can stream MySports through the DirecTV app on mobile devices or via Roku, Amazon Fire, and Apple TV.

Sports TV channels will include ACC Network, Big Ten Network, DIRECTV 4K Live, DIRECTV 4K Live 2, ESPN, ESPN2, ESPNews, ESPNU, Fox Sports 1, Fox Sports 2, Golf Channel, MLB Network, NBA TV, NFL Network, NHL Network, SEC Network, TBS, TNT, TruTV and USA Network.

Broadcast networks will be available via initial local TV stations owned and operated by ABC, Fox and NBC in those 24 markets.

DirecTV is also reportedly negotiating to add CBS-owned TV stations as well.

After the initial three-month period, the regular price will move to $69.99 a month.

The new sports package will feature networks owned by Walt Disney, Fox Corp., and Warner Bros. Discovery -- the partners in a joint venture that intended to launch Venu Sports.

Venu Sports was intended to launch last fall with around 40 networks.

DirecTV, Dish Network, and other pay TV providers opposed that launch in filings with a U.S District Court in connection with a lawsuit filed by Fubo TV. That lawsuit claim Venu Sports was anticompetitive and violated antitrust rules.

The lawsuit was pulled by Fubo after Disney announced it was buying a 70% stake in Fubo, a sports focus virtual pay TV distributor for $220 million. Disney intends to merge its Hulu+Live TV with Fubo.

There are many things in life that don’t come with a guarantee -- whether in sports or in everyday life.

AT&T uses that premise -- and the inherent unpredictability of the college football playoffs --  to introduce the “AT&T Guarantee,” the wireless brand’s new network reliability and customer care pledge, with a little help from former NFL greats Tim Tebow, DeMarcus Ware and Marshawn Lynch.

AT&T’s guarantees to new and existing customers include speaking with a tech expert or scheduling a callback time within five minutes of calling for help; same or next day availability for an appointment with a technician; and prompt repair for network interruptions, along with crediting customers for a full day of service.

The brand worked with agency partner OMC on a series of ads focusing on areas of life without guarantees. From the accuracy of quarterbacks  or rental car companies, to the butter container in the fridge actually containing butter, or even certainty of your ownexistence, the launch campaign applies the comedic premise across a variety of scenarios.

 “Whether it be in sports, in business or even our commute to work, we're used to nothing in our lives being guaranteed,” OMC Chief Creative Oficer Matt Miller said in a statement. “This work takes a witty, relatable look at all those countless uncertainties, then shows how at AT&T it's different. AT&T is guaranteed to have your back.”

The multiplatform “AT&T Guarantee” campaign debuted during the Orange Bowl on Jan. 9, and is running across a series of college football playoffs games. media targeting both Hispanic language, and general market audiences on TV, print, online video, social media, and online display.

According to a spokesperson, the “AT&T Guarantee” campaign will remain a focus for the brand throughout the year, with future ads campaign continuing the approach of depicting relatable guarantee-free scenarios.

The launch of “AT&T Guarantee” follows some crises for the brand in 2024 – including a nationwide outage last February which impacted some 92 million voice calls, according to the FCC; as well as a data breach the company disclosed last July, which it said it learned of in April.  It also comes on the heels of the brand’s simple holiday advertising message, “A Voice Can Change Everything.”

Today, AT&T also announced it is working closely with agencies such as CalFire to provide cell coverage to areas in the Los Angeles area impacted by wildfires –while  prioritizing the needs of the public safety community. According to a release from AT&T, CalFire’s mobile FirstNet cell sites in the area are providing first responders with “greater command and control of their own network” through Compact Rapid Deployables (CRDs) which can be set up in minutes.