From founding a specialist marketing evaluation and modeling agency to co-founding the Measure.Monks—our data-driven team that builds marketing effectiveness models to help brands deliver more profit—my professional journey can be divided into four milestones: starting, scaling, merging and integrating a business. In this piece, I aim to share my experience (instead of unsolicited advice) with the hope that established and aspiring founders can draw inspiration from it.   

Starting a business 

Looking back, this might have actually been the hardest part of it all. Let’s just say it takes a pretty large leap of faith to go from the comfort of having a salary and holidays to being completely responsible and accountable for your income. People’s common perspective is that you can work when and how you like, but my reality looked quite different. No, I didn’t have a direct boss—but I did have to constantly be on hand for clients to get the business off the ground. In my mind, any day off was a day lost in growth. 

Those early days were testing times, but resilience and hard work got me through them. While resilience is required in taking the bad breaks at the start (which I believe happens to test your mettle), hard work is needed to create more leads to increase your chances of bringing in bigger projects. In hindsight, having a co-founder would’ve helped enormously, but I’ve always been lucky that my wife knows the industry and is incredibly supportive. 

Scaling a business

With more work came more income, and as the team grew, the pressure eased. Upon reflection, I realize how reliant you can be on one client in the early days, which is a very precarious position to be in. If they drop you, your business drops—and this means making tough calls about the team. Fortunately, I could always lean on my advisor and chairman Paul Edwards, who was an invaluable coach, highlighted things I’d overlooked, and helped me manage and expand the team. I’ve found that having an external advisor is not only what kept me sane, but what kept our company’s standards high. In turn, these standards drove our mission, vision and values, which proved key to attracting and retaining talent. 

Merging a business

After years of great growth, we reached the point where we had nurtured an incredible team and built amazing market-leading products. But to truly accelerate our growth, we had to go global—and needed a partner to do so. Avoiding private equity as cash wasn’t the issue, our focus was on access to clients and facilitating global growth. After a lengthy scouting process, we were introduced to Media.Monks. We were immediately blown away by their agility, sheer focus on groundbreaking innovation, and culture of entrepreneurship. Making the merger decision may have been nerve-racking, but we knew we had the support of our people, whom we kept informed along every step of the process.

And what a great decision it was! Our merger was handled superbly by SI Partners, who managed our pitch process and the offers that led to the Letter of Intent, all the way through due diligence, legal and finally signing all the agreements. Having heard horror stories about this process taking up all of the leadership’s time—with a suffering business as the result—I was not looking forward to it, but our M&A partners made it easy to navigate. 

Integrating a business

Wasting no time, Media.Monks quickly initiated integration. Turns out, they are pros at this. As a dedicated Post Merger Integration (PMI) team made everything run smoothly, we immediately felt part of the team. They provided a detailed plan of everything we needed to fall in on, like accounting practices, legal, HR, CRM software, audits and more. However, allowing us to move at our own pace was the real value of the PMI team, which made us feel comfortable in the nearly 12 months it took to fully merge.

On the business side of things, we jumped straight into the global network, sharing our story with any team that would listen, which was met with sincere interest and support. These last few years have led to significant global growth, as we’ve not only gained clients in new markets, but also expanded our Measure.Monks team. At the moment, we have talent located in New York, Toronto, the UK, Buenos Aires, Melbourne and Singapore, and this list will only keep growing. 

While our team folds into the data pillar, we seamlessly work across our media, content and technology pillars. As a result, we regularly venture into new territory, from supporting our agility-focused media teams to running creative measurement and optimization with our content teams to developing new products with our data teams. There’s so much more to be explored, created and delivered—especially given the recent uptake in usage of AI and automation—and that’s why my excitement about this journey never wavers.

Performance marketers have been an underutilized resource to date, but their years of experience using AI for marketing success make them well suited to play a large role in broader AI adoption. Blind disciples of every generative AI shortcut will get burned and those resistant to change will become irrelevant. Nobody knows this more than performance marketers. 

As it relates to the digital marketing AI arms race, Google, and to a lesser extent Meta, weren’t nearly as proactive at highlighting their work relative to Microsoft (the largest investor in OpenAI, the company responsible for GPT-4). The irony is that Google and Meta had been at the forefront of incorporating their long-standing investments in AI, which was already deployed in almost every corner of Google and Meta Ads platforms and products.

Google and Meta represent nearly half of all digital ad spending in the US and represent an even larger share of the typical performance media budget. AI integration in Google and Meta has most prominently centered around machine learning algorithms for bidding and ad serving. That said, there are examples of generative AI as well (suggesting ad copy and creating distinct ad copy from permutations of existing headlines and body copy), and AI’s tentacles can be felt everywhere in the Google and Meta ad ecosystem. Prominent examples include:

• Performance Max (Google) and Advantage+ (Meta) are effectively end-to-end automated campaigns that use AI to target, generate ads and optimize toward set goals.
• Automated bidding sets dynamic bids in real time using machine learning to more efficiently optimize toward the highest ROI.
• Responsive Search Ads (Google) uses AI to mix and match different portions of copy to deliver the best permutation for the individual searcher (right ad to the right audience at the right time).
• Recent Google Marketing Live (GML) and Meta Connect 2023 conferences announced products around AI-powered assets, AI-generated images, generative AI to create ad copy and auto enhancements to text placement, brightness, etc.

In that same vein, performance marketers, most of whom earned their stripes running or overseeing Google and/or Meta Ads, are particularly well suited to guide advertisers through this next major stage in digital transformation. The nearly half decade of experience most performance marketers have both harnessing and reining in AI tools justify them playing a central role guiding marketing teams in developing and deploying generative AI adoption.

What about this experience gives performance marketers an advantage? 

• Threading the needle between uncritical adoption and complete resistance to change
• Understanding of the importance of high-quality data inputs 
• Understanding the importance of setting guardrails and tweaking those over time 

Bringing healthy skepticism to the table.

Seasoned performance marketers have had to adapt and learn new types of automation many times over, and can share their war stories. From broad match keywords, Meta auto-placements and iteration after iteration of automated bidding on Google gone awry, we’ve seemingly seen it all. Google and Meta were trailblazers in incorporating AI into ad products, and reps would very earnestly push adoption of products that could be buggy and at worst underperform manual alternatives. However, Google and Meta were also diligent about refining those products over time and performance marketers who were not willing to continue testing at all over the last few years were quickly left behind. Broad match keywords, automated bidding, Advantage+ shopping campaigns and many more products delivered more scale at comparable efficiency to non-AI driven products. 

As AI plays a more permanent role across creative, customer journey, audience identification and more, this balance will be crucial. Blind disciples of every generative AI shortcut will get burned and those resistant to change will become irrelevant. 

Garbage in = garbage out.

One of the biggest distinctions in a strong performance marketer versus a mediocre one is her understanding that the inputs to automation can have a profound effect on outcomes. Performance marketers who press the easy button and switch from hundreds of manual bids per week to auto-pilot don’t get strong results. Worse yet, they’re quick to declare, “It doesn’t work!” Data volume and quality are the foundation of an effective AI deployment strategy. Knowing which data sources to use and exclude, and which campaigns to match with each specific type of automated bidding, is a crucial skill. Performance marketers know to incorporate lead quality data to B2B auto-bidding, initiate testing on campaigns with higher conversion volumes, and not to launch immediately after a strong holiday or back to school period.

In this sense, performance marketers have years of “prompt engineering” reps without even realizing there was a name for it. Marketing organizations stand to get AI into market faster, and benefit sooner from the positive results, by tapping into that experience. 

Performance marketers are masters at fine tuning.

The last level of mastery that performance marketers have achieved has to do with learning the intricacies of the algos. We have applied max CPCs, cost caps and negative keywords to rein in the occasionally deleterious effects of AI unchecked. At a high level, AI can be fickle and human intelligence is crucial to avoid these blips. We have seen a top performing ad set stop delivering seemingly out of nowhere, only to have a minor 5% increase in ROAS target return it to normalcy. We’ve learned to mine for insights around how, why and where AI is working:

• Is stronger performance because we’re seeing increased CTR or conversion rate?
• Are we getting in front of the same audience more cost effectively or reaching a better audience?
• Did we create better ads, or did the platforms get better at matching them to the right people?

We ask these questions daily. That curiosity bordering on paranoia allows performance marketers to squeeze the most out of AI, as well as limit downside risk. 

Performance marketers have a feel for AI’s rhythms, like a mechanic knowing just which bolt to tighten to get the rattling sound in the car to stop. This mileage, or put anachronistically “human intelligence,” is tough to replicate. 

This AI mileage and its broad applications are why performance marketers should have a seat at the table. As an agency leader I’m better equipped to weigh in on how we utilize AI to address tasks, reporting, data integration, scripts and implement processes around AI because of that performance DNA.

There's a lot of talk about AI's potential—its future possibilities and predictions. But let me assure you, the moment for AI is not just coming; it's here, it's now, and it's making waves across all industries. And what’s specifically interesting to me is that it’s changing the world of marketing and digital platforms.

But what about the barriers to entry? It's important to remember that incorporating AI into your operations doesn't mean a full-scale overhaul is necessary. At Media.Monks, we understand that each brand is unique and some may require a more iterative approach. This perspective allows for cost-effectiveness and accessibility while still benefiting from the AI wave. A phased introduction of AI-driven improvements can bring immediate benefits to your customers and your business performance. You might begin with an AI chatbot to enhance customer service, or leverage machine learning to personalize content for each website visitor. Initial steps like this can provide quick wins, delivering enhanced user engagement and improved conversion rates. As these enhancements demonstrate their value, you can gradually expand AI's role within your digital landscape. It's about creating a tailored, strategic path towards AI integration, instead of diving headfirst into the deep end.

So, let’s take a journey into the current and very real applications of AI within the digital platforms landscape, areas where AI is not just delivering promises, but measurable results for marketers.

Here’s where to get started with AI.

Integration of AI with traditional platforms. The integration of AI with conventional platforms is helping businesses refine operations and customer experiences. The merging of CRM systems with AI, for example, allows a brand to learn from its customers’ behaviors in real-time, thus offering better service and products tailored to individual preferences.

Optimizing user experience. AI-driven data analysis is providing actionable insights that directly enhance user experiences. Whether it’s through customized content, personalized interfaces, or the elimination of user flow pain points, AI is driving a new era of user-centric platforms.

Facilitating personalized marketing. Gone are the days of generic, one-size-fits-all marketing. AI is enabling a new level of personalization that makes every interaction feel like it's uniquely crafted for the individual user. From product recommendations to personalized messaging, AI is helping brands forge deeper connections with their customers.

Enhancing analytics. AI-powered predictive analytics are transforming how businesses understand their customers and markets. These tools provide an unprecedented level of insight into future customer behavior, market trends, and potential business risks.

Cross-department collaboration. AI isn’t just for tech teams. It’s providing opportunities for seamless collaboration between departments, helping to create unified, efficient approaches to everything from product development to customer service.

AI solves many of the challenges brands are dealing with right now.

Next, let’s look at some great real-world examples where we have worked on bringing transformational improvements to key KPIs by both iterative and larger form implementation of AI enhancement. Here are some of the challenges we are helping with day to day:

“Help, I’m drowning in a sea of content!” When the volume and complexity of the information is overwhelming for visitors, sometimes standard search just won't cut it. A potential application of AI here is to create an intelligent search functionality that leverages natural language processing and machine learning. It understands user queries better, allows for conversational dialogue and provides more relevant results, continuously improving based on user interaction patterns.

“How do we extend meaningful connections with customers whilst building a community of users?” An AI-enhanced platform could provide personalized content based on customer interests and product usage patterns. By understanding each customer’s interaction with the product, AI can tailor content, extending the brand experience and fostering an engaging online community around shared product experiences.

“How do we cope with the daunting task of managing job applications from a vast pool of diverse applicants and numerous roles?” Here, AI can be employed to develop self-segmentation tools and create individual user journeys based on each user's unique profile and preferences. AI can analyze data at scale, drawing insights that allow a recruitment agency to tailor each experience and guide potential applicants towards roles that suit their skills and aspirations.

“How do we effectively showcase an extensive network of services and provide evidence of campaign effectiveness to potential customers?” By implementing AI-driven analytics, this company could deliver detailed campaign performance reports to customers, even predicting potential future outcomes based on historical data. This approach provides a tangible measure of ROI for clients.

Each of these scenarios illustrates the transformative potential of AI within the digital platform landscape. Broadly speaking, AI complements and enhances our existing strategies, enabling us to craft more engaging, personalized, and efficient experiences for users. AI isn't just a box to be checked; it's a versatile tool that we are using daily to create meaningful and impactful digital experiences.

Prepare yourself for sustained success with AI.

With AI’s potential being realized in real time, the thrill is in watching these developments unfold and harnessing them in transformative ways. Remember, the future is not some distant point on the horizon; it’s happening right now. By embracing AI in a thoughtful and strategic manner, we can achieve immediate wins and lay the groundwork for sustained, long-term success.

At Media.Monks, we’re always on the lookout for ways to integrate the best AI technology into our business. We do this not just because we know AI is (and will continue to be) highly disruptive, but also because we know our tech-savvy and ceaselessly curious people are bound to experiment with exciting new tools—and we want to make sure this happens in the most secure way possible. We all remember pivotal blunders of these past months, like private code being leaked out into the public domain, and thus it comes as no surprise that our Legal and InfoSec teams have been pushing the brakes a bit on what tech we can adopt, taking the safety of our brand and those of our partners into consideration. 

So, when OpenAI—the force behind ChatGPT—updated their terms of service, allowing people who leverage the API to utilize the service without any of their data being used to train the model as a default setting, we were presented with a huge opportunity. Naturally, we seized it with both hands and decided to build our own internal version of the popular tool by leveraging OpenAI’s API: MonkGPT, which allows our teams to harness the power of this platform while layering in our own security and privacy checks. Why? So that our talent can use a tool that’s both business-specific and much safer, with the aim to mitigate risks like data leaks.

You can’t risk putting brand protection in danger.  

Ever since generative AI sprung onto the scene, we’ve been experimenting with these tools while exploring how endless their possibilities are. As it turns out, AI tools are incredible, but they don’t necessarily come without limitations. Besides not being tailored to specific business needs, public AI platforms may use proprietary algorithms or models, which could raise concerns about intellectual property rights and ownership. In line with this, these public tools typically collect data, the use of which may not be transparent and may fail to meet an organization’s privacy policies and security measures. 

Brand risk is what we’re most worried about, as our top priority is to protect both our intellectual property and our employee and customer data. Interestingly, a key solution is to build the tools yourself. Besides, there’s no better way to truly understand the capabilities of a technology than by rolling up your sleeves and getting your hands dirty.

Breaking deployment records, despite hurdles.  

In creating MonkGPT, there was no need to reinvent the wheel. Sure, we can—and do—train our own LLMs, but with the rapid success of ChatGPT, we decided to leverage OpenAI’s API and popular open source libraries vetted by our engineers to bring this generative AI functionality into our business quickly and safely.

In fact, the main hurdle we had to overcome was internal. Our Legal and InfoSec teams are critical of AI tooling terms of service (ToS), especially when it comes to how data is managed, owned and stored. So, we needed to get alignment with them on data risk and updates to OpenAI’s ToS—which had been modified for API users specifically so that it disabled data passed through OpenAI’s service to be used to train their models by default.

Though OpenAI stores the data that's passed through the API for a period of 30 days for audit purposes (after which it’s immediately deleted), their ToS states that it does not use this data to train its models. Coupling this with our internal best practices documentation, which all our people have access to and are urged to review before using MonkGPT, we make sure that we minimize any potential for sensitive data to persist in OpenAI’s model.

As I’ve seen time and time again, ain’t no hurdle high enough to keep us from turning our ideas into reality—and useful tools for our talent. Within just 35 days we were able to deploy MonkGPT, scale it out across the company, and launch it at our global All Hands meeting. Talking about faster, better and cheaper, this project is our motto manifested. Of course, we didn’t stop there. 

Baking in benefits for our workforce.   

Right now, we have our own interface and application stack, which means we can start to build our own tooling and functionality leveraging all sorts of generative AI tech. The intention behind this is to enhance the user experience, while catering to the needs of our use cases. For example, we’re currently adding features like Data Loss Prevention to further increase security and privacy. This involves implementing ways to effectively remove any potential for sensitive information to be sent into OpenAI’s ecosystem, so as to increase our control over the data, which we wouldn’t have been able to do had we gone straight through ChatGPT’s service. 

Another exciting feature we’re developing revolves around prompt discovery and prompt sharing. One of the main challenges in leveraging a prompt-based LLM’s software is figuring out what the best ways are to ask something. That’s why we’re working on a feature—which ChatGPT doesn’t have yet—that allows users to explore the most useful prompts across business units. Say you’re a copywriter, the tool could show you the most effective prompts that other copywriters use or like. By integrating this discoverability into the use of the tool, our people won’t have to spin their wheels as much to get to the same destination.

In the same vein, we’re also training LLMs towards specific purposes. For instance, we can train a model for our legal counsels that uncovers all the red flags in a contract based on both the language for legal entities and what they have seen in similar contacts. Imagine the time and effort you can save by heading over to MonkGPT and, depending on your business unit, selecting the model that you want to interact with—because that model has been specifically trained for your use cases.

It’s only a matter of time before we’re all powered by AI. 

All these efforts feed into our overall AI offering. In developing new features, we’re not just advancing our understanding of LLMs and generative AI, but also expanding our experience in taking these tools to the next level. It’s all about asking ourselves, “What challenges do our business units face and how can AI help?” with the goal to provide our talent with the right superpowers. 

It goes without saying that my team and I apply this same kind of thinking to the work we do for all our clients. Our AI mission moves well beyond our own organization as we want to make sure the brands we partner with reap the benefits of our trial and error, too. This is because we know with absolute certainty that sooner or later every brand is going to have their very own models that know their business from the inside out, just like MonkGPT. If you’re not already embracing this inevitability now, then I’m sure you will soon. Whether getting there takes just a bit of consultation or full end-to-end support, my team and I have the tools and experience to customize the perfect cape for you.

We’ve all seen and heard how generative AI can supercharge creative content production by creating large volumes of images, video and copy in just seconds. This is only one sliver of AI’s potential, because conversational interfaces that learn from us will profoundly transform the way we search for and discover products and information. And we’re already seeing it happen before our eyes: Instacart offers contextual advice for grocery shopping, Zalando created a virtual fashion consultant, and Intercom launched a GPT4-powered business messaging solution that can solve 50% of customer questions instantly. AI is changing the way people interact with your brand, and this is igniting a paradigm shift in brand interfaces and product design.

For many brands, this creates a challenge. How do we connect people with the right answer, content or product they are looking for? The examples above hint at an answer: AI and LLMs go a long way in making consumer experiences more intuitive. Here’s how we’re thinking about it in our Platforms practice.

New search behaviors will elevate the role of the dotcom.

One area that will drastically influence consumer behavior is search. Search is already the default starting point for consumers, but Google’s new AI-powered results page will soon be the only place a user needs to visit, bringing comparison and conversion onto one screen.

This brings some urgency to how brands approach their own platforms, because to bring their products to the top of search, they’ll need to think less about keywords and more about context and intent. What context would users search for around your products? What would they intend to do with it? What values do your offerings deliver to people?

No one yet can say how to solve SEO in the future. But we can help brands begin to integrate this layer of information into their catalogs and user experiences now to prepare for that kind of change—because in this new world, I see an elevated role for the brand dotcom. Think of Google as the department store that carries all brands, and your platform as the expressive branded spaces users will choose to go to connect and build a relationship. Delivering on this expectation will be the key factor to success in the age of AI.

AI is elevating the brand experience.

I’ll extend the department store analogy a little bit further to illustrate the role of AI on modern digital platforms. A good store employee only asks if they can help at the right moment, and AI will likewise be to gently and organically nudge users through conversation. The difference is that AI will be fully trained on your brand, products and services and can represent those perfectly. Think personal product advice, answers, cross- and up-sales, all in the context of a user’s intent.

A restaurant chain, for example, might use natural language to transform its ordering platform, especially for catering and large orders. Rather than scroll through a menu, users could describe an occasion, like “I’m throwing a birthday party for my 5-year-old son. We’ll have 15 people, mostly children.” The system can then take that information and recommend a customized party package. Any allergies among or dietary restrictions in the group? Not a problem—the AI can edit the order for the customer to review. Think of AI as a butler for your brand and its customers.

More personalized experiences give more opportunities for relationship building.

These little details—why you’re ordering, when you need it by, plus any additional personal requests—go a long way in getting to know your customers. The results are both better customer experiences and the ability to forge hyper-personal relationships, ultimately fulfilling the original promise of digital.

We are finally moving beyond segments and personas. A properly programmed AI understands every user’s personal sentiments, curiosities and needs, because it’s able to pull from and connect different pieces of data from across the consumer ecosystem. It can remember those facts and become more personal with every interaction, like offering personalized promotions and loyalty incentives honed to every user’s context. This new type of personalization shows great promise for conversion.

It's also great for building customer loyalty, because AI unlocks interactions that are designed specifically for building longer lasting relationships with them. As customers engage over time, their interactions across the platform produce greater and more detailed insights that can be used to further optimize the experience and deliver upon their unique needs.

Start with a sprint, then optimize and personalize.

AI will continue to shape consumer expectations and behaviors, underscoring the need for platforms that can pivot with speed and agility. It’s more important now than ever to be able to listen, learn and adapt to how your customers are engaging.

On the flip side, that means your implementation of AI is also always a work in progress. If any of the above sounds interesting to you, rest assured that you don’t have to make a full overhaul of your website. It starts with looking at what you already have and seeing if your tech stack can support these hyper-personalized experiences. Innovation sprints or experimenting with building better experiences—on the main dotcom or maybe in a separate domain—are great places to start, as are smarter search functions that are fairly easy to implement. Then optimize continuously to perfect your toolkit and extend your ability to personalize.

It's too early to say with utmost specificity how AI will shape customer experiences years down the line. But by realizing how recent AI developments are serving pre-existing marketing goals—more personalized user flows, greater customer loyalty, and an elevated brand experience—it’s clear that now is the time to lay the foundations for AI-powered customer journeys.

Want to learn more about how our platforms team can support you in building more personalized experiences?

If you missed it (or could use a refresher), no worries—we’ve collected insights from across the week that set the agenda for what brands and their partners are focusing now and into the next year. Want to see the key themes at a glance? Find our deck at the bottom of the page.

Surprise: everyone was talking about AI.

It’s no surprise that among all the themes covered at Cannes this year, generative AI was the toast of the town. Our programming at Les.Monks Café centered on how marketers are using the tech now—or how they can lay the foundation for the revolutionary effects of AI in the very near future. “AI: Powering Transformative Customer Experiences” was one panel touching on these topics.

At the top of the conversation, Jay Pattisall, VP & Principal Analyst at Forrester, shared insights from his recent forecast report co-authored by Michael O’Grady. “In Q1, 19% of marketers in the US have used generative AI in their marketing execution. By Q2, that grew to 56%. There’s a really substantial growth,” he said, noting that early use cases include content development as well as media strategy and buying.

But what does this look like? Carlos Ricardo, Sr. VP Marketing Services & Creative Production at HP, laid out the brand’s strategic balance in identifying opportunities now versus building toward future goals. “We established what would be the potential business impact in terms of prioritization,” he said. “So, we determined 14 different work streams that we are currently working on which we call ‘Day Zero’—experiments that have already started.” In addition, the team has mapped out plans for 30, 60 and 90 days into the future to keep its AI transformation on-track.

Solange Bernard, Sr. Director/Head of Marketing Communications at Tim Hortons, also offered a peek behind the counter at how they’re using AI: “The way we’ve been approaching it is twofold. One, you see it as an opportunity to be more efficient. And then there’s also creative content development—there’s a lot of excitement in what we could be doing.” Bernard noted AI tools have enabled the team to take their first steps into virtual production to scale up creative.

AI plays a key role as an integrator that unlocks growth for brands.

As Pattisall shared, AI is more than unlocking creative content at scale—there’s also great potential in media. Later in the panel, Media.Monks Co-Founder Wesley ter Haar explained that when you bring both disciplines together through dynamic creative optimization, you truly unlock AI’s revolutionary impact. “For me, it brings to the front the original intent and promise of digital advertising: this idea that we can be real-time responsive, have highly personalized goals, and highly targeted feedback loops.”

This sentiment was echoed at our “TuesdAI Breakfast Session” with our EMEA CEO Victor Knaap and EMEA Chief Growth Officer Maria Nordstrom. With the discussion focused primarily on the basics of generative AI, Knaap explained the importance of integration across the business to “make an enterprise-ready pipeline where we can go all the way from insights to the assets that run on media,” and that he expects to see brands implement structural changes from the top down to accommodate.

One example: the work we’ve done with BMW and Mini, in which “atomic assets”—bits and pieces of creative, like the car model or environment featured—come together based on user profiles and data. “So, you get an infinite amount of assets that can be served into media,” says Knaap, noting that this infinitude can even resonate with audiences you haven’t formally targeted—leading to newer insights along the way.

The secret to cultural relevance? Leaning into communities that align.

AI wasn’t the only topic for discussion at Cannes this year. There was also a lot of talk on building cultural relevance and authenticity, especially when it comes to serving a movement or community. This is already top of mind for many brands during Pride Month—but the 50th anniversary of hip-hop during August this year offers a case study of this concept in real time as brands lean into the culture.

This was a key topic in our panel “Hip Hop 50. Then. Now. Forever,” hosted in collaboration with Billboard, ADCOLOR and Sony Music Group. “Any time a brand wants to utilize or activate a culture, it’s got to be really thoughtful, and it’s got to have intention,” said Eric Johnson, Executive Creative Director, North America at MassiveMusic. “It’s really important for brands to honor the culture and understand the culture.”

With the group diving into legendary brand collaborations in the early days of hip-hop—like Run DMC’s historic signing with Adidas in the 80s after endorsing the shoes in their songs—Cashmere President and Chief Creative Officer Ryan Ford expressed the importance of seeking these natural alignments. “We’re trying to help brands understand where the authentic alignment is already. It’s not just about slapping a ‘Hip-Hop 50th Anniversary’ logo on your product, right?” Instead, he says, you need to think hard about how to show up for the cultural moment.

Mike Van, President at Billboard, offered one approach. “[Hip-hop culture] is inherently entrepreneurial, it’s bootstrap culture all the way. It’s all about financial independence and empowerment, and you have a whole generation now of consumers and fans of hip-hop who are thirsting for that kind of content.” The opportunity: brands can become arbiters to build knowledge within the culture.

Real purposeful marketing focuses on real solutions. 

One area where cultural relevance is key is purpose-driven marketing, which shows no sign of slowing down on the award circuit. That said, the nature of what passes for truly transformative, purposeful work has evolved from previous years. “We’ve moved beyond just raising awareness for good causes. We need tangible solutions,” Sara Cosgrove, our Global Director of Awards & Creativity, on our “Women Connect” panel.

Cosgrove was joined by Jo Wallace, Global Executive Creative Director, and Ashley Knight, Strategy Director, in the panel, which was moderated by Luciana Haguiara, Executive Creative Director, Latam. With Wallace and Knight having served on juries this year, the group pushed back against work that tacks on a cause. “It has to have absolute relevance,” Wallace said. “We’re noticing a real disparity between brands that have a genuine purpose and a reason to function in that space and to bring good, and brands where there’s some laziness—you’re trying to bolt on this purpose and it shows.”

A favorite piece of work among the team is our Havaianas Pride Research project, where we teamed up with Havaianas, Datafolja and All Out to create Brazil’s biggest LGBTQ+ survey. Questions related to community had been excluded from Brazil’s official census, so the survey was designed to make the community and its needs more visible. Its findings were released on a beautifully designed web platform developed by the Media.Monks team. 

There’s no single definition of “good” creative.

Speaking of impactful work, the leadup to Cannes this year didn’t have the single frontrunner that was expected to sweep all the awards—but that’s not a bad thing, because it’s indicative of more diversification of what “good” creative is. An increasingly diverse talent base, plus more diverse and representative juries at the festival, will continue to affect what work is awarded and further challenge industry norms and expectations.

“It all comes down to empathy. There’s never been as many diverse crises we’ve been facing as a group of people, as an industry, and I think the expectation is creativity needs to do more to create empathy among these groups,” Knight shared. “Having more diverse perspectives that can speak to other people’s circumstances and needs can only be a good thing and that’s where I see a lot of change in the work this year.”

So, what makes outstanding work? The Women Connect panel made a rubric: have a clever insight that links to the brand, don’t overcomplicate things, play to emotion, and give newcomers the chance to challenge their more established peers. This helps bring new perspectives to the fore that can uniquely relate to audiences.

Supporting green talent is the idea behind our NextUp.Monks competition, in collaboration with Cannes Lions, which aims to elevate up-and-coming creative talent. This year, teams competed by answering a creative brief from Meta, "VR for Good," which challenged participants to transform how Gen Z thinks about VR and show how a headset can change minds and transform lives. We finished the week with a toast to the six competition winners—Vasyl Ilba, Mykyta Zolotoverkhyi, Ashwin Paul, Jorene Chew, Anna Zhang and Yazad Dastur, Jr.—who touched on their processes and experiences bringing the brief to reality.

One interesting tidbit came from Dastur, on zeroing in on an idea that has an impact. “While we wanted to do something different, we didn’t want to do something big. We aligned really quickly that we wanted to focus on a very small problem that would be able to help everyday life.”

Looking ahead, brands are planning their transformation strategies.

Throughout Cannes, we got a glimpse into what brands are thinking about right now. But what should they be doing now to prepare for next year—and beyond? S4 Capital Executive Chairman sat down with Salesforce President Sarah Franklin and Diageo Chief Digital Officer Susan Jones to speak on “Gathering the Transformation Trio” and aligning C-suite leadership across agency, technology and brand for continued success.

Franklin kicked things off by touching on the evolving role of the CMO. “You’re seeing more CMOs as more strategic in the business, the pathway to these more strategic roles, even the pathway to the CEO which, I think, speaks volumes for how much is on the shoulders of the marketeers and how strategic they are,” she said. Sir Martin Sorrell’s advice to building more strategic brands: be agile, take back control, and invest in first-party data.

On agility, Jones spoke on the need of continually evaluating and re-evaluating your activities. “Test new things as they come long to understand how they work, and then take a step back and go, ‘Is this sustainable? What’s a better way?’” This agility helps empower teams to reorganize around changed or emerging needs.

When it comes to in-housing, Sorrell notes that the important thing is bringing teams together to work far more efficiently—something that AI can help unlock. “Being able to disseminate knowledge across the organization on the assumption that you’ve ingested the right data, and that you’ve opened it for access to all, is the really powerful thing—and it means you’re going to become a much more singular force for agencies to deal with,” by breaking down the silos and politics that typically slow things down.

Finally, “You have to have a strong foundation of your data. Your data has to be in order,” particularly when it comes to setting up artificial intelligence. But as the lifeblood of your brand, a solid data foundation can accomplish even more. Franklin mentioned Formula One, whose “Drive to Survive” Netflix series brought in a new fanbase, many of whom are women. “So you see how something which is very orthogonal to their actual business, which is a TV series, created this whole new community of fans for them. And what they’ve done from the data side to be able to really drive that personalization has been really impressive.”

The festival captured an industry at a pivotal moment.

While AI dominated the conversation at Cannes this week, it’s important to consider some of the pre-requisites touched on elsewhere throughout the festival: getting your data in order, integrating the business to achieve new outcomes and ensuring you lead with authenticity with everything you do. The beautiful part? Once you’ve made a solid foundation on each of these, you’ll be prepared to fully unlock the potential of technologies like generative AI. 

That’s it for Cannes this year—and we can’t wait to see how AI, more intentional creative and greater diversity on teams will continue to influence creativity next year.

Indeed, the efficiencies and opportunities that AI enables can radically uplevel brand experience and output, though unlocking their true potential relies on understanding how to uplevel teams to use the technology effectively. Those who can fully leverage the power of AI and infuse it within every aspect of their business will dominate the market. But for those lagging behind, this is a Kodak moment: there will be no loyalty for businesses that are slow to deliver AI-powered experiences that make consumers’ lives easier.

Throughout this guide, we’ll showcase AI’s potential to transform marketing today and tomorrow, as well as the actions you can take right now to reap those rewards and lead in the new era.

The marketing and advertising industry is united by the common goal to leverage technology in new, creative ways—not only to translate data into personalized campaigns, but also to enhance internal operations. This is where automation could come in, if it wasn’t for the fact that marketing is traditionally quite limited in using such technologies. Simply put, many marketing teams haven’t been exposed to automation beyond connecting CRM to email marketing, even though there’s so much more out there.

From business to advertising, development and production operations, digital process automation can help unlock efficiencies across the entire enterprise. There are ample automation solutions for digital operations that can provide support across a company’s content, data, media and tech efforts. While the positive impact of enterprise automation reaches far and wide—from enhancing digital ad operations to improving internal people services—the biggest benefit is the ability to free employees from repetitive tasks or unnecessary complexities in the workflow, so as to enable them to direct their attention and energy towards more relevant work. Especially considering the current economic headwinds, it’s crucial to make sure that your talent can maximize their impact. 

My team of Automation.Monks is specialized in enabling the workforce to embrace automation as a new way of working and realize its full potential. We encourage people to automate as much as possible, no matter how big or small individual tasks are—if a machine can do the work, we should probably let it. This requires us to rethink how we operate within a business and how we collaborate with both tech and each other. The team not only focuses on automating our internal people, operations and processes, but also on supporting brands in automating their enterprise. So, let’s take a look at how we aim to achieve maximum efficiency, visibility and connectivity with automation solutions built by our analytics practice.

Helping brands future-proof their business with GA4.  

Our bread and butter is helping brands automate their people, platforms and processes. The objective is to ensure that these work in ways that businesses can accelerate their digital transformation and prepare themselves for the modern era. One of our go-to tools for measurement is Google Analytics. As Google’s GA360 is scheduled to sunset in the summer of 2024, many brands are busy migrating to the new GA4 product to take advantage of the measurement platform of the future. Among many other useful updates, this tool helps brands collect website and app data to get a better sense of the customer journey by utilizing event-based rather than session-based data. It also includes privacy controls and behavioral and conversion modeling that help fill the gaps in your data caused by the cookieless future.  

GA4 adoption requires collaboration between departments across an organization, and is therefore a change management process as much as it is a technology solution. The flatter, richer insights from GA4 data can help brands deliver more value and achieve faster competitive advantages—particularly when the adoption process is planned, communicated and managed to promote knowledge-sharing and digital maturity growth. Many brands have benefited a great deal from automating their business processes. Let’s take a look at the positive impact experienced by some of our key partners.

We’re supporting a global CPG brand that strives to increase their business revenue YOY by 3%, with a media objective of 3% ROI growth—ambitious, but certainly possible. As its partner for global content production, we advised the brand to focus on the efficient use of first-party data, while also establishing the use of connected data collected from across the customer journey. We pitched GA4 as the obvious solution, keeping in mind our pillars of quality, speed and value. Using custom built in-house automation, we helped the brand rapidly deploy 169 GA4 properties in minutes—all the while managing the shift to GA4 and maintaining top quality first-party data during the adoption. The results were impressive: through our collaboration, this brand has been able to unify its marketing efforts and metrics across 37 brands in 150 countries, ultimately realizing a growth of more than 70% in global ROI since 2017.

Another major brand that we were able to help automate at scale is Diageo, the multinational alcoholic beverage company. Diageo has made the ambitious commitment to increase their market share from 3% to 6% in FY 23. In order to realize this, the brand needs accurate tools with actionable insights. Once again, we presented GA4 as the straightforward solution. Considering the planned sunsetting of GA360, we immediately started planning the GA4 adoption process. Diageo’s scope covered as many as 150 brand websites, including 39 D2C sites (and counting) where we collect transactional data, which is a large-scale task. We leveraged custom Google Tag Manager templates for the GA4 tagging as well as our in-house automation tool to automate the GA360 rollout for the GA4 deployment in minutes versus what would normally take a team weeks to accomplish.

Deploying a common data layer taxonomy, harmonized across all brand sites, allowed for true apples-to-apples data comparison. On top of that, it was pivotal to delivering high-quality, privacy-first, consented first-party data. As a result, the team was able to both save over 200 hours of work and assure quality and reliable repeatability. Moreover, any future updates to measurement are consistently applied across all brand sites using the same solution—and align with Diageo’s overall strategic goals.

Designing the future of Media.Monks with clients in mind. 

Automation is critical to driving your enterprise into its next phase of digital transformation. Though solutions are largely technology focused, it’s important to be aware of the fact that automation can only truly succeed at scale and have a significant impact on your operations if it’s spread across and woven into every facet of your company culture. By incorporating many new, exciting and innovative tools into the tech stack and empowering your people, you can lift your business to the next level of operational excellence. For example, my team is currently working on productizing cloud-based “starter kits” that can easily deploy within a company’s tech stack and seamlessly integrate with existing or modified operational processes. CMOs can leverage these tools to connect their media efforts to the rest of the organization, which allows for better visibility, data interoperability, and measurement in aligning media efforts to business objectives. This is just one of the many ways in which automation can help organizations become more efficient in reaching their marketing and advertising goals.  

No matter the size of your business or the industry that you’re in, enterprise automation enables you to both streamline your people, processes and operations and enhance the output of different teams. In other words, it allows you to do more with less. Our advice? Start building an automation-first company culture now. Recognize where the biggest pain points are in your workflows and thus where your workforce needs to level up with new skills. When it’s deployed in line with your business goals and objectives, automation will maximize your existing talent and set up your business for future success. However, since there’s no one-size-fits-all solution for enterprise automation, the key is to start now.

The impressive output of generative AI has led some to voice concerns about whether their livelihoods are in jeopardy. Creativity, after all, has long been considered a strictly human skill.

But creatives aren’t about to lose their jobs to robot overlords who can spin strings of text into pixelated gold. To the contrary, these tools—which rely on human input and some level of artistic aptitude to really shine—are unlocking creative potential and helping people bring their concepts to life in new ways. This outlook prompted the Labs.Monks, our research and development team, to explore how generative AI can uplevel the work of our teams and our clients.

“We’ve been playing with this technology for a while, and after it began to trend, we’ve been getting more and more questions about it,” says Geert Eichhorn, Innovation Director and Head of Labs. For instance: a lot can be said about the future of content creation aided by AI, but how could today’s tools integrate into a present-day production pipeline? 

Looking for an answer, the Labs.Monks collaborated with animators and illustrators on our team to develop a prototype production workflow that blends traditional animation methods with cutting-edge AI technology. The result is an animated film trailer made using a fraction of the time and resources that a typical, frame-by-frame animation of its length would require.

Learn to live with the algorithm.

Ancestor Saga is a 2D-animated side project focused on a central question: what if people in the Viking Age realized they were living in a simulation? After learning that their purpose in life is to entertain the gods, will they accept their new reality, or put an end to the world by bringing about Ragnarök?

The theme might feel familiar to anyone trying to make sense of the increasingly algorithmic world we’ve suddenly found ourselves in. “We wanted to tell a story that could integrate with the tech we’re using: virtual worlds and virtual people,” says Samuel Snider-Held, Creative Technologist. Associate Creative Director Joan Llabata takes this thought further, citing some of the challenges faced when humans and AI don’t quite connect. “There’s some space where we need to find the best way to communicate with the machine effectively,” he says.

When using generative AI, a bespoke approach is best.

That challenge of getting humans and AI to play nice demonstrates the need for a team like the Labs.Monks to experiment with the tools that are available. While off-the-shelf tools are great for empowering individual creators, integrating them into team pipelines requires a more custom solution.

AI is designed to do specific tasks very, very well. Projects that involve multiple capabilities and phases call for a workflow that can integrate a variety of generative AI to fulfill different goals throughout. With an animation project, this means plugging into creative concepting, storyboarding, sound and of course animating the visuals.

In our case, says Snider-Held, “We wanted to explore how AI could allow us to do the work we really want to do, even if the time or the budget isn’t there.” He found that while our animation team loves classic, frame-by-frame animation, the method is often overlooked because it is slower to produce and less cost-efficient than other ways of animating. 

Now the team had a clear goal: orchestrate an AI-based workflow that could output a frame-by-frame animation in record time, without compromising quality. They took inspiration from rotoscoping, a method used by animators like Ralph Baskhi, in which an artist traces images over existing footage. This task of translating an existing recording from one style to another was ideal for image-to-image generative AI. In addition, the team used AI technology to develop background designs and read out the animation’s voiceover.

Generative AI isn’t a radical departure from tradition.

The team began by recording a 3D character model in a virtual setting, capturing a variety of poses for an illustrator to trace over. These visuals were then used to train the AI model on how to draw the character in different movements. “If you draw about five frames, you have enough to teach a neural network how to paint the others,” says Snider-Held, noting that it’s important to select frames that are different from one another so the AI can pick up on various forms, shapes and poses.

In addition to rotoscoping virtual production, the team also experimented with live-action stock footage. Being able to use two different types of visual source material baked extra flexibility into the process; teams could mix and match the different methods according to their specific needs or abilities. Fantastical creatures might be captured more easily in virtual production, while a team lacking in their ability to animate lifelike movements may prefer using live-action film as a base. “You get better acting from footage versus a 3D model, but the visual output is ultimately the same,” says Snider-Held.

Much like how that process emulated classic rotoscoping by hand, other ways of integrating AI followed a traditional animation process, albeit with some additional steps here and there. For example, the storyboarding phase is important for visualizing which types of shots or animations are needed for a specific sequence. In addition to pondering that, the team also planned which kinds of AI would be best for generating this or that shot.

Using Stable Diffusion—a kind of generative AI that translates a text prompt into an image—allowed the team to create a large volume of backgrounds that they could swap in and out to test how they looked. “You can explore a lot in this phase,” says Snider-Held.

As for developing backgrounds in particular, “It’s like describing the shot you want to a director of photography,” says Llabata. He was able to test hundreds of different environments, camera angles, artistic styles, lighting and more, all with relative ease.

Unlock efficiencies and long-term gains.

The findings above hit on perhaps the biggest gain that a generative AI-powered workflow can provide: greater flexibility throughout the life of a creative project. Being able to generate 60 frames in one minute—rather than one frame in 60 minutes—makes it incredibly easy to pivot or change things up in the blink of an eye.

It doesn’t require a sophisticated hardware setup either, further making content creation accessible to teams of all sizes. “You don’t need a giant server or cloud computing,” says Eichhorn. “A reasonably good gaming PC can churn out assets like backdrops quickly.” Still, more complex uses of AI like rotoscoping may require more power.

The flexibility unlocked by integrating generative AI into a team’s pipeline continues to pay dividends beyond the life of a single project. “If you have a project whose scope is really big, the effort and money you spent in that R&D is compounded in value over time,” says Snider-Held, noting that whether a brand wants to make 10 animations or 30, the steps to lay down an AI-powered foundation will be roughly the same.

Experiment to find an approach that suits your needs.

Tools like stable diffusion aren’t meant to replace those in the creative field. “An AI will not achieve anything by itself,” says Llabata. Instead, these products will give teams the ability to chase more ambitious projects with fewer constraints in time and budget. Just consider how closely the creation of the Ancestor Saga trailer follows a traditional animation process, just with more efficiencies baked in. 

Such flexibility afforded by generative AI can go well beyond traditional animation.

Whatever your use case for generative AI, understand that while building tools from scratch can be challenging, the result is extremely powerful. “Our approach is that if an off-the-shelf tool is mature enough, use it. If not, create it yourself,” says Snider-Held. In addition to ensuring a tool is calibrated for their specific needs, teams who go the bespoke route will also be better poised to future proof as the technology continues to evolve at a rapid pace.

So, think you’re ready to explore what generative AI means for your field? Learn more about the ins and outs of the technology in the latest Labs Report exploring the rapid evolution of digital creation.

Owned digital products designate every digital platform whose code belongs to the brand. The terms “platforms” and “digital products” are often used interchangeably, but while the former can be mistaken for third-party channels like TikTok or IG, the latter is, in my opinion, a better name for a brand’s unique spaces. Marked by flexibility and potential for personalization, these digital products encompass everything from dotcoms to TV apps—and can serve whatever purpose brands deem necessary in meeting their goals and keeping with consumers’ desires.

Because there are no intermediaries, you can have full authority over the brand image that your digital products project. And that’s a big responsibility. What the brand experience looks and feels like on these platforms is how people will perceive your brand to be, so what should you prioritize when it comes to building your own digital products? 

Functionality, efficiency and innovation.

Back in the day, websites were unidirectional and served mostly as a source of information. Now, standards are higher. Whether we’re looking at content hubs or a smartwatch app, successful digital products must strike the right balance between functionality, efficiency and innovation. Consumers won’t stick around for websites that make it hard for them to find what they are looking for—or even worse, that don't fully work—but they will remain loyal to those that provide a seamless user experience.

That said, building functional websites from scratch is no easy feat. Because of this, many brands resort to auto-site builders—especially when it comes to ecommerce integrations. While this may temporarily fix the problem, website templates are not a permanent solution because it begs the question of whether consumers are going to be able to remember it. As they search for product options and scour through multiple tabs, will yours stand out among the rest?

Innovation is about creating the “wow” moments that will remain engraved in people’s minds, and adding interesting features that make a platform completely different from those of your competitors—even if your offering is similar. HP’s Possibility City, for example, is not just another ecommerce platform. Rather, it’s a showcase of HP’s digital printing presses that doubles as a hub to house sales events—from product presentations and webinars to one-on-one demos. And while visitors explore the brand’s lineup, the platform learns from their interests and provides them with tailored content recommendations.

Data and personalization: the next frontier of loyalty.

Provided that your platform is intuitive in its use and delightful in its appearance, the next step is to offer personalized features that make the experience truly unique. To get there, you need the data analytics infrastructure to provide valuable information about your consumers and a team of experts who can turn that into actionable insights.

I always work closely with the data team on both the company and the client side to improve our customer understanding. On one hand, a strong first-party data framework can help you identify how consumers are moving across the ecosystem—where they click, how they behave and where they find friction points. By designing around these general trends, you can deliver a more seamless experience for all.

On the other hand, individual data unlocks a new world of possibilities in terms of personalization. With Possibility City, for example, we included a virtual assistant that learns from visitor preferences—whether they’re looking for efficiency, sustainability, security or other priorities—and guides them through the brand’s offering. We also tied the platform into a CRM funnel that helps automate the closing of sales, keeping us informed of customer needs and how to improve efficiency. 

Designing around your business priority.

In addition to collaborating with data experts, my team and I work closely with the business consulting unit, as they can provide valuable insights into a brand’s digital roadmap and long-term business goals. Digital products should be built around this vision—not only to help brands achieve their goals quicker; also, to ensure their platforms are one-of-a-kind. 

In working with multiple airlines throughout my career, for example, I found that while some needs were universal, no two business models were ever alike. Options like “book a flight,” “check-in,” or “see my reservation” were common currency—but while certain brands simply wanted a functional app to help travelers organize their trips, others sought to raise the average ticket value by encouraging consumers to opt for upgrades, extra bags and other add-ons. The mere act of designing around these priorities made each platform totally different from the next. 

The bottom line is that digital products are as much the translation of your business as they are the embodiment of your brand identity. To get the most out of them, you need to understand your consumers and, above all, your own brand. In working with clients, my goal is to help them create differentiated products that drive their business forward, and it’s the brand’s values and identity that ultimately do the trick. By taking identifiable brand elements and combining them with functional, innovative and personalized digital products, we can create a truly memorable brand experience that forges deeper connections with your audience.