Input-Ready Data: Making the Most of AI in Marketing

Tell me if this sounds familiar: My kids, who are digital natives, think I’m kidding when I tell them there were no cell phones or the internet when I was in college. They say, “Yeah, right dad,” like it’s something they can’t even imagine. It’s the same reaction I used to have when my parents would say they remembered a time when there was no such thing as color TV.

Now, with artificial intelligence (AI) seemingly “everywhere all at once,” it’s fair to say that 20 years from now, people who have never lived without AI won’t be able to comprehend a world before it existed. Like the internet and television, AI is a turning point— when every single thing we do, especially in the world of marketing, is going to be different.

It’s a lot to take in. Everyone is preoccupied with the big picture— the marathon— and there’s a lot we don’t know yet about AI. But what I do know is that if marketers don’t have strong repeatable processes and standard operating procedures, they won’t have much use for automation and AI.

It’s a state of readiness that I’ve been thinking about and calling input-ready data— the idea that as market platforms increasingly embrace machine learning and AI, there needs to be a system framework for organizing the plethora of data that can be ingested to alter performance on these platforms so that they’re more accurate, more up-to-date and more easily accessible.

Input-ready data, I believe, is how marketers can use AI to make more informed decisions quickly to build scalable strategies that set their brands apart. And it starts with a few essential building blocks:

1. Use data to make the case for more marketing investment.

If you were to ask me why Rise Interactive is the best performance marketing agency when others have the same tools we have, I would tell you it’s because we have a mathematical philosophy and differentiating factors in how we approach our business. Helping marketers find smarter ways to leverage media data to make better decisions is at the core of what we do.

Likewise, working with marketers to hone in on a strategy designed to differentiate their brands and help them win using the same tools, models, algorithms and AI as their competitors is something I find interesting. A big part of the future, I believe, is having access to unique data to help steer these models in such a way that reflects a brand’s strategy and secret sauce.

Brands now have access to the same machine learning and AI tools, not to mention the fact that many of them are free, so the importance of knowing how to get the most out of each is becoming increasingly important. Take, for example, ChatGPT. You don’t just “turn it on.” There are prompts, and you have to ask it a question or give it direction. You have to tell the AI model what to do, and this all comes from data and a strategic vision.

I was at a conference recently where a marketing leader from Hershey’s defined the brand’s target audience as anyone with a mouth. Another from L’Oréal defined theirs as anyone with skin. Consider the possibilities and results if you were to break down these audiences into cohorts and target them with personalized messaging defined by AI: You can move even more product, do so more efficiently, and scale your business.

And when you use data to do this, you can empower the CMO to make the case to the CFO for more investment dollars because you’ve demonstrated a massive opportunity for a financial return. (We actually took this on a couple years ago at Rise, when I challenged our CFO to become more growth-minded and think beyond the expense side of the business, and at the same time, challenged our head of marketing to understand what kind of data CFOs need to see to feel good about the budgeting decisions they’re making. I encourage you to read about the 10 best practices that came out of the work they did together.)

2. Standardize processes that can later be turned into AI.

If you took inventory of your input-ready data— data that you have at the ready to influence these platforms— would you know what you have? Would you know how to use it? For that matter, have you built a process around using these tools that’s scalable and can be automated so that you can start to benefit from AI? These are questions I encourage clients to ask themselves and that we’re asking ourselves at Rise.

Still, AI does not need to always be on a grand scale. New tools are emerging every day that can help us be more efficient. At Rise, we spend much of our time attending meetings and responding to emails, so we’re looking at tools that can help us do this more efficiently— latest technologies that can dictate meetings, learn each participant’s voices and are searchable. Now we’re looking at how we can use this kind of tool in our sales meetings so that our teams can get all the information they need about a client before we sign them without having to start from scratch.

There are so many things you can do when you give information to a system and it gives you an output, and that exchange is what I’m talking about— and what a marketer will be able to do through this idea of input-ready data.

And let’s not underestimate the speed factor: The marketer doesn’t have the time or ability to create these things fast enough to keep up with consumers who are in front of so many platforms and channels all at once. So how does a marketer target the right person with the right message and how does speed play into that to differentiate yourself from your competitor?

Again, If you don’t have repeatable processes, you’re not going to have much use for automation or AI. Before worrying about the marathon, start focusing on the data that needs to be cleaned up and in a position where you can quickly use it to your benefit, whether that’s AI, digital marketing, sales, CRM— the list goes on.

3. Build a team that can capitalize on the possibilities AI enhancements have to offer.

A key advantage of leveraging input-ready data in the use of AI will be the ability to act on real-time opportunities. To foster that skill across an entire team, marketing leaders must hire a new breed of talent.

I’ve been talking for quite some time about the need to shift to a different type of skill set for our marketing teams to be able to do this. And while we’re always prioritizing people who have a vision, a strategy and ideas for using these tools to do remarkable things, there are a few specific traits I also believe are worth considering in building out the digital marketing team of the future:

• Comfortable integrating AI into their daily work. AI-powered tools like smart assistants, voice recognition software (e.g., “Voice In”) and video-monitoring apps with closed captioning help teams streamline everyday workflows and scale content quickly, leading to improved efficiency.
• Able to optimize the most cutting-edge technologies. This includes AI powered by GPT-4, the latest version of the sophisticated language learning model ChatGPT.
• Know how to collaborate cross-functionally. Marketers who look at their strategy and see silos— from tech to teams— are struggling to keep up. It’s essential that you break down organizational silos and drive collaboration across teams.

Without a focus or direction, it’s easy to get lost in the possibilities of AI because the possibilities are endless. But we’re only at the start of this marathon, with time and opportunity still to think and talk about what will be necessary to go the distance. Let’s connect and join me in this conversation.