How to Use AI for More Meaningful Marketing: 4 Steps

Blog Post
June 15, 2018

It’s been a decade since Mad Men’s Don Draper and his entourage dramatized the now-antiquated approach to marketing: create a product then convince consumers they can’t live without it. For today’s marketers, given the focus on big data, personalization and one-to-one marketing, that methodology feels foreign.

However, as technology continues to evolve, current thoughts on marketing are being challenged yet again—this time by advancements in artificial intelligence (AI). These advancements can be turned into opportunities if marketers have clear ways to harness the technology to address customer needs.

Read on for four practical steps toward harnessing AI for use in marketing.

What is AI (and IoT, for that matter)?

Though the term is widely used in marketing circles, it’s worth starting with a simple level-set definition: artificial intelligence is technology that gives machines the ability to seem like they have human intelligence. (Read more on the use of AI in marketing in one of our previously published blogs.)

The irony of AI is that it combines some of the most advanced, impersonal computer technology with the end goal of getting more personal and in touch with human needs and emotions. Using technology to be more humanlike? Yes, that’s the goal—and one on which many great brands have already delivered.

The irony of AI is that it combines some of the most advanced, impersonal computer technology with the end goal of getting more personal and in touch with human needs and emotions.

Here’s another term that is nearly two decades old but now growing in popularity. IoT refers to the “Internet of Things,” a phrase coined by Procter & Gamble executive Kevin Ashton in 1999. In short, IoT is the network of physical devices, vehicles, home appliances and other items embedded with electronics, software, sensors, actuators and connectivity which enables these objects to connect and exchange data. Let’s simplify things with a few concrete examples.

  • General Electric has long focused on building technology that improves the consumer experience in daily life. One example is their use of IoT technology to build light pole sensors that range from convenience to safety benefits in parking lots. The sensors can make customers aware of open parking spots or be used to detect gunshot sounds, alerting police to danger in the area. In business, IoT technology is also freeing up people to do more meaningful work, while having computers do previously tedious, manual labor by threading AI throughout its operations. For example, 15 years ago GE’s machine operators and technicians monitored its aircraft engines, locomotives and gas turbines by listening to their clanks and whirs and checking gauges. Today the company uses AI to do the equivalent—even predicting failures in advance.
  • A little closer to home, there have been significant advancements in smart home product developments. Smart thermostats, over time, learn the habits of a home’s occupants to adjust the temperature and not only make the home more comfortable but also energy efficient. Smart security systems allow you to automatically lock and unlock your door based on presets or manually from your mobile device. ADT offers home and personal security through their ADT Go app that allows the user to press an SOS button and have emergency response deployed instantly. It integrates with other safety features to monitor for carbon monoxide, and with home systems like Amazon and Google to control locks, cameras, lights, thermostats or virtually anything, all from a central hub accessed on your smartphone.
  • Procter & Gamble is a consummate example of “growing up” their employees with a mindset of innovation and helping customers get jobs done. They developed a system that blended the flavor profiles of one of their top brands of coffee—a process that’s long been done by humans to try to tailor the flavor to consumer preferences and market trends. Having flavor sensors to identify subtle nuances and quickly evolve to meet consumer tastes means getting to market faster with a more appealing product. In this case, it saved the company in excess of $20 million a year. Other brands are using technologies to develop custom beers suited to your tastes. (Even Don Draper might have turned in his Old Fashioned cocktail for a craft beer had technology been available for alcohol distributors to detect his taste preferences and then make recommendations.)

These brands combine AI and IoT with media channels, content and marketing to provide a holistic and omnichannel experience to customers that feels more like a conversation than marketing. At the center of every good example of AI in use is a clear benefit to a company, process and/or consumer.

However, many marketers still feel the sting of too much hype and too little payoff when it comes to AI. In fact, only 18% of marketers claim that AI is delivering the goods as promised, and 43% felt they were over-promised, according to global marketing automation expert, Resulticks.

61% of marketers say personalization is a priority for their company, but it appears there is still a gap in applying it to practical marketing implementation. 

In that same study, 61% of marketers say personalization is a priority for their company, but it appears there is still a gap in applying it to practical marketing implementation. Perhaps the solution is shifting mindsets from simply meeting sales goals to using AI’s powers for “good” in helping to solve customer problems.

Marketing as the ultimate “fixer”

It may not have been explicit in your job description, but being a “fixer” is now a key function of marketers: determining what a customer is trying to get done and being there to offer a relevant solution. It’s not just about “pulling” information about customers to push products, but really getting to know them and what they need to provide solutions to problems they’re currently having—or ones they don’t even know they have yet.

That kind of interaction blends the data and science of AI and what a company knows about an individual, with the art of how to speak to them in moments that matter, in a tailored and relevant way.

To get to a practical marketing level, think of the process involving four key components:

  1. Collecting data
  2. Drawing insights
  3. “Listen” to behaviors
  4. Building relevant interactions

1. Collect data

Data is foundational in any marketing application, but getting cross-platform systems to work together is just as essential. Think of Amazon and the years and dollars spent getting them where they are today: held as a frontrunner in one-to-one marketing. But sometimes they still get it wrong. Take this personal Friday night example: I’m on my couch ready to watch a movie using my mobile and Google Chromecast to display to my TV. However, I can’t do that through my Amazon Prime account because Amazon and Google are like the iPhone and Android phones—they don’t work together. They’re competitors, and I get it, but that’s not helping my own user experience.

The same obstacle exists in marketing. Today most brands have a database, and that’s the most valuable starting point. They’re capturing unique interactions with the customers and have the data to show for it. But, just having the data isn’t enough. Marketers need to draw insights from the data and make it actionable.

2. Turn small data into big insights

As marketers we’re acutely aware of “big data.” But now we’re starting to think in smaller data chunks. Think of the technology now available that tells us what customers are thinking, doing, wanting and considering. The list is virtually endless: Fitbits, Nest Thermostats, Alexa, Google Home, ADT Go Family Security app and so on. These small-data points are resulting in a very big data explosion. There’s even technology that can watch human expressions and understand emotions. The job of marketers is to take all that data and listen to what it means for an individual.

3. “Listen” to behaviors

Making data small means doing a lot of listening. Where did you search online? What did you download? What app did you use? Were you on your laptop or mobile device? Were you at home or in the office or out of town? 

Then you can sift through to find what’s important, so you understand what it means for John Doe—in the moment—so you can react in a way that’s helpful and meaningful to him

It’s asking, “How can I help you today?” and using all the massive amounts of data you may have on John (or someone like him) and turning it into small data that addresses a meaningful response to John in his moment of need. It means constantly thinking with a mutually beneficial mindset…what will ultimately most help John, as well as best serve my brand? The intersection of those two things is where the magical marketing happens.

4. Build relevant interactions

We use a framework that is grounded in both art and science. We start by building strategic marketing solutions that focus on the human aspect of marketing. This involves persona development, mapping the buyer’s journey and creating rich content that’s relevant to that journey. We use technology as an enabler to help engage customers, but the technology must be built on a premise of listening to the customer to understand what they need, how they need it, where they are in their journey, and how we can help them—and talking to them so that we’re delivering value every step of the way that ultimately helps them solve for whatever their need is.

Our partnership with WiPro offers a technical bridge between big data and the ability to execute highly personalized, relevant marketing campaigns. I often tell clients that we leverage such tools to amplify what they know about their customers and give them deeper and alternate views of those customers and their buying signals. This allows us to predict likely behavior and to communicate in a very personalized way to help their customers get the jobs done they’ve set out to complete. That insight transcends to creating a martech ecosystem that allows you to build very personalized content to foster conversations with those customers that doesn’t feel like marketing at all.

Marketers: it’s time to get started        

Overwhelming as this might feel, the art and science of human marketing is something brands don’t have to build from the ground up. The world of artificial intelligence has opened the doors for nearly every marketer to build tighter, more meaningful relationships with customers. As the use of AI continues to expand throughout organizations, it’s the job of marketers to harness that data and use it to become more relevant to customers. Even resource-strapped brands or those who simply don’t want to manage the innovation required to stay competitive for the long-haul can find help in partners.

Ultimately, our job as marketers is to deeply understand our customers and help them in ways that are smarter, easier and more productive—perhaps even entertaining. When we do that, it’s like having a conversation with a friend—and it makes marketing more human. When we do that—we all win.

Ready to get started with more meaningful marketing? Check out our approach to building your Data & MarTech Ecosystem, or get in touch.