Raise your hand if you’ve read at least one article about robots replacing certain jobs in the future…What was that? 


C-3PO, we weren’t asking you.

Kidding aside, there are a lot of misconceptions about automation, and how it relates to marketing. These can be blind spots for marketers if they are trying to understand what their MarTech providers do, and how they do it. We’re here to identify those unknowns, and to make sure that complex technology isn’t code for confusing technology. 

FICTION: Automation, Artificial Intelligence and Machine Learning are ALL the Same Things

Fact: Nope, they’re not. 

Let’s take a minute to get acquainted with some of the definitions that we’ll be using throughout the rest of this blog. 

    • Automation is a range of technologies that reduce manual intervention into the processes, often with the goal of increased speed, quality, and output.

Why do marketers care? Listen, we know that the glossary isn’t always the most exciting section of any book to read, so we’ll get to the point. If you don’t have automation, then you’re paying humans to click the same buttons day in and day out. Automation takes some of the rote tasks off your team’s plate, so they can do some deeper thinking and strategizing for your brand, while also building relationships with prospective renters or residents. 

    • Artificial intelligence (AI) truthfully this one is tough to define. AI is an umbrella term for many types of advanced technologies and ideas. What do these AI technologies have in common? Through algorithms (another term! Let’s say code/equation) they enable a computer to perceive, reason, and learn. 

Why do marketers care? AI is difficult to build and it focuses on solving complex problems like optimization and prediction. Marketing budgets are often the first to get cut (P.S. This is a bad idea), so, we know that your marketing spend needs to be air tight and drive leads. AI does this more efficiently and powerfully than any team of humans. AND, it gives your sales and marketing team time to focus on big picture priorities, rather than accidentally majoring in stats, while proving your marketing budget’s impact. 

Here is where this gets complex, and hopefully not confusing. 

    • All machine learning is AI, but not all AI is machine learning. Translation: machine learning is a subfield of the AI umbrella. A machine learning system relies on the right algorithm to make sense of a data source. Another way to think about this is to substitute the word “algorithm” for “complex-mathlete-AI-machines.” Data is the fuel that runs said machines, and they are very dependent on the quality of the data. Perhaps you’ve heard the phrase, “garbage in, garbage out.” Sure, this is a data science cliche, but it’s also true. Machine learning needs to be fed accurate and meaningful data in order to produce results that are also accurate and meaningful. Over time, these algorithms learn to adapt and make better decisions.  

Why do marketers care? Machine learning algorithms look through a vast data set to begin to understand patterns that may be too subtle for any one human (no matter how talented) to pick out. This allows computers to learn (i.e. machine learning), without being explicitly programmed with specific rules for xyz scenario. And for marketers, this means that machine learning can notice that on Tuesdays researching renters or residents are more likely to pick up a phone and call your team, or fill out an online form. Once patterns like this are noticed, your marketing spend can be allocated toward customer journeys that are more likely to end in an inquiry, like a phone call or website form fill. 

FICTION: AI is All-Powerful

FACT: AI is powerful, but it’s not bippity-boppity-boo magical. It needs to be built and trained with data sets to refine results. 

AI and data are among the buzziest of buzzwords and sometimes they get thrown around seemingly without their meanings attached. They are powerful, but they’re not Hermione Granger magical. They are logic-based systems. 

Humans, like you, first define the problem that they’re trying to solve: I want to get more high-quality leads via digital marketing. Then, they identify the right technology to solve it, train the algorithms with strong data sets, deploy and validate the algorithm, monitor the algorithm, and keep iterating or making it better. Monitoring the algorithm is important because sometimes the world isn’t the same as when the process started, and this can change the data. What do we mean by that? Think of how COVID impacted the market, it ALSO impacted the data. So, data scientists need to monitor for big changes like this and keep retraining the algorithm. Check out the graphic below to understand the development process for AI projects. 

As we said above about monitoring, data scientists test that the results are indeed valid, and solve what they were attempting to solve in the first place. Check out the visual below, to understand how AI and machine learning become more refined and consistent as data scientists train the algorithm, deploy and validate the algorithms, and monitor the algorithms. 

FICTION: All This Tech Talk Is Only Important in “Fancy” Industries

FACT: Your industry is that fancy. Pinkies up, dear. 

We get it, it’s easy to think of AI and machine learning as things that billion dollar companies like Google might need, but who is to say that your multiple-hat-wearing-marketing-team-of-two, could be more impactful when backed by an algorithm? 

Well, in the land of digital marketing, we are here to say your digital marketing WILL be more effective when backed by smart AI tech solutions. To be blunt, the “this doesn’t apply to my industry” argument is antiquated.

COVID accelerated tech-adoption to super sonic speeds, and there’s no going back. What do AI and machine learning rely on? Data sets. What does a predominantly digital customer journey give marketers? Data for said data sets. (P.S. there’s a lot of buzz around data and first-party, third-party, and cookies, so go read this blog to learn more). 

There is absolutely a benefit of being an early adopter of new technologies. As we see it in marketing, you have two choices: adopt automated AI driven technology solutions to optimize your marketing, or find yourself left behind with 2019-style marketing solutions. No bueno. 

Complex and Clear

It’s no secret that in our industries the customer journey is complex and nuanced. And, it’s clear that data empowers marketers to reach the right researching prospects with the right message, at the right time. Learn more about the G5 approach to data-driven marketing by downloading our CDP + Data MarTech Report