Artificial intelligence (A.I.) gets a lot of buzz lately, and with good reason. More and more digital tools are taking advantage of smart features that can actively analyze and adapt to situations in real time almost as well as an actual person. Across industries, organizational leaders are examining how A.I. technologies can remove bottlenecks, enable them to scale their services, and enhance the efficiency of their workforce.

Yet, no industry stands to gain more from A.I. right now than marketing. Marketers have core goals that include understanding customer needs, delivering relevant and helpful content and product suggestions, and converting individuals at a consideration phase of a buying journey into purchasers — all objectives that can be made more attainable with the use of A.I.

That explains why a 2020 Deloitte survey of companies already using A.I. revealed that three of their top five business goals for the tech were intrinsically connected to marketing:

  1. Enhancing existing products and services
  2. Creating new products and services
  3. Improving relationships with customers

Helping with Tasks Big and Small

Though A.I.’s capabilities improve seemingly by the week, most current applications don’t involve high-level strategies or complex tasks. A.I. systems are great for recognizing basic signals and taking the correct action in response, such as automatically sending welcome emails to new users and customers or sending follow-up messages after a sale.

Perhaps the most common A.I. marketing application today is the programmatic buying of digital advertising, which refers to smart systems that select and place digital ads based on optimization criteria. Broader tasks, such as improving sales forecasts with machine learning-based analytics, are on the uptick, however. As are intelligent software platforms that augment the reach and effectiveness of human resources, notably smart decision trees and suggestion systems used by customer service agents.


At every stage of the customer journey — from before they are even aware of a potential solution to a problem or need they might have, through the analysis process, and even after a purchase is made — A.I. can help reduce friction and identify leaks in a marketing funnel. Consider the example of online furniture brand Wayfair, which deploys an A.I. model that ranks visitors to their website based on likelihood to purchase a particular item (based on browsing histories and geolocation data) and then promotes products to users that are keyed to those predictions.

“Across industries, organizational leaders are examining how A.I. technologies can remove bottlenecks, enable them to scale their services, and enhance the efficiency of their workforce.”

Others utilize intelligent chatbots to enable conversational commerce by answering basic questions, offering helpful links, and connecting visitors to a human agent at the appropriate time. These bots help reduce online shopping cart abandonment through targeted outreach like sharing a customer testimonial to a user that appears to be reluctant to make a final decision. According to the Harvard Business Review, efforts like that can increase conversion rates fivefold.

Leveraging Machine Learning Responsibility

ML, or machine learning, is a subset of artificial intelligence that involves algorithms that are trained on massive quantities of data and over time learn to spot patterns, generate predictions, and make difficult decisions automatically. They can read text, analyze images, and pore over massive databases far quicker than even the most talented human tech wizard and accurately categorize, segment, and prioritize the information.

Companies like online personal styling service Stitch Fix use ML to track customer preferences and deliver product suggestions with a high likelihood of matching a user’s tastes. They draw data for their ML model from a variety of sources, including:

  • Internal transactions
  • Pricing data
  • Publicly available repositories (e.g. market trend data)
  • Social media posts

It should be noted, however, that though consumers appear willing to trade away a certain amount of human connection in exchange for better services, privacy concerns and fears of automation run amok are not uncommon or completely unfounded. Many homes are now filled with smart speakers listening to every word, but a growing number of consumers are voicing their anxiety at the thought of their intimate thoughts or shopping choices being made public

Hence, it is vitally important for brands using these tools to be as transparent as possible about what they are doing with customer and user data and how they are protecting it. Thought leaders in this space are establishing protocols that stay ahead of the growth of intelligent technologies.

Scalable Copywriting Inches Closer to Reality

One area of A.I. that gets outsized attention but which still has some room to grow is the use of machine learning in copywriting. The appetite for helpful and well-written content online is insatiable and many brands would love to be able to scale up their content pipeline with A.I. writers.

“Brands using these tools must be as transparent as possible about what they are doing with customer and user data and how they are protecting it.”

GPT-3 (Generative Pre-Trained Transformer 3) is currently the most advanced system for producing human-like copywriting. Developed by OpenAI and released in June of 2020, it is built on a dataset of hundreds of billions of words from sources like public domain books and Wikipedia articles. After training the system on that much written information, it has developed an uncanny knack for predicting what comes next when fed a brief overview of a topic and can produce sometimes eerily lifelike, even poetic, prose.

That said, it can generate as many hits as misses and still requires a fair amount of work producing the input copy. There’s a common aphorism in computer science called “garbage in, garbage out.” It implies that you’ll never get valuable content out of a GPT-3 system if you don’t give it something halfway decent to work with at the start.

There are a number of online services based on GPT-3 and a few other machine learning language models, including Writesonic, Shortly AI, Anyword, and Copysmith. They have their uses but aren’t quite ready to fully replace a human copywriter — though that day will almost certainly arrive and if past A.I. innovations are any judge, possibly within just a few short years.

The Revolution Has Already Begun

Whether you’d like to accelerate trend analysis, add ML tools to your ad buying or SEO strategy, deploy a virtual copywriting solution, or simply gain better insight into how your organization operates, there is almost certainly an A.I.-powered platform available right now to help — regardless of the size or complexity you bring to the table.

And the time to start considering which to use is right now.


Hanlon works at the bleeding edge of modern marketing with automated and intelligent tools that enhance customer experiences and grow brands. Ask us what we can do for yours.