The huge volume of data churned out whether from sales, online customer behavior or market research surveys has brought companies to cave into the applications of artificial intelligence (AI) in their marketing practices. With the goal of improving ROI, driving down operational costs, creating the best customer experience and other ways of optimizing customer lifetime value model, AI in marketing has been adopted by some companies that meet the necessary requisites to adapt such technology. However, for most small and medium enterprises, AI applications in marketing have fallen short of their expectations of huge profitability. In this article, we’ll look into the necessary constituents to begin using AI for your marketing and what industries have benefitted the most from applying it in their solutions landscape. Finally, we’ll learn how to identify if your business is ready to consider adopting AI in your marketing future.

Basic Applications of AI in Marketing

For AI in marketing to work, a vendor company and in-house data science or AI experts analyze data flow and current marketing systems. They then determine the meaning of the results and calibrate accordingly. Marketing applications of AI have evolved together with the demands of marketers, advertisers, sales managers and entrepreneurs to cater to different customers in their acquisition funnel. For example, AI applications in marketing help identify unique market segments through clustering or segmentation. Marketers can derive meaningful results from data patterns with the help of AI that would otherwise be very difficult for humans to do in a short span of time. Marketing tech firm Optimove assists marketers in finding unique market segments through its highly complex behavior modeling system. Through customer micro-segmentation technology, they divide customers into precise groups and then use data attributes to predict customer base behavior and value. The information is used in selecting which type of market action should be applied to each customer segment. ownerIQ, a Boston-based digital media company, integrates marketing processes by providing second party data (those that come from marketing partners that a brand is working with or from non-competitive brands) used in marketing tactics. Marketers can also find common patterns of behavior among customers from a specific lead source through AI. It also supports online entrepreneurs in finding patterns on upselling data and recommending products that are best bundled to improve take rates. AI also helps optimize desired outcomes. PredictiveBid, an AI-powered bid optimization app, reduces the risk for marketers bidding on unprofitable keywords on Google Adwords. It analyzes millions of keyword bids in real time and then employs a bidding model according to a company’s marketing goals. Quarizmi also uses AI to refine keywords listing and calculate optimal bids to help online marketers improve their campaigns. Personalized marketing is another area where AI is applied. Canadian tech firm helps increase ad exposure to drive optimal results for advertisers through image and video content optimization. Its system chooses an image or thumbnail video that best represents a product for a particular user. And who would ever thought that automated article writing can be made personal? Narrative Science offers data-driven technology that writes auto-generated unique descriptions based on company data — all with a conversational tone. Boomtrain, on the other hand, offers AI-powered insights to create one-to-one communication for every customer across multiple channels. If you’ve noticed personalized content, images and format molds when visiting a website, it’s most likely that this technology was developed by LiftIgniter. On the other hand, BlueKnow employs AI to send custom messages (inclusive of alternative offers) to buyers within minutes whenever they abandon their carts in an online store.

Who Stands to Benefit the Most in AI in Marketing?

TechEmergence recently launched an expert consensus poll to over 50 executives running companies at the intersection of AI and marketing. They asked the executives for their opinions on which industries were seen to be most and least promising for applying AI to marketing. AI and how it can make a difference in the coming years, among others. And the results are quite interesting. From our sample companies, TechEmergence found out that, by and large, in the next five years, there won’t be many major shifts towards AI in marketing for most businesses, especially the average small and medium-sized enterprises. Most opportunities will be tapped by eCommerce and social media giants that will be using tons of AI applications and reaping huge profits with them. In other words, they will look into direct-to-consumer niches that are most likely to bring in higher ROI for their AI products. And with the type of industries that they sell into, it comes as no surprise then that retail trade and online and social media industries are their most profitable customers. This is followed by finance and insurance companies that use plenty of AI applications in their marketing operations. However, the application of AI in marketing among companies in industries such as utilities, wholesale trade and public administration is slower compared to the pace in social media and eCommerce.

Is It the Right Time for the Adoption of AI in Marketing?

Before you decide on plunging into the AI and marketing hype, consider the two prerequisites for utilizing AI in your marketing efforts. First, it is necessary that your business has digitized, trackable marketing and sales processes. You can’t drive a car without fuel, and so is AI in marketing without data. Robust data is a primary indicator of how well AI is to be an immediate part of your marketing process. It should also be digitally trackable to generate information and to differentiate your business’ “wins” from “losses.” Without digitized, trackable data, your efforts of using machine learning will only work at cross-purposes. Think of how Accenture and IBM are able to perform very well in their marketing analytics versus that of a startup that doesn’t have the massive amount of data that these tech giants have acquired. Second, an in-house AI expert or data scientist is required before adopting AI in marketing. While vendors that offer marketing applications make it sound so easy to get into the know of their products, the reality is that your business will be all balled up running your system like clockwork without someone who has a genuine data science experience.


Given the current state of AI in marketing, businesses such as large, tech-savvy eCommerce or online media firms try to harness this technology in many ways from understanding different buying persona to creating automated messages. However, AI in marketing for small and medium businesses is most likely to be not profitable right now and won’t likely get them on the good side of the market. This is because only the big players can test the potential of AI in marketing since they can leverage a good mix of robust data infrastructure and in-house machine learning experts. However, there is still a huge potential in this field. I offer a new litmus test to determine the best time for your business to jump into the AI realm:
“Research companies that offer similar products and services to yoursbut that are five to ten times larger. When you find strong evidence that larger, similar firms are gaining strong ROI on AI marketing efforts, it’s time to seriously consider adopting the technology.”
If your current business passes this test, then you can proceed with planning AI in your marketing future. However, if it doesn’t, I advise against doing so given the larger risk that you will be taking.   Image credit: IDG Enterprise]]>