Machine Learning Marketing Report

Machine learning. Is there anything marketers are more excited about right now? While machine learning marketing applications are still a rarity for businesses outside of the enterprise level, the folks over at Executive Consensus (EC) think that’s going to change in a big way over the next few years.

In their latest expert consensus, Machine Learning in Marketing - Expert Consensus of 51 Executives and Startups , they polled executives at more than 50 companies, specializing in the fields of both AI and marketing. Their goal was to “determine the applications of machine learning and AI that are driving strong business value now, as well as the applications that would make the biggest difference in the next five years.”

Respondent Background

Most of the companies surveyed were small, with 70% clocking in at fewer than 50 employees, and primary company revenues between $0-$500k and $1-$5M. The main products and services these companies offer are analytics (26%) and targeting/segmentation (24%). And entry level price points for most respondents are under $999 (41%) or between $1k-$5k (27%).

EC also identified the primary business goals of participating companies. “Generating new revenue,” “retaining existing customers,” and “acquiring new customers” were the top three goals, leading EC to presume that that the participating companies were targeting marketing departments within their client companies. Additionally, 80% of sample companies focus on eCommerce and retail verticals, while 60% focus on online and social media companies.

Selling AI and Machine Learning

When asked about the challenges of selling AI marketing tech, respondents identified “demystifying the technology” as the biggest hurdle, garnering it almost as many responses as the next three challenges combined. “Low data quality” and “attribution is difficult” rounded out the top three here.

While EC acknowledged that “it’s hard to explain” could be viewed as an excuse for underdeveloped sales or marketing skill sets, they pointed out that AI is still viewed as something for “early adopters” and that explaining such advanced technologies is challenging for even the most experienced salespeople and marketers. As AI continues to grow in popularity and use, however, EC sees these conversations getting easier and less intimidating.

Current and Five-Year ROI

So what does the current and five-year ROI forecast look like? EC’s sample companies posture that the areas of opportunity for AI in marketing will not shift much. eCommerce and online/social media verticals maintained the top two spots, with direct-to-consumer industries benefiting the most from AI marketing.

When it comes to which businesses have the most potential for value with AI in marketing, digital media and eCommerce companies came in first, with SaaS and social media businesses closing in on third place. EC guesses that the latter two rank lower because “such businesses are less common than the first two.” Anyone can create an ad-driven site or an eCommerce store, but few people can do it successfully.

The research sample also showed a clear leaning towards businesses that “‘live and die’ quantifiable digital interactions.” Specifically those with the kind of data that can train machine learning models and improve performance over time. B2B physical businesses and service firms also ranked low, as they have much less quantifiable transaction data and their sales rely heavily on client interactions.

When it comes to current profit potential in AI marketing applications, “search” was voted the most profitable. And, interestingly enough, in a content-driven climate “segmentation/targeting” outranked “content generation” significantly in profit potential, though EC chalks this up to the fact that more of their sample companies were working on the former.

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So what did the respondents think about the five-year profit potential of AI marketing applications? I thought you’d never ask. The responses for this section aligned with the value propositions given by the respondent companies. “Recommendation/personalization” took top honors, and ranked highly as a core value proposition.

However, while “analytics” was the number one value proposition reported, analytics-related apps like “decision support” and “forecasting” didn’t make their way onto the data chart. EC guesses that this is because the companies they surveyed are developing analytics technologies specific to their needs.

When Will Machine Learning Be a Crucial Part of Every Business?

Finally, the sample companies made their adoption predictions on when AI/ML would be necessary additions to companies of all sizes and verticals. 2020 was the year that 17 respondents chose for universal integration. Only time will tell, but until then, the results of this survey would encourage us all to brush up on emerging trends, adoption, and inevitable global takeover of machine learning.