How AI & Automated Marketing Have Changed the Game

content marketing, Marketing & Advertising Technology, Other

June 26, 2018 by

In the last decade, marketing automation has transformed the business world in radical ways as it creeps into every stage of a B2B or B2C sales funnel. Customer Relationship Management (CRM) tools have revolutionized prospect management, programmatic advertising has boosted ROI on ad campaigns, and email marketing apps like MailChimp have changed the way that businesses interact with customers.

But in 2018, marketing automation is taking the next step forward in refurnishing the CMO’s digital toolkit by playing off developments in Artificial Intelligence and Machine Learning algorithms. Today, there is no digital marketing solution that can’t benefit from AI, and according to a recent report by Salesforce, “High performers are 2.2 times more likely to use AI in their marketing campaigns than under-performers.”

In this article, we will explore just a few of the high-profile solutions that AI has either produced or augmented. Let’s jump right in -

Data Integration

As the number of tools that marketers use to collect and collate data grows exponentially every passing year, the need for an integration mechanism has never been more pressing. Unsurprisingly, AI is stepping in as a great unifier for disparate information streams, bringing together insights that are easy for marketers to overlook. As pointed out in a recent Forbes article, "AI is needed to help integrate across tools, datasets and platforms."

According to research performed by chiefmartec, in 2017 the number of automated solutions available to marketers had increased by 40% from the previous year. Between 2011 and 2017 the number of these solutions has increased from 150 to 5000.

Not only can AI bring these data sources together, but will also work to build unified analyses based on seemingly unrelated data silos. Prior to the advent of AI, Marketing Automation tools could focus on email campaign optimization; after AI, email campaigns can be influenced from data across the company, including site behaviors, social media activity, and more.

This level of analysis is impossible for traditional algorithms, since the connection between two quants from different aspects of a project can be completely inscrutable to human reason. By bringing them together, AI will help marketers to see the big picture more accurately, with less effort.

Decision Making

AI is well equipped to help businesses in making difficult or repetitive decisions, freeing up time for other tasks. In the past, automated marketing was already helping marketers with certain decisions, such as which markets to tap. For B2B businesses, lead scoring has helped to select ideal contacts for developing business relationships.

Moving forward, AI will be able to recommend or even make decisions on its own, in more complex and difficult areas. AI Researcher Ajay Agrawal has worked with colleagues from various universities to develop a simple structure with application in multiple domains - including home security, business, and politics - which will enable companies to automate complex decision making processes from the ground up.

As Amazon CEO Jeff Bezos argues, “Basically, there’s no institution in the world that cannot be improved with machine learning.” AI has already bested human performance in multiple fields, including the diagnosis of certain illnesses, the maintenance of hedge fund portfolios, and even in playing complex strategy games like Go. In an increasingly competitive marketplace, drawing on the power of AI will enable businesses to utilize resources more efficiently.

Lead Generation

Marketing automation has gone a long way in streamlining lead generation for both small and large businesses. By sifting through simple signals in potential prospects on social media and other sources, lead-finding tools are able to identify ideal customers for B2C businesses, and even partners for B2B.

But so far, this analysis often depends on simple, publicly available information that makes sense to human beings. For instance, automation tools may suggest prospects for a shoe company based on whether they “liked” shoe brands on a social media profile.

AI can do much better by looking at information that previous tools could never process. Not only do humans tend to over-emphasize certain parameters and overlook others, but miss other signals that could correlate with an excellent prospect. For instance, software like Netra can learn about a prospect from images they share, while CaliberMind processes the language in social media posts to build a better understanding of individuals.

Virtual Assistants

Marketing automation in the form of CRM has done much to scale conversation with individual clients, track conversations, and neatly organize template responses for stock issues. Now, AI may go the rest of the way by having many of these conversations automatically.

In fact, this is already happening throughout the business world in the form of virtual assistants. A simple form of virtual assistant that appears throughout social media and homepages is the “chatbot”; generally chatbots are able to handle basic Q&A, place orders, and retrieve information.

Going forward, virtual assistants will become more versatile, as they help out with tasks on the business side of things. A race is currently underway to optimize the workflow of marketing professionals with assistants that can set up meetings, organize workday calendars, and prioritize tasks automatically. Some of these solutions are already available, such as x.ia, or the new Duplex feature that will soon be available through Google Assistant.

Automated Copywriting

The ability of AI to help businesses in correspondence demonstrates the "natural language" capacities of artificial intelligence. This will eventually enable AI to help produce marketing copy optimized for individuals. Automated Insights, a company actively working in this domain, aims to “produce personalized narratives at any scale – stories that are completely tailored to each reader and sound like a person wrote each one individually”.

Much like programmatic advertising already ensures that ads are seen by the most suitable prospects, automated copywriting can even ensure that the ad is customized down to individual words and sentences, ensuring the maximum possible value for each impression.

This ability to write natural copy will extend at least in part to content, such as blog posts, and is already being used to produce white papers. Amazingly, Gartner reports that by the end of the 2018, 20% of business content will be authored by machines

Getting Started

As this article seeks to establish, the promise of AI is not pie-in-the-sky. Many of the benefits it brings to marketers have already been deployed in the real world, and many more are just on the horizon. If past precedent is anything to go by, there is little point in waiting: Salesforce has conclusively proven that companies investing in AI outperform those who don’t by 200%.

To learn more about how AI is changing the marketing landscape, check out our free webinar The Rise of the Algorithmic CMO with Amit Shah.

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