Are you conducting contextual marketing using Artificial Intelligence (AI) or just doing targeted programmed marketing? There’s a difference that many marketers don’t recognize. Programmatic marketing is based on if this/then that rules that are set up by a person, but AI-powered platforms base actions on patterns and insight from data. Don’t think of AI as a replacement for humans; we’re not in the movie iRobot. AI is a supplement for our abilities and knowledge.

Defining Artificial Intelligence

On a recent Social Business Engine podcast episode, Paul Roetzer, CEO of PR 20/20 and founder of the Marketing Artificial Intelligence Institute, described AI as “the umbrella of the tools and technologies that are designed to make machines smarter.” Machine learning sits below AI and is not a synonymous term. When a computer looks at past user behaviors to make suggestions, that is machine learning. Within machine learning is the subcategory deep learning.

Marketers understand that AI is becoming a major player, but according to OnBrand Magazine’s  State of Branding Report 2017, only a third of more than 500 “global brand managers and CMOs” plan to invest in AI-powered technologies this year. Instead, they’re planning their budgets for analytics, social media monitoring, and other previously effective tools.

The data that AI collects and analyzes is well above the data a marketer would garner from asking their prospect questions. As Roetzer points out, AI isn’t sci-fi or a fad. Now is the time to start to look at AI and understand how you can apply it. In this blog post let’s review some of the software that relies on AI and is available to marketers today.

AI-Powered MarTech

artificial intelligence in marketingAccording to a study by Demandbase, 80% of B2B marketing executives think that over the next five years B2B marketing will change entirely. The changes are starting now for both small businesses and large corporations. Educating yourself on what AI is and how you can implement it in your organization is a must. A few possible AI applications include targeting customers, making data backed actions, and streamlined reporting and analysis.

Machine learning recognizes patterns and their evolution within datasets. Programs such as Demandbase apply machine learning to increase sales pipeline by identifying prospects and focusing on Account-Based Marketing (ABM). Ceralytics uses AI for optimizing content marketing. The tool helps to clarify your audience’s needs and shows you what topics to cover.

You may have heard of IBM Watson from when it won Jeopardy a few years ago, or maybe over the winter holidays you discovered IBM Watson Trend; it predicted the best gifts for people based on AI. Watson Marketing solutions include analytics for customer experience, a content marketing hub, and strategizing of interactive design.

Albert is an AI Marketing Platform that can conduct campaigns “across all channels, paid and nonpaid, including email, mobile, social, search and display.” The longer the software is used, the more data is built up and the better decisions the machine can make. The software can help to save time and money, increase sales, create a better customer experience and so much more.

Recently Salesforce revealed that their AI layer, Einstein, is now going to be available to all of their clients. The AI is built directly into the platform and provides predictive insights to target new segments, optimize campaigns, enhance the customer experience and many other features.

These are just a handful of the marketing technologies available today that use Artificial Intelligence.

Applying AI in Your Organization

Now that you know a few examples of AI based marketing technology and what it can do, review your processes to see what can improve with the functionalities of AI. A few additional core functions AI can help are generating blog titles, automating emails, and scheduling posts on social media. If you’re unsure if the companies in your marketing stack are currently using AI, then ask. They may not have anything now, but it could be in the works.

Jumping into Machine Learning without clear intentions is not a good idea. It will be overwhelming and require countless working hours to set up objectives and then input the basic rules to get the system started. Focus on a particular problem that your brand has a lot of data on and clearly understands.

Don’t turn away from AI because you’re worried it will take your job. This science is meant to help marketers in their efforts, not replace them. Yes, your day to day operations will likely change as more tasks become automated, but this will open up more time for creativity in how you build relationships with customers.

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