Hello everyone! So, I wrote a little eBook about AI—Artificial Intelligence–which is available on Amazon. Simply type “Pam Didner” or the name of the book “The Modern AI Marketer”. Download to your Kindle and check it out. Love to hear your feedback!
I mentioned in my last podcast that I wrote this book to help myself and others understand how AI fits into the field of Marketing. In the eBook, I mentioned six use cases. For today’s podcast, I want to talk about several use cases of AI for Marketing so that you can get a sense of how AI applies to Marketing.
So one specific case I want to share with everybody is the chatbot.
Whenever you go to the website you will see a little bot at the bottom of the right-hand corner, waving its hand and wanting to talk to you. So a lot of times I will try the chatbot and ask specific questions and see if they can answer them. And a lot of time they are not giving me the answer I need and I end up talking to real people, which is fine.
But there is one website which I go to all the time trying to find freelancers and it’s called Upwork. I don’t know if you use them, but if you are looking for freelancers check out that specific website. From time to time I need to change the milestones of my project or add additional money because my scope has changed. So I don’t know how to do some of that work and I will go to their support site and they have a little bot.
And I ask multiple times in terms of different questions. Interestingly enough, that specific bot always gives me the answer I’m looking for. I am very impressed in terms of how Upwork works with the bot and build the workflow and also help the bot understand and learn from the different questions that people are asking. So that’s a very good example in terms of AI use in Marketing and Communication, especially on the website.
Create a blog post or white paper
And another thing I want to share with you is in terms of content creation. For example, many publishing companies are using homegrown AI reporters. Bloomberg uses automated technology, Cyborg, to generate 1/3 of its financial news, especially company earnings reports.
The Washington Post used the home-grown AI content generation machines, Heliograf, to create content for coverage of the 2016 Summer Olympics Games and the 2016 Election. The media company has been using this AI-based content creator (aka robot reporter) to cover local-specific news which the publisher can’t afford to assign to full-time local reporters.
So they are using the robot reporters to actually pull the content and write the content based on the keywords and also pull from trusted sources.
This works well if you know the intended outcomes of your content. For most white papers, we know what we want to say, what information we want to emphasize, and what the call-to-action should be. Given that we know the predictive outcomes, it’s actually possible and plausible to use AI to create a first draft of the white paper for you.
If you write blog posts or long-form content, look into MarketerMuse, the AI Content Intelligence and Strategy Platform that will transform how you research, plan, and craft your content. I don’t believe that MarketMuse can write the content for you, but its capabilities can certainly help you to optimize and refine your content.
Support sales via account-based marketing
Another use case I want to share with you is basically supporting sales using account-based marketing. Sales and marketing have traditionally played two separate roles within an organization. Marketing focuses on the top of the funnel and drives demand, while sales are responsible for the bottom of the funnel and closing deals. I am a firm believer that marketing’s primary role is to support sales, in addition to driving demand and building brand equity.
There are many ways to support sales as a marketer. I talked about these extensively in my book, Effective Sales Enablement (if you are interested in purchasing the book, focus on chapters 4-7).
As AI is further embedded into sales and marketing tech tools, it naturally forces alignment and bi-directional communication between these two groups. This has further elevated the need to integrate marketing automation and CRM tools. Many companies do that.
One approach marketers can take to help sales is account-based marketing, which implements targeted campaigns and outreach to complement the sales account’s approach.
The purpose of ABM–account-based marketing–is to address the needs of individual target accounts. What AI can do is further enhance customization and prediction. To do that, it requires a pool of intelligence (aka data) at both the account and individual customer levels to tailor your ABM efforts.
One of the key desired outcomes for account-based marketing is to predict prospects’ intent or enhance propensity to buy. Predictive insights and intent data give you real-time intelligence on the accounts that are most likely to convert. This obviously streamlines account prioritization and fully optimizes your budget allocation. And there are several companies that can actually help you to do that.
One of them is DemandBase. It’s used by many enterprise customers and positions itself as the end-to-end ABM solutions from identifying accounts between sales and marketing, personalizing content and ad retargeting, to tracking the prospects’ ABM results. The AI is also embedded into a DemandBase solution. This is one tool that is used widely by many enterprises.
Another company is called Lattice Engines. They have an AI-powered platform that helps B2B marketers scale their account-based marketing programs across different channels. They connect and consolidate multiple internal and external data sources, and build audience segments using AI. So these are some of the companies and also use cases for account-based marketing.
Extend reach via media-buy
Obviously another use case example I want to share with you is a media buy. The media-buy landscape has changed dramatically with the Internet.
Ad placement is no longer a direct communication between advertisers and publishers using email or phones. Now you can buy and sell your ads inventory using an algorithm. You are bidding on the different inventory. So it’s basically created and managed by machines or AI. It plays a critical role in the media buying process.
There are many, many platforms that use the latest advancements in machine learning to optimize impressions in the real-time bidding process. Such as Albert, MediaMath Omnichannel, IBM Bid Optimizer, etc. Brands can use artificial intelligence to serve more relevant and targeted messages in the right places, at the right times, by providing data-driven insights.
These are different use cases of how AI is being used nowadays in the current marketing landscape.
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Before you leave, make sure to check out the previous podcast episodes.
In the meantime, be well and let’s connect again next week. Take care. Bye-bye!
 Jaclyn Peiser, the Rise of Robot Reporter, the New York Times, Feb. 5, 2019.
 Joe Keohane, What News-Writing Bots Mean for the Future of Journalism, February 16, 2017.