Most of the talk about current use of artificial intelligence (AI) in marketing cites what the 4 Horsemen are doing or likely doing. Google, Facebook, Apple and Amazon have digital, data and automation at the heart of their businesses. They have the skills and the culture to make the application of machine learning and artificial intelligence a core competency.
Meanwhile, many marketers still struggle just to get their customer data source in order never mind speculating on how AI might improve the customer experience and/or the profitability of these customers. The hype curve of AI creates this nervous energy for marketers. To not do anything in AI seems wrong. On the other hand, to leap in expecting it to solve big, hairy 2018 problems also seems naïve.
I would recommend creating a simple ‘road map of exploration.’ Andy Betts (@andybetts1) has a useful post and diagram (above) counselling CMO’s to start planning in 2018. For once, it’s okay to start learning and exploring vs. jumping into action. I have a ‘bias-for-action’ like most marketers. We want to learn by doing. In this case, I want to pick and choose the pilots and proof-of-concepts (PoCs) while not derailing my marketing and customer service operations who already have a pretty full agenda next year. I will start by defining use cases where AI may have a positive effect on marketing.
Five Use Cases for AI in Marketing
Show the right, next call-to-action – Are people looking for a home-plus-valuables insurance quote? Trying to get answers about coverages in the weeks leading to an insurance need? Winterizing their home before jetting off to Florida for the season? These are pretty simple states but often hard to detect amongst the unknown visitors to your digital properties. Knowing the next right action to suggest and guide them is hard.
Propensity modeling used to be the answer. Defined as “a statistical scorecard that is used to predict the behaviour of your customer or prospect base,” propensity modeling works best when you know a bunch about the person. Think rich customer databases vs. a few Web clicks from strangers on your Web site.
Would you rather have a “scorecard” or a really smart robot (i.e. AI)? Imagine paying attention to the patterns of visitors to your site and all of the content they consume. Imagine if you could reliably predict/understand what they are trying to accomplish and you were able to deliver just the right calls-to-action on their screen. No more junking up their view with every possible choice they may consider. No more agonizing over Web site navigation models. With AI, you could understand what they are after and just give it to them.
Identify more accurate and actionable “look-a-likes” – Finding more prospects that look like your most valued customers and then selling them your product is generally a good thing. Most of the social networks have offered look-a-like audiences for a few years now. And given their facility with data and AI, these models will get better and better (and be worth more and more to advertisers).
As brands build their own audience pools for advertising, we need to find ways to use machine-learning and AI to identify more precise matches for our most valued customer. Just finding people in the same demographic or even the same interests as your current customer base isn’t enough. What if you could find more or less perfect matches for your top 20% most valued customers? And what if you could overcome the problem of “diminishing audiences” (when your target is so narrow you cannot cost effectively market to them) and engage them with just the right offers? AI could make that possible.
Automate market research and performance insights – We need a steady flow of timely insights about our customers (and prospects) and the performance of our marketing efforts. Currently, this process is so manual my bones ache thinking about it. If I think about all of the effort we are spending just automating a dashboard –a visualization of performance data, I have to laugh.
I want my performance AI to find patterns I would never recognize and draw insightful connections that help me market today and tomorrow.
When will my little machine-learning robot sift through all of the online panel data on a particular group of customer-types and reveal something I didn’t know to ask it for?
AI-generated content - I am less interested in teaching a robot to create a compelling article or video, than using AI to generate relevant content at a scale that is prohibitively expensive otherwise.
Let’s say you serve the small business market with a solution that lots of different business types could use. But small businesses want to buy a solution made for their business-type. If they are a dry cleaner they want a solution provider for dry cleaners. If they are a dog groomer or an art supply store, same thing. How can a solution provider create content for hundreds of small business types?
Discovering how AI can “learn” your existing content and then assemble industry-specific content to create something of value and relevance to the dog groomers and art supply store owners is the trick.
Solve customer problems conversationally – AI-driven chatbots are the most popular customer experience application judging by the number of companies offering chatbot solutions. Still, they remain in their infancy.
Get a computer to consume a “corpus” or body of data, teach it some lessons and “walla!” you have a way to quickly get personalized answers for customers and cut down on the overhead to deliver said answers. This is the type of solution that can serve both customers and prospects and will take sustained iteration and use to make very valuable.
These are just a few of the use cases on my road map of exploration in AI and machine learning. What’s on yours?
Good resources:
3 Ways AI Will Affect Marketing - Smart Insights
The CMO’s guide to AI’s marketing impact for 2018 - MarTech Today
How Will Artificial Intelligence Impact Digital Marketing in 2018? – NextWeb
8 Ways Intelligent Marketers Use Artificial Intelligence – Content Marketing Institute
10 Ways to Use Chatbots for Marketing and Sales – Entrepreneur
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