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Since the invention of mass media, the primary focus of marketing has arguably been to increase its level of personalization. Marketers constantly seek more targeted audiences and strive to deliver messages that speak more directly to them. So it’s no surprise that AI and machine learning — with their ability to predict consumer behavior and make personalized recommendations — have captured the attention of the marketing world. But the elephant in the room is that advances have far outpaced most marketers’ ability to harness them.
Unfortunately, this inability to personalize the customer experience is a huge missed opportunity. Customers now expect a tailored experience, including customized recommendations and a personal touch. And they are willing to reward companies who provide it.
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But there is a silver lining. Right now, AI-driven personalization is not just a challenge for some companies, it’s a challenge for most. This means that the opportunity has never been better for forward-thinking marketers to use AI to drive a competitive advantage.
The good news is that help is already here. Cloud providers like Microsoft, Google, and Amazon are making huge investments in machine learning, including teaching us how to use it. These providers are betting that AI will drive the consumption of cloud services. Similarly, marketing technology vendors are starting to bake machine learning into their products. So, although personalization is not quite turnkey yet, the opportunity has never been better.
Fortunately, you don’t need to be an expert to start taking advantage of AI in your marketing. The key is to start doing something, anything to build up your marketing org’s working knowledge of AI. Start small, keep it simple, measure your results, and maximize your return on learning. Below are four simple ways to get started.
Traditionally, A/B testing tools like Optimizely and Adobe Target were used to test variations of page design. More recently, these vendors have beefed up their offerings to provide always-on personalization for both websites and mobile apps. This route to personalization offers three big advantages for marketers. First, it’s easy to connect these tools to customer segments defined in analytics platforms. And by using these behavior-based segments, you bypass the need for large, IT-driven data integration projects altogether.
The second advantage is that most have rich WYSIWYG editors that give marketers the ability to update their sites or apps directly. This means that marketers can publish different messages to different segments themselves, without IT support.
Third, if you make multiple variations of creative for each segment, A/B testing tools can use machine learning algorithms to find the optimal variation for each segment while the campaign is running.
The ultimate personal experience is simply a conversation between your customer and a knowledgeable, friendly person within your organization. However, with the rise of AI, it’s now possible to simulate a one-on-one dialog with digital conversational agents via chatbots or voice-activated applications. For example, using existing chatbot platforms like Wit.ai (Facebook), Luis (Microsoft), or Chatfuel, you can build a chatbot that answers your customers’ questions. Even more interesting, they can integrate directly with existing messaging platforms like Slack, Facebook Messenger, Kik, WeChat, and even text messaging, which means you can interact with your customers directly via the apps they already have on their phone.
Voice-activated apps like Amazon Alexa skills extend the concept of digital dialog even further by allowing a natural voice conversation to take place between your customer and your brand.
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Perhaps the easiest way to start taking advantage is simply to select partners that are serious about machine learning and are building AI into their platforms. While this may not always be the cheapest option, it is certainly the path of least resistance. Three of the leaders in martech AI right now are Salesforce, HubSpot, and Adobe. Salesforce has made a dizzying array of AI-related acquisitions, culminating in the roll-out of its branded AI technology, Einstein, which includes a host of AI-powered functionality.
HubSpot has also been investing heavily, with a strong focus on content and digital analytics. Its recent acquisition of chatbot platform Motion.ai is an example of how the company continues to adapt to emerging marketing trends.
But the 800-pound gorilla of martech is still Adobe. Personalization and the rich use of customer data have been at the core of Adobe’s marketing cloud. More recently, Adobe enhanced its core platform with its own AI technology, Sensei, which fuels a range of machine learning functionality under the hood.
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But you don’t need to roll out an enterprise marketing platform to start doing personalization. A simple approach is to start building your own DIY personalized digital experiences using off-the-shelf machine learning APIs.
Cloud providers have abstracted the complex, PhD-level mathematics that underlies most machine learning algorithms into intelligent APIs that your typical developer can use.
Microsoft, one of the leaders in this space, has a suite of more than 30 machine learning APIs within its Cognitive Services offering. These APIs handle everything from computer vision to natural language processing to production recommendations. Its Custom Decision Service API, for example, uses reinforcement learning to study customers’ preferences and provide personalized content.
Similarly, Amazon’s AWS provides machine learning APIs for image recognition, language recognition, and generating lifelike speech, enabling you to literally speak to your customers digitally. Although Amazon’s suite of AI-powered APIs is not as broad as Microsoft’s, it has the advantage of Amazon’s deep, real-world, working knowledge of AI gleaned from its ecommerce platform behemoth.
There are many different options available to marketers to start incorporating AI and personalization into their digital experiences. And while the rapid rise of AI in marketing can feel a bit daunting, it’s critical to start dipping your toe in the water now to begin building up your organization’s experience with AI. A small investment today will yield a large competitive advantage tomorrow as your customers start gravitating to your digital ecosystem because, well, you just seem to “get them” more than the competition.
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