Artificial intelligence (AI) and machine learning are redefining the technological landscape as we know it. From digital assistants to self-driving cars, what was once science fiction has now become reality. While technological advances are nothing new to marketers – the arrival of TV dawned an era of true mass advertising, internet and mobile ushered in a new level of accessibility, and so on – AI now represents the next big shift for the marketing and advertising industry.
In this episode of The Marketing Remix, Ron Hadler, Sr. Director of Marketing Technology, and John Faris, President of Red Door Interactive, break down AI and machine learning, and how they're changing the way consumers interact with information, technology, and brands.
How close are we to the era where AI matters for marketing?
Whether we're doing a search, clicking on an ad, or talking to a voice assistant, AI is all around us and marketers need to be paying attention to the influence of AI.
What is “artificial intelligence” (AI) versus “machine learning”? Are those terms interchangeable?
There are 2 types of AI:
General AI
This is what normally comes to mind when thinking about AI, categorized by a human level of intelligence with the distinct ability to reason.
Narrow AI
This is where machine learning really falls and what is really in play right now. This type of AI is highly specialized in a limited context and currently applied in features like tagging of content, predictive analytics, and programmatic ads. Machine learning is taking the data you've been gathering and applying algorithms for automatic decisions. There are 2 phases to machine learning specifcally:
- The data model: The machine ingests the data, creates the model, and learns how to predict.
- Interactions: The machine puts the model in production (I.e. a chatbot answering questions).
What type of AI solutions should marketers be looking for right now?
Marketers should look into taking advantage of third party platforms with AI capabilities. Leveraging Facebook and Google platforms is an easy place to start, as they already have AI capabilities baked into their functionality. Then look toward layering on data attribution models and moving to something that's more dynamic. The biggest shift for marketers will be moving away from manual tweaks on campaigns or websites and relying on these models to do this.
What kind of impact(s) is this technology having on consumer demand?
Personalization will ultimately create a shift in demand toward those that leverage AI, and as machines continue to learn, the personalization will become more accurate. It's relevance at scale, essentially allowing us to customize content toward visitors. However, the biggest challenge will be the customization of creative, as robots can mimic well, but cannot create concepts the way humans can.
What type of technological considerations should a brand consider in order to take advantage of AI?
It's all about the content workflow. A good content management system is key, allowing you to centralize your content and then spread it out. Categories and tags on content allows AI to personalize and serve the right content to the right user.
What questions should marketers be asking and who should they be talking to within their organization if they want to incorporate AI?
A marketing technology contact within your organization will likely be the best person to talk with. The average enterprise has over 90 different platforms they are interacting with, so odds are high that some are likely already using AI. If you have tools, be sure that you are leveraging them to their full potential. The second thing to really know is what business questions you really need to address. Marketers are often looking to improve conversion rates, which AI can improve so much faster at scale than a human can.
What are some platforms that marketers may not realize they are not taking full advantage of?
Email. We've been talking about marketing automation for years but it's still very rules-based. You can actually leverage machine learning to make automation more dynamic, ingesting the data and creating a model to best reach the consumer. Business Intelligence tools likely also have machine learning capabilities and are able to do that deep analysis marketers need. Before jumping into this, make sure your data is as accurate as possible (without duplicates, consolidated, etc.).
To learn more, join us at our next Speaker Series, AI: The Future of Customer Acquisition, on August 21 from 8:30-10:30am in Downtown San Diego.
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