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Machine learning and artificial intelligence are among the most frequently used buzzwords in marketing today.
Just try to find a marketing conference that doesn’t have A.I. high on the list of topics — it’s like trying to read The Wall Street Journal without finding a single mention of cryptocurrency. And considering that machine learning is what Cambridge Analytica allegedly used to target Facebook users, you’ve been hearing about it in The Wall Street Journal, too.
At McGuffin, we strive for a solid understanding of what’s next to come in our industry, and our quarterly breakfast series, McGuffin Mornings, serves as a forum to learn more about prevailing marketing trends. For our latest event, we invited Lauren Nelson, Partner Lead at Google, Inc., to talk to our group about the shift to machine learning and what it means for marketers.
Here’s a brief recap of her most important takeaways.
Machine learning is a method of artificial intelligence where algorithms are created to autonomously learn from examples and detect patterns that lead to reasoning. It’s a monumental shift from explicit rule-based programming, which relied on human inputs for every decision made and could only create outputs based on what had been programmed into it. If you think about it in terms of your thermostat, previously used rule-based programming would be a traditional thermostat that you manually program based on your schedule each day, and machine learning A.I. would be a smart thermostat that collects data on when you are home and what temperatures you prefer, and then automatically updates the program based on your preferences and habits.
Google sees everything it does through the lens of machine learning. That includes understanding and imitating your personality to create both personal and professional Gmail auto replies. That includes Google Maps observing the length, speed and surroundings of your commute to improve it. That includes offering photo tagging suggestions for people you often “say cheese” with. Machine learning is transforming marketing to be timelier and more seamless in many applications.
More than you think. As technology advances at an exponential rate, customers have quickly found themselves more reliant on automated experiences. Machine learning systems like Google Home and Amazon Alexa have quickly progressed from frivolous purchases to must-have tech within the home. With these experiences so rapidly becoming part of our everyday lives, it’s important for marketers to pay close attention to how the customer journey is affected by machine learning and marketing in tandem, and how these touchpoints affect brand experiences and conversion.
Per Google, machine learning could get us one step closer to one of advertising’s most sought-after goals: relevance at scale. We’ve seen an increasing demand for programmatic media and custom creative content that capitalizes on connecting with consumers when and where they are in the consideration process.
Imagine having the ability to open an umbrella pop-up shop under the canopy of a train station at the beginning of an unexpected rainstorm. Lauren tells us that this is the type of power that machine learning is giving marketing and sales. In fact, McDonald’s Japan teamed up with Google’s DoubleClick to create a real-time data driven creative campaign based on weather patterns, serving up ads for iced coffees on hot summer days and popular new hamburgers on rainy weather nights. Ok, so, machine learning and marketing are giving us endless opportunities. But where should my brand start?
Machine learning from Google and other companies is most powerful when combined with your customer data and learnings about your product or service. So a good place to start using machine learning is by implementing a campaign focused on the customers you’re most familiar with. The more insights you can bring to the table, the better your targeting will be.
As much or as little as you’re ready to commit to. The more specific you get with the data, the better your results will be, but that doesn’t mean you have to dive deep into nitty-gritty customer data on your first campaign. Using programmatic media to deliver more relevant creative is where we see many clients starting out.
Here at McGuffin, we’ve created very successful campaigns with programmatic media partners focused on omni-channel, contextual personalization of ads. Using a simple system (and a whole lot of organization), we were able to deploy over 180 creative executions of the same ads. Different copy and imagery were served up based on targeted A.I. metrics. What results from the campaign is a better experience for both the brand and the consumer, and that relevance leads to higher engagement and stronger performance.
We’re seeing financial marketers like HSBC use A.I. to personalize its rewards programs using customer data and preferences to promote offerings that are most relevant to their clients. While this may seem invasive on the back end of how it works, it ultimately results in the customer feeling better understood by their financial institution. And when dealing with something as personal as money, that added sense of customization goes a long way.
Not even the tip of the iceberg. The paradigm shift to machine learning is only getting started. What we can do with the technology today represents only a fraction of what we’ll be able to do with it in the future. It’s best to jump on the machine learning bandwagon early and often, or risk getting left behind.
McGuffin Mornings is a quarterly breakfast series hosted by McGuffin Creative Group covering topics focused on trends and insights in marketing, advertising and creative, it serves as a forum for savvy marketers to connect and sharpen skills in our rapidly changing industry. If you’d like to know about future McGuffin Mornings events, you can sign up right here. We’d love to see you there.