Consider these two sentences: The fox is coming for the chickens. The seeds are coming for your yard. In each case the word “for” is doing very different work: In one it implies a negative, in the other a benefit.
Now try: The robots are coming for our jobs. Again, you could interpret this either way—and people do, depending on their points of view. In marketing, for instance, the robots are indeed coming—to help. And they’re bringing artificial intelligence with them.
AI has been called a cognitive prosthetic—technology that combines large data sets, algorithms and powerful computing to produce outcomes that mimic human thinking, but at speeds and volumes we can’t match. In marketing, a human brand representative might give an individual customer a responsive, personal experience; AI can parse data on millions of customers to deliver a personalized (if automated) experience to each. According to one report, organizations reference an average of 28 such data sources. When AI shoulders that load, it frees us for things only humans can do, like employing nuance, creativity and imagination.
Yet the benefits of AI to marketers go beyond crunching big data at speed and volume. In fact, two recent trends suggest the technology can be useful in ways specific to marketing—the decline of the cookie and the rise of emotion data.
Old cues, new connections
For decades, third-party cookies turned consumers into self-aggregators of valuable marketing data—often without realizing it. But consumers have gotten more sophisticated and are demanding more control of both their information and when it changes hands. So cookies are on the way out. Given this shift, how can brands maintain connections with people?
One way is to establish an owned solution that sorts a consumer’s myriad data points to create personalized experiences. So far so good. But while this may be easy to do for 10 customers, what happens when you have 10 million? AI to the rescue.
The kind of data available to marketers is shifting as well. The new frontier is emotion.
Our emotions have always been central to the connection we feel to brands; Deloitte research shows 60 percent of consumers use emotional language to describe their favorite brand connections, and 70 percent expect feedback as part of a brand relationship.
Now advances in cognitive software have brought these emotions into the digital sphere. AI has the growing capability to track emotional cues and detect behavioral patterns that can reveal—and even prompt—human emotional responses. What human researchers have learned, AI can apply in real time. For example, certain colors are perceived differently according to a person’s mood. Faster clicks may signify urgency and a streamlined response; slower may signal someone has time to engage. Scaling these kinds of personalized customer insights was once the stuff of science fiction, but not anymore. They exist today to help marketers and brands better understand and connect to their customers with efficiency and empathy.
Tips for effectiveness
CMOs who are already convinced of AI’s potential value and plan to explore it further might consider these points:
- Make the business case and demonstrate value.
Capabilities can be alluring, but results justify investments so be ready to show the value AI brings to marketing. Then take a step back and use the same approach to demonstrate that the marketing function will deliver more value to the broader organization when it adds the power of AI.
- Deploy and scale AI in a measured way.
As with any important new tool, there’s wisdom in taking measured steps. Find small places to pilot AI in marketing initiatives, such as content personalization and predictive ordering. Then follow an iterative pattern of trust, test, tune. Trust your data; test your AI algorithms to make sure your inputs, outputs and actions are in line with your strategy; and tune your AI engine so it can almost run on its own. Then, as you expand your use of AI, make sure to stay committed to your measurable goals.
- Be careful of human bias.
Never forget: When it comes to machine learning, we’re behind the learning part too. This means we need to be careful about building our own implicit biases into AI systems in the ways we code them, feed them data and interpret the insights they generate. Bias doesn’t have to mean prejudice. For instance, we humans are particularly susceptible to confirmation bias—a tendency to let what we already know to be “true” shape how we view new information. This explains why MIT students built a robot with humanlike arms to solve a Rubik’s Cube before realizing spikes might do a better job. (And they did. The spiky-armed version solved the puzzle in a record-breaking 0.38 seconds). AI is just as impartial in its responses—it can search for insights within the limits of our biases or without them.
Yes, the robots are here. ‘For’ us.
Here’s a bias: No machine can ever contribute to what’s essentially a human customer experience. But consider the last time a human got your name wrong on a coffee cup. Then imagine that interaction multiplied millions of times.
With a little research, marketers at almost any scale, in almost any industry, will find they have more to gain from AI than they once thought possible. Today, both B2C and B2B companies are using AI to support their marketing efforts—those experiences can be a school for new adopters. It may be the only missing element is an experienced adviser.
AI can carry our human aims beyond our human capabilities by doing away with our limiting factors—and gifting us with the time to shape strategy, messaging and brand purpose. That’s why the robots are coming, in part: to clear the way for marketers to paradoxically create more human connections, more meaningfully, more quickly, than we can alone.
Sure, the intelligence is artificial. But the potential rewards are real.