Predictive analytics is bringing forth a new age in marketing, where marketers can effectively model and learn from customer behaviors (not to mention better qualifying leads). But as predictive analytics algorithms continue improving, is it possible that they’ll take over the entire industry, including the human jobs that predated them?

How Predictive Analytics Could Replace Human Jobs

Predictive analytics is already superior to its human counterparts in the following ways:

  • Data collection. When it comes to collecting and using data, humans have a historically terrible track record. We make mistakes in how we collect the data (including choosing bad sample sizes), how we record the data (misreporting numbers), and how we interpret the data (using unreliable analytics methods). Algorithms weed out these “bad” practices and provide a reliable, objective basis for collecting and using data that extends beyond human abilities.
  • Understanding customer behaviors. You may “know” your demographics’ main motivations, but can you predict how they’re going to feel about your product in the future, or how they’ll behave in response to a pricing change? Predictive analytics can do this far more efficiently than human estimations.
  • Reducing potential outcomes to numbers. Algorithms are also better at reducing vast swaths of information down to easily understandable numbers, including probability models.

Where Predictive Analytics Falls Short

However, there are still some areas where predictive analytics falls short:

  • Intuition and creativity. The best, eye-catching marketing materials are the ones inspired by human creativity. While deep learning is enabling machines to “think” like humans and come up with novel ideas of their own, for the moment, predictive analytics algorithms can only work with the data they’re given for a specific application. Human minds are better at combining abstract ideas and coming up with truly original concepts.
  • Personality. No matter how mathematical you try to make your equations, people are still going to prefer brands that show realistic, human-like personality traits. Predictive analytics can tell you what customers like to see, but only human beings can communicate in a personal, engaging way.
  • Actionable decisions. All the numbers generated by predictive analytics are valuable, but only when put in context. Algorithms still rely on human beings to consider the probabilities, come up with inventive responses to newly revealed trends, and ultimately direct what strategies a business should use next.

How to Use Predictive Analytics

There are many valuable ways to use predictive analytics in your company, so long as you realize the fundamental advantages and limitations of this type of software. It can’t replace human marketers, but you can benefit from it by following these strategies:

  • Choose the right tools. There are many forms of predictive analytics software on the market, but not all of them are equally effective. Do your research, and go with a platform with a history of success and good reviews, such as SAP’s predictive analytics platforms.
  • Employ the best human analysts. Even the best analytics software still needs an interpreter, director, and supervisor—a human analyst to ensure proper data collection and come up with practical takeaways for the resulting insights.
  • Don’t reduce everything to numbers. For the most part, objective analyses are superior to subjective intuition or guesses. However, not everything can be easily quantified; don’t get caught up in trying to transform your marketing into a game of pure numbers.

Predictive analytics is here to stay, and it is unlikely to ever fully replace the need for human marketers and analysts. Still, it’s a powerful tool that deserves a place in your organization, so don’t underestimate its potential.

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