Since sci-fi novels began predicting artificial intelligence back in the 1950’s and 1960’s, people have worried that machines are going to eventually take over everyone’s jobs. At least one university researcher believes that half of all human jobs will be taken by machines within the next three decades. Machines have already stepped up to positions in manufacturing, retail cashiering, and even highly specialized professional positions like surgery and creative work like writing.
But marketers who worry that machines will take over their jobs can relax — at least for awhile. As it happens, computers and people are good at different things, and computers make a brilliant accompaniment to human marketers. While humans are much better at interacting with customers and nurturing leads, computers far surpass their skills in immediate big data processing and analytics, a very necessary component of big data marketing.
Here’s how human marketers and machine learning are dancing a brilliant tango together.
Machine Learning Helps Marketers Evaluate Data from Many Sources
When marketers sit down to draft marketing messages, they need intelligence from numerous disparate sources. Today’s big data marketing compiles information from email campaigns, lead generation web forms, social media data, customer-facing mobile apps, and more. Humans are really good at looking at the data and creating the right messages to speak to those audiences. But they can’t do so without the machines making sense of the data through highly specialized and often extremely fast analytical processes. Successful big data marketing requires both.
Machine Learning Means Uber Fast Data Processing
Much of today’s big data marketing, especially on the digital front, requires processing and analytics in real time, or very nearly real time. This includes things like product recommendations, targeted ad placement based on a user’s current searches, and email delivery of a marketing message based on a user’s behavior on your website.
Humans can’t act this quickly. Computers can. When computers deliver this ultra speedy response to a potential customer’s online behavior, marketers can follow up with more personalized, human contact during the lead nurturing process. It’s the ultimate one-two punch of digitized personalization and humanized personalization.
Machine Learning Helps Marketers Learn from History
Another thing that humans don’t do well is analyze large bodies of historical data to find hidden patterns and correlations. For example, for years, retail and grocery stores stocked their shelves before major storms with the standard supplies — milk, bread, flashlights, etc. As it happens, consumers actually stock up on rather unexpected things, as well. Like strawberry Pop Tarts.
Big data marketing means processing and analyzing your historical data on how leads progress through your marketing funnel; historical sales figures before, during, and after a recession; inventory fluctuations; customer lifetime values; and many other variables to determine where the strawberry Pop Tarts of your marketing cycles exist. After the computer finds these hidden patterns and correlations, your human marketers can craft brilliant strategies for generating leads and converting those leads to paying customers.
ReachForce helps marketers increase revenue contribution by solving some of their toughest data management problems. We understand the challenges of results-driven marketers and provide solutions to make initiatives like marketing automation, personalization and predictive marketing better. Whether you have an acute pain to solve today or prefer to grow your capabilities over time, ReachForce can unify, clean and enrich prospect and customer lifecycle data in your business, and do it at your own pace.