Hey, all you millennial marketers, take note--it wasn't always this easy. Literally, one recent high-school graduate ago (17-ish years), Google Adwords reps were knocking down doors at marketing firms across the United States, giving CEOs a sales pitch about keyword-rich content, closing face-to-face transactions, and returning a month later with graphs and charts galore to highlight new search results. Believe it or not, this was a model of efficiency at the time.
Buy keywords. 30 days. Graphs and charts. Rinse, repeat. Seriously--can you imagine?
In 2007, Google rolled out Adword Self-Service, giving any marketer with a credit card the power to choose their own keywords and receive real-time analytics. This revolutionary act put the power of an ad agency into marketers' hands, and the game changed forever. Today, predictive marketing companies are doing the exact same thing.
For all you non-marketing nerds, here is the rub: Predictive analytics is essentially a form of data-mining that extracts specific information from big data and uses it to identify trends and probabilities. Central to this process is, not surprisingly, the predictor, a variable that can be measured to predict future behavior (read: consumption patterns) for individuals or business entities (whatever your poison).
Super cool, right? Right. You probably feel much like the marketers of 2000 did when their Adwords rep showed up with charts and graphs at the end of the month.
Predictive analytics and big data alone are all that and a bag of chips, but for marketers, it's wildly inefficient, as they must manually navigate the data storm to discern the who, what, where and how with respect to sales prospects. Predictive marketing software is a breath of fresh air, then, allowing marketers to automate the process and control the data storm's lightning strikes, hitting sales prospects with the right message and the right time.
For instance, predictive marketing pioneer Mintigo utilizes data and machine learning to increase the marketing effectiveness throughout the customer journey (i.e., the stages a customer goes through when interacting with a particular company). Through automated nurturing, pre-determined customer journeys are transformed into predictive customer journeys. In other words, this automated process gives a single person the type of organized data insight that they would receive if they had terabytes of information and supercomputers analyzing it for them.
Simply put, predictive marketing software arms marketers with accurate insights into who is interested in buying a product or service, allowing them to devise highly personalized campaigns.
So what does this mean for marketers? Well, for starters, you can say goodbye to cold-calling. Predictive analytics software uses detailed analytics to create customer profiles with exhaustive information outlining behavior patterns, sales-conversion probabilities and current and likely future behaviors (Mintigo calls this "Customer DNA"). If you manage to jump on this train as it's leaving the station, you might even be able to achieve what's called "work/life balance." Can you imagine what life would be like if you didn't have to spend all your time poring over endless data points?
When it comes down to it, predictive marketing just makes everyone's life easier. For marketers, the cold, inhumane practice of bombarding customers with information they neither need nor want can finally come to an end. For customers, the intrusion of unwanted and misplaced solicitation of goods and services could perhaps feel more like a connection. It's not ground-breaking to say that people will engage with, discuss, and even buy something if they feel understood and respected.
Who knows, maybe big data actually builds a gateway to greater human connections in an age where face-to-face transactions seem so... 2000.