Predictive marketing. Or perhaps predictive analytics? Nah, it’s all about machine learning. Data-driven marketing, you know, with big data and all that.

So what really is predictive marketing?

If we take a closer look at this terminology (side note: who the hell comes up with all of these?!), the first thing we realize is that predictive marketing is nothing new.

Marketers have used data for a long time to analyze and forecast the success (or failure) of their campaigns. I think what drives the predictive marketing hype is that year after year marketers have had access to increasing amounts of data and especially data sources/types, and now the technology to harness that information is becoming more commonly available. So instead of expanding on the things they already worked with, marketers did what marketers do: rebranded the whole thing as a new approach.

Big names (and big gains?)

Already the behemoths of SaaS industry, like Adobe, Salesforce and Nokia, have engaged heavily with the concept of predictive marketing and analytics. The field is still open for newcomers too: a San Francisco based startup called Radius has raised so far $125 million from investors. Their main product is a software that “uses more than 50 million data points” for predictions.

What is shared between all predictive marketing solution providers is the consensus about the fact that this technology is the next logical step in marketing, and those who ignore it are doomed to perish. The ability to understand and identify every individual customer and their individual needs, based on their behavior, time, location, relations, and thousand other variables, is a huge asset. Also things like predictive lead scoring have been attributed under predictive marketing, so there’s rather nifty new possibilities in all stages of the funnel.

Studies keep showing time and time again that consumers want personalized online services now more than ever. Predictive marketing seems to be an answer to that loud and clear demand, whether or not consumers themselves know that they want it. I guess in the end the real question is where lies the balance between consumers’ need for privacy and their need for personalization – or do they even know there’s a line in the first place.

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