What’s the Problem with Predictive?

By April 29, 2016
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I’m originally a developer, and in being a developer, I’ve always dealt with fact and data. In being a data-driven person, I am naturally attracted to predictive and predictive marketing.

Over the past few years, this small space called predictive marketing has grown into an entire software category. Today, forward thinking companies look to predictive to adopt the power of big data to better identify and address their customer.   I am definitely a believer but this wasn’t always the case.  When I first found predictive I found it interesting but felt it was just a feature… a better way of scoring.

Predictive scoring is hugely valuable and is the baseline functionality (or least common denominator) of the predictive movement. The predictive marketing category was born out of scoring because we are so intimately familiar with this function. Predictive allows us to score accounts a heck of a lot better with applied data, but that’s really just the beginning.

So, What is the Problem with Predictive?

Problem #1: Predictive is an Enabler, Not a Crystal Ball

The problem with predictive is it’s ahead of its time.  I think it’s massive value is clear, but there is still work to do. There is a lot of messaging out there from vendors promising things like, “We’re going to increase your likelihood to close by 300% “. Or “I am going to uncover million dollar deals just waiting for your phone call”! While I think these are things that predictive can help drive—predictive itself isn’t going to produce these outcomes. Predictive is an enabler, not a crystal ball.

Moreover, predictive doesn’t replace the human element, it feeds the human element. Marketers are still need to market, and sales people still need to sell. Predictive augments the ability for humans to do what we do best. To simply go out and say you are going to have better outcomes with predictive is not responsible. Ultimately, it is what you do with that data that is most important. Nobody knows the future. We still need to go out and market and sell to prospects.

Problem #2: Predictive Is Only Being Used at Top of Funnel 

The second problem is that many of the solutions to date have been fairly myopic. If we think about scoring and predictive demand gen, these are single points in the funnel. I believe there is a much bigger story for predictive than these two entry points. What’s interesting to me, is the vision outlined by our CEO Vincent Yang. Since the infancy of this organization he has set his sites on using data to augment the entire funnel. This vision is why I decided to join EverString.

So What Is the Solution?

Think bigger. We need to think about how data can actually permeate our daily lives and not replace the functions we do, but augment them. Data will not replace us, it will help us do what marketers and sales people do best. Its about being visionary enough to understand that we can be more creative, we can be more effective, and achieve results faster when we use data to fuel our initiatives.

The best marketers I’ve met in my life are amazing creative minds. I find myself in conversations with the team here at EverString just plain dumbfounded at the level of creativity that comes out of this group. This level of creativity is possible because we are using data to help with the some of the mechanical part of their jobs. I think predictive is capable of a host of new possibilities for individuals and companies alike.

So where is this all headed? Stay tuned….

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