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All I Want for Christmas is Predictive Lead Scoring

Unless you’ve been living under a space rock this holiday season, you’ve likely heard a familiar refrain:

I don’t want a lot for Christmas
There is just one thing I need
I don’t care about the presents
Underneath the Christmas tree

I just want you for my own
More than you could ever know
Make my wish come true
All I want for Christmas is you, yeah.

Now, are these Mariah Carey lyrics? Or the feelings of your average B2B marketer about predictive lead scoring?

Both.

It should be said that data modeling, which “predictive marketing” and other buzzwords are simply marketing-speak for, is a proven process. There is no way to understand what will be than to take a Polar Bear Plunge into what was.

Traditional lead scoring, meaning a score threshold which is established by a “best guess” of marketing and sometimes in a joint effort with sales, isn’t worth the matrix it’s often written in. One-dimensional, opinionated data (like scoring certain job titles above others) can create structure, but it doesn’t create a model.

Lead scoring has traditionally been facilitated by marketing automation, or even manually via “first blush” glances. The problem is this: that approach only takes into account the data that either resides in CRM, or “behavioral activity” that happens on a web property the scoring organization owns. That’s a huge selection bias.

To a create scoring model that truly provides value, we need to add a few things. First, we have to bring both positive and negative outcomes to the model so we can correlate those outcomes to the data we have on the buyer. Next, we need a TON more data. Predictive lead scoring provides both and therefore yields a much more reliable outcome.

Getting up to speed, what happened in 2015?

The biggest trend, aside from the simple fact that predictive has burst onto the scene in a big way, is predictive score as a function of demand generation. Ultimately, marketers know what their ideal leads look like and therefore they can use non-traditional data sources to go find more of those “A” leads.

Like most technologies in marketing, new tools always are mistaken for lead generation at first and in their second maturity cycle they are adopted as a more attributive strategy. Predictive lead scoring is no different.

A combination of predictive lead scoring and the entire notion of automation qualified leads will ultimately help marketers uncover their best customers. But they will need to use core tenets like marketing automation and account-based marketing to engage those buyers in a hyper-personalized way.

Using outbound to “tackle” predictive lead scoring-identified buyers is no different than cold calling, the best organizations already know this.

What you need to know before the champagne is served for 2016

The account-based marketing craze is upon us, with much of the the same fury as the predictive lead scoring bonanza. Both tools, along with marketing automation, are building the pillars of the tech stack. There’s going to be a good degree of consolidation from a technology perspective and it speaks to the need to create a highly process oriented buyer engagement strategy with all of these critical tools optimized.

Obviously, that’s easier said than done so the #1 area I would recommend executives invest in is education for the marketing department. No other area will yield as high of a result. We are putting some very complex technology in front of today’s marketing departments and we are asking them to learn on the job and it’s costing hundreds of millions of dollars not only in time and materials but opportunity costs.

At the end of the day if all we get out of this complex data science is the same as a well-targeted lead buy, we’re doing something wrong. The data will unlock a ton of great information on what creates your best buyer and what interests them – don’t get distracted by the first piece of low-hanging mistletoe.

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