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Categories: Marketing, Predictive,

Since I’ve taken on the role of CEO at Leadspace, I’ve had countless conversations with great marketers on the promise of predictive analytics. Many of the conversations relate to ROI or how to choose a potential vendor or partner, but most often, the question becomes when, and how fast, they should invest.

Predictive analytics in B2B sales and marketing has been around for the better part of a decade. The last six months, however, has marked a sea change in the growing awareness of this space. Part of this awareness has come from several recently published articles that are finally helping marketers make sense of the trend, including a great piece from David Raab on how to evaluate the landscape and Gartner’s recent Market Guide.

These reports are becoming more consistent in their coverage and highlighting key considerations for marketers looking to invest in the space. In short, there is growing consistency in the view that:

  • Predictive analytics platforms, and the models behind them, can drive dramatic improvement in performance (e.g. see SAVO). Among the top established players, however, most companies are using fairly similar analytics packages, and it is hard to differentiate on this alone. As Gartner likes to say, “math is just math.”
  • Access to meaningful data and meaningful analysis is critical to the success of the model and its potential business impact. And, the most valuable data is increasingly external – beyond the walls of the organization.
  • The ability to take action in the B2B environment, through sales deployment, marketing integration and, increasingly, advertising targeting  is critical to driving ROI from any implementation.

The fact is these similar perspectives point to a growing consensus in the B2B predictive analytics industry. This means we’re starting to get some product alignment on the value of the business, and it provides some clear axes for demand gen leaders to evaluate the different vendors entering the space. Most importantly, it continues to remind us that measuring not only statistical relevance, but also the business applicability of actions, has to be top of mind.

This milestone draws clear parallels to a model describing the 4 stages of disruption. It’s a model that has stuck with me since my days at Skype as key to understanding technology disruption.

disruption

Source: Steven Sinofsky, Board Partner, Andreessen Horowitz

Predictive analytics are changing the way marketers do traditional lead scoring and demand generation. In the early days, this was disruptive. I believe we have now moved past the evolution phase to seeing a convergence in how predictive analytics can replace the traditional lead discovery, enrichment and scoring paradigm that has existed since the start of marketing automation.

This marks a very exciting time if you’re in demand gen where the proven value and convergence of the industry are making the market more of a “no-brainer” than ever before. We see this with increasing numbers of customers starting to deploy B2B predictive analytics, even if the total market is still relatively new.

Thinking back to those conversations with marketers wondering when to invest, it seems now is the pivotal point to make your move with confidence in the robustness of the market, while still having the opportunity to use big data and analytics to stay one step ahead of the competition.

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