The Informed Enterprise

Data science, predictive, and recommendation technologies have the potential to help us understand where the opportunities lie, and how to most effectively pursue them. This will take CRM from a past focused on workflow and automation to a future focused on intelligence and prescription.

We see customers apply data science to improve lead scoring, customer engagement (frequency and quality), and messaging. Currently most of these efforts are focused on silos of data (inbound lead flow, customer interactions, targeting databases), but they will quickly evolve to integrate as much information as is available about prospects, customers, and their interests.

The Right Signals are the Foundation

How can we all prepare for this new world, so that we are at the forefront of the informed enterprise? We must create a body of knowledge that can power data science and predictive algorithms:

  1. Does our CRM have clean, normalized data? If we have the same company or person represented in multiple, disconnected records no algorithm in the world will be able to make sense of that information.
  2. Does our marketing database have the up-to-date and normalized information that we need to segment, score, and route leads?
  3. Do we have a way to maintain the marketing and CRM information up-to-date (hopefully in near-real-time)?
  4. Do we have the additional data that represent buying signals, mapped to the right companies and people? Signals include both behavioral information (is this company hitting our website) and demographic/firmographic information (does this company fit our qualifying criteria? Is this the right decision-maker, and if not who is?)

If we start with a clean dataset rich with the right signals, any of the great predictive and analytic technologies available in the market will do a great job for our businesses. Otherwise, garbage in will inevitably result in garbage out—and it will continue to be a noisy world.