Phase I: Instrument Your Sellers

Phase I is about getting better data, and we do this by instrumenting the team. Instead of having the team use their desk phones, we have them use a connected system to make phone calls. Instead of letting emails go back and forth under the cover of night, we track them. With phone calls and emails automatically logged -- even the calls and emails that go unanswered -- the data becomes pristine and useful to AI. 

Phase II: Optimize Your Buyers

With clean data, CRM now becomes useful to our AI efforts. AI wants basically four categories of data:

Descriptive data--who are the prospects, and what characteristics do they have?
Activity data--what actions have been taken? (calls, emails)
Contextual data--what are the prevailing conditions at any given time (weather, economics etc.)
Results data--what have been the outcomes of our activities?
Phase III: Optimize Your Sellers

For the sales leader who wants to build a team that can reliably hit quarterly targets, it’s important to understand who they have in which seats. AI can instantly evaluate the historical performance of thousands of reps, identifying the behaviors and attributes that separate one group of performers from the next. Phase III relies on data from Phases I and II, but it flips the unit of analysis from the buyer to the sales rep.

Phase IV: Custom AI

With good data on buyers, good data on sellers, and good data on how opportunities make their way through the sales cycle, the remaining opportunities to leverage AI for revenue lift fall into the catch-all category of “what else?” These answers can be broken up into two categories:

More data / data sources
Different questions