Making Smarter Decisions: Why Sales Prediction Analytics will challenge everything we know (Part Two)

The focus on Sales Predictions has been very much focused on Sales Prospects (Lead Scoring) versus full Sales Opportunity Funnel Predictions with numerous vendors sourcing more relevant sales prospects, based on criteria for the predictive analytics to predict validity of leads to help focus sales call activities on higher scoring leads, vs. lower scoring leads – all with the vision of accelerating sales quota attainment.

This could be based on a social media (Twitter trigger where a prospect is saying I need to buy a new car, thinking of a Honda), that is mined and sent to a Honda sales representative in the location closest to the Tweeter, and a sales rep engages in the conversation immediately on the social channel, saying Hi I am Sally, I am the Honda rep on 50th St., a link to our new models, what to chat?

Recently, SalesChoice Inc. analyzed over 40,000 SalesForce.com records over four years with SFDC data, and Marketo data, and we found incredible findings. Frustrated by inaccurate sales forecasts, the CEO & SVP of Sales wanted to mine hidden patterns in their sales data. The results found that where the company thought there was competency in specific areas in the company, these assumptions were not valid. For example, the company prided itself that as Sales Relationships moved from their current account to a new company, that they believed their success rates on conversion loyalty was incredibly high, or purchasing content syndication was a valuable marketing investment. Being able to analyze, correlate and mine relevance of all the patterns all at once allows sales predictions full funnel analytics to bring facts to the table, based on both historical, current data patterns, with statistical relevance stripping away inaccurate facts so the predictions are valid. These new approaches will enable sales professionals for the first time in history to have a real-time scientifically proven method to guide their sales rep activity. These approaches also allow sales management to engage in real time coaching, with triggered insights never seen before.

I like to call this new Era the Science of Selling where for the first time, diverse disciples are coming together from: Advanced Math, Artificial Intelligence, Text Mining, Statistics, Genetic Programming, etc….wrapping predictive analytics to analyze, both structured and unstructured data patterns inside CRM solutions and also external to CRM solutions from diverse data sources.

The implications to business results are already increasing sales activity relevance by 20-50%, with case studies being carefully hidden due to the competitive nature of these investments. In addition, sales reps can be rapidly advised where there is greater value and propensity to advance an opportunity, benefit from the behaviors of successful quota performing reps, by seeing their activities in real time, with anonymity, this provides a visualization that I refer to as a SalesGPS – knowing when I am on ramp or off ramp, trying to avoid all the obstacles in front of my sales goal by trusting the intelligence of the software predictions are more accurate than my intuition, and for sure my memory. The world has simply become too complex to manage without smarter tools to augment my human intelligence.

This brave new sales predictions world will further challenge marketing program value in ways that are unprecedented, and sales executives will be able to make tough calls on talent much earlier, based on their behaviorial patterns. Some of the breakthrough research that we are doing with the University of Toronto, we believe will help inform sales management if resources will ever have the potential to make their plan simply based on their behaviorial patterns. So our company, SalesChoice, is acutely focused on new approaches bringing the science of selling to higher levels of performance precision and revenue realization.