SalesChoice is highlighted in new Forrestor Report on CRM Sales Automation Software in two key categories relating to predictive sales analytics and prescriptive analytics:
SalesChoice is moving ahead with a Predictive Analytics/Data Sciences Webinar series.
With 40-60% of sales organizations behind in meeting their sales quotas, most Chief Revenue Officers (CROs) are not confident that they will get to their revenue target. According to Accenture and CSO Insights, less than 14% of CRO’s are confident they will make their plans.
Dr. Cindy Gordon’s presentation on Big Data and Predictive Analytics at the Sales & Marketing Middle East Conference May19-20 Abu Dhabi.
Predictive Analytics: Four Attributes
Predictive and prescriptive analytics are new territory to most companies working in big data today. According to Gartner Group, Predictive analytics describes any approach to data mining with four attributes:
SalesChoice specializes in Predictive Analytics and Making Sales a Science. We launched our new Predictive Insight Engine in the Fall of 2014, and we are in rapid commercialization mode currently.
We are under very restrictive NDAs as our science is uncannily smart and is reliably predicting future outcomes at 85% or more accuracy. Every client has received value and insight. How they apply this intelligence is something we are continuing to research. But what is clear our data scientists are finding incredible
Series 1: Brave ‘Now’ World Part
This is part three of a three part series. Today with so much data coming into organizations, the majority of companies are challenged to source new insights. Increasingly out world operates in near real time, and we expect our data and our patterns to unfold at the right point in time.
By Cindy Gordon
Part one of this three-part examined how big data has changed our approach to crafting business questions and the expectations of what information we’ll have access to when we make decisions.
Today analytics is moving rapidly into business operating processes and practices. The term being coined to describe this new field is machine-to-machine process intelligence, which at its core is predictive analytics.
Series 1: Brave ‘Now’ World Part
As humans, we have an insatiable appetite for deriving insights from data. With the intensification of big data and the promise of connecting the dots, our hunger for meaningful insights is greater than ever.
We rely on data for daily tasks without a second thought. We scour the web and mobile apps for movie recommendations, gift purchases, climate patterns, transportation foresight, healthcare, fraud detection, consumer behaviour, future sales outcomes, and even for the ideal romantic companion.
Originally posted on ITBusiness on February 7, 2014.
The last post I wrote at ITBusiness defined three market segments: predictive analytics, business intelligence, and big data to help frame a baseline of understanding. This blog post I wanted to continue our conversation and focus on why you should care, or with my western heritage, we always used to say, where is the beef?
This post was originally published by ITBusiness on February 6, 2014. It can be accessed here.
I must admit, I can get easily confused in discussing predictive analytics, or business intelligence, then adding the term big data in the mix, the sense-making becomes more challenging. With this market being so enormous and promising claims of unparalleled competitive edge, a few simple insights to decipher what’s in the market playbook – can only help us all learn more rapidly.