Nutshell
SEPTEMBER 9, 2020
Sales managers are responsible for growing revenue. That means 1) providing sales reps with the guidance they need to continuously improve, 2) building a sales process that gives reps the best chance at closing each lead, and 3) understanding which efforts are moving the needle and which are a waste of energy.
QYMATIX
NOVEMBER 1, 2022
There is keen interest in artificial intelligence (AI) and machine learning specifically for sales management in the B2B market. Gartner’s “2021 CSO Priorities Pulse Survey” shows that investment in AI analytics and technologies is rising. But other factors are making hyper-automation in sales inevitable.
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QYMATIX
FEBRUARY 13, 2024
In many sales departments of companies, sales staff are under much pressure by having to fill out documentation with forecasts, e.g., “How much do you sell to customer XY in 2020?” These forecasts , which cost sales staff much time , are also very error prone. How do you get started with predictive analytics?
QYMATIX
FEBRUARY 13, 2024
In many sales departments of companies, sales staff are under much pressure by having to fill out documentation with forecasts, e.g., “How much do you sell to customer XY in 2020?” These forecasts , which cost sales staff much time , are also very error prone. How do you get started with predictive analytics?
QYMATIX
NOVEMBER 6, 2023
In B2B wholesale distribution, sales managers and executives must increase their return on sales (ROS) to remain competitive and profitable. This article will discuss ROS and how sales executives can improve it using predictive sales software and AI in B2B. What is Return on Sales (ROS)?
Miller Heiman Group
AUGUST 8, 2019
It’s clear that a CRM alone isn’t enough to help your sales teams adapt to changing buyer needs and win more deals. But a sales analytics platform powered by artificial intelligence—transforms your CRM into a crystal ball predicting which actions increase a seller’s odds of winning a deal—and help them close it faster.
QYMATIX
NOVEMBER 23, 2021
In many sales departments of companies, sales staff are under much pressure by having to fill out documentation with forecasts, e.g., “How much do you sell to customer XY in 2020?”. These forecasts , which cost sales staff much time , are also very error prone. How do you get started with predictive analytics?
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