Shakespeare is dead! Let machine learning bring intelligence to your text.
One first-hand example of predictive text scoring and sentiment analytics using machine learning.
We are always looking for a way to bring machine learning to ERP-Systems. Companies can apply a Predictive Scoring using Machine Learning to prioritize sales leads, discover cross-selling opportunities and to classify text.
To support the efforts of our B2B marketing team, we invested time and resources, developing a machine learning scoring system for our blog content.
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The remarkable truth about Predictive Sales Analytics & Controlling
Is predictive sales analytics software the newest secret weapon in B2B?
No organisation will survive the next decade without harvesting the power of predictive sales analytics. However, many sales leaders in Business-to-Business (B2B) still lack the understanding of its benefits or the infrastructure they need.
Some ignore the value of their sales data, languishing unused in their ERP and CRM systems. Furthermore, B2B sales controllers are expected to gather an ever-increasing amount of sales data for their sales leaders to neglect value extraction. Moreover, there is no value in the data if it is not used to improve revenues.
Predictive Analytics CRM - A New CRM or Predictive Analytics? What comes first?
The top 3 reasons why successful companies avoid changing their CRM and use Predictive Analytics instead
Implementing a new Customer Relationship Management System (CRM) is a minefield for B2B companies. These projects tend to last longer than planned and cost more than budgeted. In many cases, they fail altogether.
CRM vendors are quick to oversell the utopian benefits of their solutions. Companies buy them in good faith without clear and measurable expectations.
How to use software for customer churn to improve customer retention - Qymatix Example
Reduction of customer attrition by implementing a churn prediction software in your sales reporting
Understanding and avoiding customer churn ( or attrition) in Business-to-Business(B2B) organisations can make the difference between a successful financial year or a miserable one.
Every experienced sales leader knows that some customers will eventually churn. Studies in the field of customer retention talk of a 5 to 25 % customer churn per year, depending on the industry. Customer attrition is revenue lost.
CRM Analytics – The Qymatix most effective three tips for B2B sales
Sales Analytics is changing the way sales teams work in B2B. Both Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems offer pro and cons for sales analytics. Some teams are already using machine learning for Predictive Sales Analytics from their ERP data; most are just implementing analytic in their CRM.
Predictive analytics - how much data do you really need?
How Much Data Do You Need For Predictive Analytics?
Predictive analytics is one of the technologies with the highest financial impact in B2B sales. Several popular applications of predictive analytics are becoming “must-have” nowadays.
Sales leaders rely on lead scoring, customer attrition modelling, cross-selling analytics and pricing analytics to prioritise their sales activities and increase their customer lifetime value.
The Top 5 ERP Sales Data Mining Techniques You Need in B2B Now
Pythia, priestess of Apollo at Delphi, commonly known as the Oracle of Delphi, was one of the most important oracles of Greek antiquity. In classical Greece, an oracle was a person considered to provide insightful advice or prophetic predictions, inspired by the gods. It was, of course, a form of divination.
How to measure ROI of advanced sales analytics projects
Return on Investment (ROI) is one of the most popular evaluation metrics and performance measurement used in business analysis nowadays.
The ROI is a powerful tool for evaluating the performance of any financial investment, in this case, advanced sales analytics projects and software.
Predictive analytics applies mathematical methods and techniques from data mining, statistics, machine learning, and artificial intelligence to make predictions.
Predictive Sales Analytics is used nowadays in applications such as lead scoring, pricing analytics, churn risk analysis and cross-selling, among others.
Predictive Analytics in B2B E-commerce: A customer acquisition example
As "Business Manager E-commerce" I work daily with new trends and strategies to improve and optimise the buying experience of our B2B customers.
There is one trend that Business Managers cannot avoid in E-Commerce these days: the systematic use of data to optimise product and sales strategies.
Predictive Sales Analytics Software | Qymatix Predictive Sales New Release
With the valuable input from partners and customers, Qymatix has released an improved version of its predictive sales analytics product.
The new version of the SaaS brings together extensive research in the field of predictive sales analytics and front-end usability. Sales leaders in Business-to-Business will benefit with an easy-to-use and easy to understand self-service predictive sales analytics software. Users do not need their IT department to perform advanced sales analytics and will no longer suffer “spreadsheet misery” during sales reporting.
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