A 10 Mio. use case of predictive sales discovered.
A current 37 % customer churn identified.
Improved dynamic pricing and cross-selling.

Problem

The company, founded at the beginning of the past century, is a worldwide market leader specialist in the energy sector. It offers more than 30.000 components across four business units, reflecting the four main product applications in power distribution. The firm organises its highly skilled B2B sales team by business units and within them by key accounts.

While some of the product families are project- and tender-driven businesses, the products for smaller applications are not. Differences in product-life cycles made cross-selling analytics and churn prediction extremely challenging. Furthermore, quality and regulatory requirements drive the global business markets.

The company is reorganising its sales activities around key accounts, and it is trying to bring more foreseeability into its sales planning. At the moment, the salesforce directly serves more than 4.000 customers and oversees a revenue of a couple of hundred Million Euros. The corporation introduced a customer relationships management system some years ago, although the sales team does not use it consistently.

The executive team has prepared remarkable sales analytics cases. They are, sadly, not adequately used to change sales behaviour or to prioritise accounts with cross-selling or pricing potential or with attrition risk.

Most sales reps work with enthusiasm and commitment, yet passively, waiting for Key Accounts to open new tenders or for distributors to place new orders. The salesforce usually negotiated prices individually using a price list and customer agreeability. The company did not measure customer churn. It utilises an SAP ERP system.

The main goal of the company was to implement a sales analytics software employing artificial intelligence to give their sales team an incentive to use their CRM and a competitive edge. Moreover, together with external partners, the company board was looking to implement predictive sales analytics to ensure long-term business profitably.

The company has engaged the services of an independent global business advisory firm to help them manage change and to mitigate risk. The consultancy partner has been seeking for sales analytics use cases within the group. A dedicated team of data scientists and business consultants hired Qymatix to analyse how the company pricing strategies, cross-selling potential and churn risk could influence its financial success.



Solution

The advisory partner commissioned Qymatix to analyse different sales analytics use cases within the company and to present possible predictive analytics examples using the Qymatix Predictive Sales Software.

First, in one half-day workshop, the Qymatix team discussed with the advisory partner the essential predictive sales methods used by our software, including several use cases and examples for manufacturing and distribution. We also invested time in assessing together management expectations, the feasibility of predictive analytics within the company and data quality issues.

In a couple of weeks and using the internal sales data available the Qymatix team presented a very attractive sales analytics case for the company, including a descriptive, predictive and prescriptive analysis of several years of ERP data. We assessed together with the management the expected benefits of our predictive sales software, with particular regard to churn prediction and prevention.

The customer obtained valuable insights regarding the definition and measurement of churn, including an assessment of the potential current attrition risk, pricing potential and cross-selling opportunities. Furthermore, during a feedback workshop, senior executives learned how to apply machine learning and predictive analytics for dynamic pricing in B2B distribution, increment cross-selling with existing customers and predict churn.

The final goal of the final implementation project is to expand ERP and CRM systems with Qymatix Artificial Intelligence technology and to support the efforts of a renewed sales management team. Also, the advisory partner aims to turnaround the financial fortunes of the company by operationalising predictive sales across all sales teams.



Results

The Qymatix team provided the customer with specific advice on how to segment and manage customers based on attrition risk and hidden sales potential.

Together, we identify the need for a strategic focus on customer retention, expansion and account recovery.

The company recognised dynamic pricing and price optimisation as a top priority. The Qymatix software made visible the specific accounts and product lines where they need to focus their pricing strategy.

The Qymatix Predictive Sales Software made visible a 37 % current customer churn and predicted accounts at risk of churning.

The company and its financial advisor identified financial gains of around 10 Mio. Euros per year, together with a roadmap for discovered cross-selling potential, better dynamic pricing, and customers lost and at risk of churning.



 

Ready to get started?

CONTACT US

Find out how you can accelerate your sales with Qymatix Predictive Sales Analytics.

Do you have questions?

+ 49 (0) 721 86016373

We are happy to help you. Qymatix is just a phone call away.


daniel-about-sales-analytics

“Qymatix helps growing medium enterprises to find undetected business opportunities with existing customers. With thousand active ones in our portfolio, Qymatix Predictive Sales Analytics is exactly what we need.”

Daniel Schuster – Welotec GmbH

armin-harbrecht about sales analytics

“Regardless of your company size, Qymatix is the best complement for your CRM system. Its predictive sales analytics tool helps sales leaders to focus on the projects with the best chances.”

Armin Harbrecht – aramido GmbH

Hermann Waselberger über predictive sales

“Qymatix Predictive Sales Software makes customer attrition risks and untapped sales opportunities over hundreds of customers and thousands of products easily accessible.”

Hermann Waselberger – AET Entwässerungstechnik GmbH

 

Was this article useful? Yes No 0 of 0 found it useful.