Case Study

Data-driven segmentation to improve customer service models


€1 M

increase in sales

Hundreds of work hours

saved through a data-driven coordinated approach across sales, marketing, and customer service

The Business Challenge

Our client Rockfon, the world’s leading acoustic company, wanted to improve customer experience through ensuring the focus and responsibilities of the multi-disciplined teams to better match the changing needs of their clients. Rockfon sought to strengthen its “win local” approach, and further build on its personalized customer service strategy.

The team also wanted to gain a more detailed, data-driven understanding of how customers interact, buy, and use their products and services. This information would allow them to personalize propositions according to market-specific dynamics, improve the team performance by shifting their focus to the right customers at the right time, and overachieve the sales targets.

dashboard on desktop
Technical approach to need based customer segmnetation

The Solution

We started by understanding how over 700 customers in one of Rockfon’s largest B2B markets behaved. We analyzed historic sales for each customer. This enabled us to create data-driven profiles of each direct customer based on the frequency, recency, monetary value, engagement, progression over time, and revenue potential, using RFM segmentation modeling through K-means.

The newly derived profiles were used to segment customers by their needs and then assign them to the most appropriate service models. Each sales representative receives a list of priority customers in their respective region with tailored suggestions on how and when it is best to address their contacts.

We partnered with Rockfon’s marketing team to bring the customer segments to life through building customer personas. The personas were drafted based both on data-driven profiles and the industry expertise of the sales team.


We conducted workshops with sales, customer service, and technical teams to finalize the customer personas per each segment and relevant service level, to meet their needs accordingly.

Being part of the whole process, the sales team easily implemented and used the refined service-level guidance for their respective customers in both their daily responsibilities and their annual account plans. The single, cross-department understanding of the customer base allowed a smooth transition of customers through every stage of the sales funnel. The solution resulted in revenue growth surpassing the industry one on a half-year basis.

Two new customer service models became the outcome of the project. Rockfon took the opportunity to serve smaller and less frequent customers with a lighter digital and inside sales model that suited their less frequent ordering style while being efficient for the company.

k-means clustering for need-based segmentation

need-based segmentation results

How we used data science and Key Leading Indicators of Sales to better understand marketing campaign effectiveness and improve sales and marketing ROIs


Increase in conversion rates online

Improved marketing ROI

Through enhancing valuable marketing activities

Customer profiles cleaned

Through accurate CRM data management

The Success

We managed to increase the overall customer satisfaction due to the tailored service models approach and a highly improved personalization of customer communication and offerings.

We helped Rockfon identify a more effective marketing strategy. The sales representatives now have the choice between choosing a mass marketing strategy for customer accounts that require future nurturing and a “hypercare” strategy for the more promising customers (potential new sales) or the ones at rescue (risk of churn).

Clear customer analysis resulted in saving significant time for the sales team that can now be dedicated to the direct sales process. Hundreds of work hours per week were saved at Rockfon through determining a data-driven action plan with clear customer personas and suggestions for best actions per segment.

Business impact

We calculated the customer segmentation impact through segmentation results monitoring and process evaluation surveys, filled in by all sales representatives.    The surveys are conducted on a yearly basis, while the segmentation results are monitored every quarter.

We identified the customers that were moving between segments (I.e. going up a segment, going down a segment) for monitoring purposes. The service model nurture structure boosted customers going up a segment. The sales from the customers going up/down a segment added 1M euros to the total sales for 2019.

Survey results showed that sales reps can clearly define the difference between the segments and are using the service models connected to the segments. The sales teams highly valued the cross-functional support they received and outlined it as one of the key factors helping them reach their sales targets.

Related content

Want to know more?

Segmentation / Customer Lifetime Value

Segmentation and CLTV analysis empower businesses to personalize customer experiences and maximize revenue.