The client, a global high-tech engineering firm, struggled with root cause identification that caused higher churn across its diverse customer base. A subpar process visibility, absence of tracking mechanisms, and non-availability of countermeasures further led to customer attrition and high revenue losses.
Fuzzy LookUp by Microsoft
Advanced analytics
Advanced Churn prediction models
ML
The after-market departments across industries, particularly construction solutions – are characterized by a wide array of products and services, complex customer relationships, and an extensive stakeholder network. Many construction companies still struggle with legacy systems and a general hesitance towards emerging technologies. Besides limiting efficiency improvements, it also leads to gaps in process management and communication. A lack of comprehensive digital infrastructure also leads to improper planning, sales forecasting, and budget issues. In addition to data silos and inaccuracies, companies also grapple with lower process visibility leading to huge losses in revenue, customer retention and satisfaction, and, ultimately, market reputation. The right data analytics tools, unified platforms, and insight-driven mechanisms that can proactively analyze customer behavior and forecast demand and sales while addressing customer churn are paramount to creating or leveraging opportunities – ensuring long-term business viability.
The client, a global high-tech engineering leader with expertise in machining, mining, materials, and construction solutions, was dealing with similar concerns in its construction after-market division. Their diverse product and customer portfolio houses over 75,000 records with 60 variables each, handling 6 years of information on hundreds of customers, 7,000+ equipment parts, and 9 equipment types. The complexity of their information ecosystem, coupled with siloed and unstructured data due to outdated data-capturing mechanisms, hindered their ability to pinpoint the root causes of customer churn. Moreover, they struggled to implement effectively targeted and more personalized retention strategies. Their inability to track and address customer attrition directly impacted their revenue and business performance. The client sought a solution to proactively predict customer churn and identify its drivers, thereby improving customer satisfaction and retaining them.
Our experts at Bosch SDS, with their decade-long experience and extensive contextual knowledge of business/ market intricacies of hi-tech engineering markets combined with digital management complex product portfolios – offered a digital-first solution to address the client’s customer churn challenges. Amalgamating data management and advanced analytical tools, the solution was implemented in two key phases with multi-layered transformation enablement. Our process involved:
Bosch SDS’ Customer churn prediction system enabled the client to access mission-critical enterprise data and unlock valuable insights key to the sales and marketing teams, helping them make strategic decisions and recalibrate their customer retention approaches.
Predicted customer churn with more than 85% accuracy
Optimized outbound telemarketing
Strengthened customer retention
Stringent handling of piracy issues
Prompt resolution of end-user concerns
Analyzed the impact of discounts and premiums on customer churn and enabled optimized pricing models
Bosch’s commitment to continuous improvement and customer satisfaction has solidified its position as a trusted partner in the engineering industry. Unlike conventional data analytics tools, Bosch offers a comprehensive approach combined with the ability to understand the business/market intricacies, encompassing data harmonization, predictive modeling, and insightful visualization. Our comprehensive churn prediction system enabled the engineering firm to transition from reactive to proactive churn management, resulting in significant financial, operational, and strategic benefits. Significantly reduced customer churn directly translated to retained and enhanced revenue streams. With effective piracy handling, the client minimized revenue loss from counterfeit products. Through data harmonization and structuring, the company streamlined data access and analysis, saving time, costs, and resources. Finally, it strengthened customer relationships and loyalty and bolstered its competitive edge.
