This is an executive summary for the E&I Digital Strategy Lab course in the summer term 2025. Festo LX, the digital learning platform of Festo Didactic SE, has shown strong user growth in recent years. However, its current retention rate of 59 percent reveals a strategic opportunity: many institutional licenses are not renewed after expiration. This signals a need to reinforce long-term engagement and user satisfaction beyond the initial onboarding phase to sustain the platform's growth and impact.

Goal

The project aimed to identify and address the key friction points in the Festo LX user journey that contribute to early disengagement. The core objective was to derive data-driven, actionable recommendations that increase platform stickiness, improve user experience, and ultimately raise the license renewal rate. A special focus was placed on the post-onboarding phase, which has proven critical in determining long-term retention.

Methodology

We combined a comprehensive secondary research base with primary data and user insights. Our methods included the analysis of over 1,200 open user feedback entries, a literature review on churn, retention and customer satisfaction, a structured benchmark of five competing platforms, and two expert interviews - one with a Festo sales representative and one with a director of a Higher Technical Institute. Internal license data, user sentiment trends, and platform usage analytics rounded out our evidence base.

Results

Our research uncovered three critical levers that influence retention: relevance, clarity, and continuity. Users stay engaged when content is practically useful, interfaces are intuitive, and technical performance is reliable. However, user feedback and system data reveal four recurring dropout triggers: confusing platform navigation, mobile device incompatibility, unfair quiz validation, and a lack of structured follow-up after onboarding.

To address these, we propose three strategic initiatives. First, quiz usability should be improved through adaptive input validation and retry options. Second, a standardized post-onboarding framework should be introduced, including success calls and usage reviews to confirm early value. Third, we recommend developing an AI-powered tutor named Festo Assist to offer real-time learning support and generate actionable feedback data directly within the platform. These solutions aim to build confidence, reduce dropout rates, and promote long-term loyalty among both end users and decision-makers.

Cooperation Partner

• Festo Didactic SE
  Rechbergstraße 3
  73770 Denkendorf
  Germany
  www.lx.festo.com
  
   

Contact Person

• Ute Gebhard
  ute.gebhard@festo.com
  
  Philipp Melzer
  philipp.Melzer@festo.com
  
  Daniel Garcia Salas
  daniel.garciasalas@festo.com
  
  Daniela Follmer
  daniela.follmer@festo.com
  
   

Student Team

• Alexandra Kluge
  Valerian Patschka
  Christoph Hauer
  Marcus Semelmayer
  Federico Lilgenau
   

Project Manager

• Sandra Jeske

• Caroline Fabian