[Client Info]SAAS PRODUCTIVITY PLATFORM
A widely used SaaS provider delivering enterprise productivity tools for project tracking, collaboration, and reporting across teams. Xuno partnered with their growth and product teams to reduce churn, improve onboarding, and enhance feature adoption with embedded AI and predictive analytics.
#1. summary.
The goal was to reduce churn and improve onboarding for an enterprise SaaS productivity platform used by 30K+ teams globally. Despite solid acquisition rates, the client saw limited feature adoption and weak retention beyond the first 30 days. Xuno supported the product and growth teams with embedded predictive intelligence and a fully managed engagement model. The 9-month engagement focused on behavioral analytics, churn modeling, onboarding optimization, and real-time product dashboards.
Technologies used:
#2. challenges.
The client had high initial sign-ups but weak product activation. Their onboarding experience was static, didn’t adjust to user behavior, and failed to guide enterprise users to value fast. Retention beyond the first 30 days dropped significantly. Internal teams lacked visibility into key friction points, and data was fragmented across tools, making it difficult to detect why users were churning or abandoning mid-flow. They needed a solution that could uncover these insights and optimize in real-time.
#3. solution.
Xuno implemented predictive models to identify drop-off points and deployed dynamic onboarding flows that adjusted to user behavior in real time. We also built friction maps and user heatmaps to show where engagement lagged and helped test onboarding sequences with A/B variants tailored to different user types. Our team created a suite of internal dashboards powered by real-time product telemetry that gave marketing, product, and success teams daily insights to act on, reducing their dependency on ad hoc BI requests.
#4. outcome.
Churn dropped 29% within 60 days of implementation. Time to activation improved by 2.3x, and enterprise renewal rates increased by 18% quarter-over-quarter. Internal teams moved faster with access to real-time product intelligence and saw a 41% improvement in product-led growth metrics. The predictive models built during this engagement became part of the client’s internal playbook for all new feature rollouts.
