# Predicting renewals and reducing churn at scale > Enterprise cyber security software provider ยท SaaS & Tech A large cyber security software provider had seen churn creep up to nearly 8%, well above the SaaS benchmark. QuantSpark's predictive renewals approach is projected to add up to $30m a year by lifting gross retention. ## At a glance - **$30m** projected annual retention benefit ## What was the problem? After five years of strong growth, the provider's churn had risen to nearly 8%, around four points above the 4-5% SaaS benchmark. With annual revenue above $500m, each point of gross retention was worth millions. Compounding the lost revenue, its 300-strong customer success team had no standard way to track renewal actions or assess their effectiveness. The business needed a scalable way to identify at-risk customers, a method to introduce effective interventions, and an interface to monitor churn across the business. ## What did QuantSpark do? QuantSpark engineered features tailored to the client's product and customer base and identified the strongest drivers of churn risk, finding that a lack of customer engagement over three or more months was a top predictor. The team tested several algorithms and selected a Long Short-Term Memory neural network, which models how risk evolves over time for each customer, and built the infrastructure to run it daily and serve scores to frontline teams. A working group of customer success managers validated the risk scores and shaped the dashboards, building trust and adoption, and precision and recall rather than raw accuracy were used to judge performance. ## What changed? By moving customer success from reactive firefighting to proactive nurturing, the provider is projected to lift gross retention by 2-3 points, worth up to $30m a year, while deepening customer relationships and creating room to grow expansion revenue (a projection). The model also gave customer success teams the underlying drivers of risk, enabling more useful conversations, for example instituting monthly check-ins after the analysis linked missed customer-success meetings to higher risk. --- Canonical page: https://quantspark.ai/case-studies/predictive-renewals-churn-at-scale More about QuantSpark: https://quantspark.ai/llms.txt