Have more informed renewal conversations

Sturdy consolidates all customer communications such as emails, live chats, support tickets, surveys, and call transcripts into a unified environment where its AI models extract and categorize risk-indicating signals [1]. The system identifies concrete triggers such as feature requests, requests for contract review, budget concerns, instances of poor service perception, or billing issues. Each signal is processed automatically, with downstream routing into customer success, finance, or executive channels depending on the category and urgency. For example, a contract termination request appearing in an email can auto-generate an alert for an escalation team to retain the account immediately. The platform eliminates the need for manual tagging, which enhances adoption velocity and accuracy [2]. The outcome is a full at-risk dashboard that quantifies every issue relevant to an upcoming renewal discussion, removing dependency on anecdotal knowledge. Case studies indicate that organizations using Sturdy preserve measurable revenue by catching churn signals weeks before contracts close, with examples including 100% retention reported in key account segments [3]. This level of insight creates an explicit feedback-to-action cycle where risk is flagged, assigned, and resolved before it impacts retention KPIs.

Sturdy Connect™ architecture enables near-real-time integration with leading sales and customer systems including Salesforce, HubSpot, Zendesk, Jira, Slack, Zoom, Outlook, Gmail, Gainsight, Gong, Snowflake, and Tableau [4]. This bidirectional configuration enables signals generated inside Sturdy to appear directly within CRM tasks, Slack channels, or operational dashboards used by revenue teams. For instance, a customer expressing dissatisfaction in a support ticket can produce a CRM task in Salesforce and simultaneously notify the account lead in Slack. Integrated analytics can also output structured customer intelligence into Snowflake or Tableau for advanced modeling. Because integration does not require manual engineering effort, deployment occurs in a matter of clicks, reducing time-to-value across enterprise stacks. Importantly, eliminating duplicate data flows aligns success, sales, and support around a single intelligence framework. Teams become able to monitor real customer communication data without context loss, improving alignment on revenue protection strategies. Testimonials support this effectiveness, noting retention gains became measurable within six weeks after integrations were live [5].

Organizations deploying Sturdy have documented substantial revenue protection. Specific case outcomes include 30% improvement in month-over-month retention within six weeks [5]. A client case involving Syntrio reported saving $1.2 million in at-risk renewals by leveraging surfaced churn signals [6]. Another company recorded absolute retention with no churn in a segment of more than 100 accounts during the evaluation period [6]. These data points reflect how Sturdy shifts churn into an addressable revenue lever rather than an unpredictable revenue loss. Because churn improvements compound across an entire SaaS book of business, even reducing churn by a percentage point materially increases long-term lifetime value. Research from Sturdy illustrates that moving churn from 10% to 9% can add approximately $17,000 to each customer’s lifetime value [7]. The evidence demonstrates that measurable churn prevention directly scales into sustainable NDR growth.

The At-Risk dashboard is the system interface that aggregates and categorizes all live risk signals, giving decision makers full visibility into the source and severity of churn drivers [8]. Risk cues range from budget tension and feature requests to negative service sentiment and escalation threats. The dashboard provides predictive renewal probabilities tied to specific customer behaviors, such as knowledge of risk when a feature discount request surfaces. Alongside the dashboard, Sturdy distributes a Revenue Risk Calculator, a quantification tool to estimate the proportion of book value that may be under threat. The combined analytical layer allows revenue teams to model retention sensitivity against customer behavior in a measurable way. Root-cause analysis supports transparency, with examples where organizations uncovered one product line accounting for 84% of customer dissatisfaction [9]. This format produces forecast predictability without manual analysis and aligns customer intelligence outputs with financial KPIs.

The software is delivered as a fully SaaS, cloud-based platform that avoids heavy implementation burden [2]. Unlike platforms requiring manual configuration, Sturdy eliminates custom model training or manual data tagging, relying on pre-trained AI models optimized for customer communications. Integration with Slack, Salesforce, HubSpot, and other enterprise systems is configured through Sturdy Connect in a few clicks, resulting in dashboard population shortly after connection [4]. Organizations report capture of retention results and measurable churn reduction beginning inside the first month of usage. Illustrative outcomes include measurable improvement in retention metrics within six weeks after live deployment [5]. This acceleration is facilitated by automation that turns conversation-based signals into actionable workstreams without process redesign. Proven market deployment across four or more years reflects real-world validation of the platform and cumulative intelligence refinement from analyzing billions of customer communication words [10]. For revenue leaders, time-to-value translates into not only faster retention ROI but also improved forecast clarity earlier in deployment cycles.