Predict and proactively act on customer risks and opportunities

Sturdy ingests data from customer communications across email, tickets, chats, call transcripts, meeting notes, and survey feedback, then fuses that information into one unified repository accessible company-wide. The platform emphasizes that it captures up to 95 times more data than traditional manual approaches, addressing the problem of incomplete data logging and disparate silos [1]. This consolidated view includes customer history such as account segmentation, ARR, support tickets, and interaction context, allowing a full picture of customer behavior and engagement. Sturdy markets this as enabling teams to access “all of your unstructured data in one searchable channel” [2]. This approach creates a single source of customer truth, removing duplicated or fragmented reporting and ensuring all revenue-facing teams can work from the same real-time customer dataset. The consolidation engine actively cleans data during ingestion, automatically normalizing inputs for consistency across systems. This means consistent, accurate, and comprehensive profile enrichment with virtually no IT or data science requirement from the enterprise.

The platform applies natural language processing and machine learning to extract early-warning churn indicators from the customer record. It highlights issues such as executive or sponsor turnover, negative sentiment, contract renewal or cancellation mentions, and feature-related frustrations [3]. Sturdy has demonstrated that approximately 17 percent of communications contain a meaningful “signal” such as churn propensity or expansion opportunity [4]. These signals are fed into customer health scoring models that merge structured usage and ARR attributes with unstructured indicators for a predictive risk profile. Automated routing ensures that high-ARR customer issues immediately alert the correct relationship owner through Slack or email. This unlocks the ability to prevent account dissatisfaction at an earlier stage of the lifecycle, reducing churn probability and aligning with operational retention targets. The AI-driven visibility gives leadership clarity into both quantitative financial exposure and qualitative relationship risks within the customer base.

The Sturdy Automations engine enables teams to create alert workflows using a point-and-click designer. Executives can configure automations by combining filters such as customer signals (e.g., negative sentiment, contract mention), customer attributes (e.g., ARR, segment), and delivery targets (e.g., a Slack channel or individual). The system then distributes alerts the instant a relevant event is detected, ensuring time-sensitive issues are not overlooked. For example, a churn-risk signal in communications from a high-value account would automatically push a notification to the assigned Customer Success Manager. Slack and email integrations are enabled by default, and further enterprise connectors like Salesforce, Jira, and ServiceNow are extending the automation ecosystem [5]. The automation system enables high-volume, repeatable interventions and allows management to formalize rules for escalation, thereby ensuring governance across the retention function. This bridges the gap between passive churn detection and proactive customer intervention, materially accelerating time-to-action.

The platform integrates directly with Salesforce and HubSpot to bring in account metadata, revenue fields, and customer attributes [6]. It also synchronizes with support platforms such as Zendesk, where tickets and chats are mined for retention signals and embedded into health dashboards [7]. Collaboration tools including Slack and Outlook are directly ingested, while IT operations systems like ServiceNow and Jira allow Sturdy to map product-related service escalations into customer profiles [8]. Unified dashboards combine this continuous stream with AI-driven interpretation into an updated customer health layer. The interoperability allows enterprises to deploy Sturdy as an embedded customer intelligence fabric across the CRM and CX landscape, creating a continuous loop of insight. Integration depth means less IT lift and minimal deployment lag, with onboarding measured in days. The outcome is seamless consolidation of interaction data across enterprise-critical applications, enabling strategic oversight across retention workflows.

Sturdy references customer outcomes demonstrating quantifiable retention impact. For example, one client achieved 100 percent retention across a 100+ customer segment base after deploying Sturdy to consolidate and monitor customer signals [9]. Another executive reported a 30 percent month-over-month retention improvement within six weeks, attributing performance gains to the visibility provided by Sturdy’s AI pipeline [10]. Client companies have also discovered root-cause dissatisfaction indicators, such as a case study revealing one product line generated 84 percent of customer confusion until identified through Sturdy analysis. Feedback insights often deliver retention gains of measurable ARR protection, with Sturdy marketing collateral citing 30 percent improvements as typical outcomes [11]. This translates into minimized churn risk percentages across at-risk ARR, safeguarding net revenue retention metrics. Sturdy’s deployment results validate the premise that continuous feedback monitoring creates material performance improvements, elevating enterprise retention outcomes.