Fulfillment pending after resolution identifies interactions where the agent completed corrective action during the call but informed the customer that downstream fulfillment, confirmation, or implementation would occur later. This captures the gap between immediate resolution and final delivery.
The signal distinguishes between calls that end with complete resolution versus those that end with resolution in progress. An agent who says “I’ve processed your refund and you’ll see it in 3-5 business days” has resolved the issue but fulfillment is pending. An agent who says “I’ve credited your account and the balance is now zero” has completed both resolution and fulfillment.
This evaluation covers various fulfillment types: information being sent, account changes being processed, refunds being issued, services being activated, or confirmations being delivered through other channels.
Customers often conflate resolution with completion. When agents complete their part of the process but customers still need to wait for fulfillment, this creates a gap where customer anxiety and repeat contacts frequently occur. The customer heard “resolved” but experienced “still waiting.”
Operations teams need visibility into fulfillment dependencies because these represent handoff risks. If downstream fulfillment fails or delays, the customer will call back frustrated, often reaching a different agent who lacks context about what was promised.
Customer experience teams track fulfillment-pending interactions because they predict contact patterns. A spike in resolved-but-pending interactions typically leads to increased contact volume 3-7 days later as customers follow up on promised actions that may have been delayed or unclear.
Compass identifies interactions where resolution language (“issue resolved,” “processed your request”) appears alongside pending fulfillment language (“confirmation will be sent,” “reflected in your next statement,” “takes 24-48 hours to process”).
The signal requires both elements: the agent must have taken corrective action during the call AND indicated that additional steps will complete outside the interaction. This ensures the signal captures true fulfillment gaps, not unresolved issues or information-only calls.
Customer experience teams use fulfillment-pending patterns to predict and prepare for follow-up contact volume. When these interactions spike, they can adjust staffing levels and prepare agents with common follow-up scenarios.
Operations teams track fulfillment dependencies to identify bottlenecks in downstream processes. If agents consistently promise 24-hour fulfillment but the backend process takes 48 hours, this creates systematic customer disappointment.
QA teams focus on fulfillment-pending interactions to ensure agents set appropriate expectations about timing, next steps, and what customers should expect. Poor expectation-setting on fulfillment timing creates preventable repeat contacts.
This signal is part of Chordia’s Signal Intelligence capabilities.
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