Use Case: Orchestrating Deal at Risk Alerts

Use Case: Orchestrating Deal at Risk Alerts

An account manager opens the CRM and sees a renewal marked as “on track.”
But what she doesn’t see is:

  • Product usage has dropped 27%
  • The main champion hasn’t attended the last two check-ins
  • A 12-day old support ticket is still unresolved

By the time those signals surface, it’s already too late. The account is at risk.

This could have been prevented easily if the support engineer knew that a renewal was upcoming and prioritized the ticket. This could have been prevented if the success rep knew there was a ticket.

Each team member sees part of the picture, not the full story.

How Data Orchestration Changes the Game

Customer success tools are good at tracking outcomes. They struggle to detect change as it happens.

Data orchestration solves that by turning scattered customer signals into one coordinated alert system. When product, billing, support and CRM data stay in sync, teams can see decline as it begins and step in before it’s out of control.

A single drop in usage is noise. A drop in usage paired with delayed payment and poor sentiment is a warning.

Orchestration connects those threads so teams can step in before a customer steps out.

Bringing It to Life

The value in orchestration isn’t in tracking customers; it’s in translating signals to action.
To prevent churn, you need a system that recognizes change early and routes it to the right person. Here’s how to make it work:

  1. Identify Risk Indicators
    Find the early warning signs that often precede churn, such as usage drops, support escalations, billing pauses or low engagement from key contacts.

    These signals already exist in product, support and CRM systems. They just need to be connected.

  2. Define Connection Logic
    Decide which combinations actually represent risk. If usage is down 20%, what NPS should raise a flag?

    Is that flag raised in Slack, Jira or a CS platform?

    Who needs to take ownership?

  3. Iterate as you Grow
    Risk signals evolve, and so should your detection logic.

    As your product grows and customer expectations shift, update your detection logic to reflect new behaviors.

    The goal isn’t a fixed health score. It’s a system that adapts to how customers actually use and value your product.

unnamed

The Impact

When churn stops being a surprise, teams can respond in time.

With signal orchestration, risk management becomes proactive, not reactive, and renewal conversations start with insight, not recovery.

That’s what BonData does. It connects signals across systems to help teams protect revenue before it’s at risk.

Book your demo today.

Data Stack

Liberating the Data Engineer

Data experts are not human middleware. Liberate your data team from firefighting and maintenance to building intelligence

Your Data Needs a Brain
AI Data

Your Data Needs a Brain

Data pipelines transport information but can’t remember what it means. Without contextual memory, AI makes expensive guesses. Why your data needs a brain.

Data Stack

Why Best-of-Breed Is Killing Your Data Stack

High data costs, engineering drain, and slow decisions? Discover how the ‘Integration Tax’ from your fragmented, best-of-breed data stack is silently compounding your problems.