At-Risk Account Playbook and Save-Motion Assignment
Knowing an account is at risk is only half the job — turning that into the right save motion, assigned to the right person, is where most teams fall down. Playbooks get applied uniformly regardless of segment, so an enterprise account gets a self-serve win-back offer while an SMB account gets an exec-escalation process it doesn't need. Save tasks land on a CSM who's already at capacity, and when an account trips several risk criteria at once, it can generate five overlapping tasks instead of one coherent plan, so the account either gets ignored or gets contacted five uncoordinated times.
STARTING PRICE
From €299
Standard tier · Multi-step workflow with AI extraction/decisioning and 2-3 integrations.
Get a quote →Saves roughly 6-9 hrs/week for a CS team running save motions across a mixed-segment book of business.
How the automation works
We build a playbook engine that matches the save motion to the account's actual segment and risk profile — enterprise accounts get exec-to-exec escalation paths, SMB accounts get self-serve win-back offers — instead of one generic process. When an account trips multiple risk criteria at once, the engine consolidates them into a single prioritized task rather than stacking duplicate playbooks. Assignment checks the CSM's current workload and availability before routing a save task, and re-triggering is suppressed while a save motion is already active on an account, so the customer gets one coordinated outreach instead of a wave of disconnected messages. Playbooks vary by churn driver — a pricing objection gets a different sequence than a product-gap complaint or a champion departure — and each assignment carries a deadline, so an at-risk account never sits untouched in a queue while attention drifts elsewhere. Executive sponsors are looped in automatically once contract value crosses a defined threshold, pairing the CSM's tactical save motion with a senior relationship touchpoint for the accounts where losing the deal carries the biggest revenue consequence. Outcomes are recorded whether the save succeeds, fails, or the account churns anyway, building a feedback loop that sharpens which playbook variant actually moves the needle for a given churn driver over subsequent quarters.
Process flow
- 01
Risk criteria trip trigger
One or more defined risk criteria (health score drop, usage-drop alert, renewal risk tier) fire on an account.
- 02
Match playbook to segment ai
The account's segment (enterprise, mid-market, SMB) and risk profile determine which save playbook applies, rather than a single default process for every account.
- 03
Consolidate overlapping triggers ai
If an account trips multiple risk criteria at once, the engine merges them into a single prioritized plan instead of firing a separate playbook per criterion.
- 04
Assign to CSM with capacity check ai
The save task routes to the account's CSM only after checking current task load, so it doesn't land on someone already over capacity or out of office.
- 05
Suppress duplicate re-triggers output
While a save motion is active on an account, the same risk criteria re-tripping doesn't spawn a second parallel task and a second round of customer outreach.
Inputs
- Account segment and tier
- Risk trigger events (health score, usage-drop alerts, renewal risk tier)
- CSM current task load/capacity
- Playbook library by segment and risk type
Outputs
- Single prioritized save-motion task per triggering event
- Playbook-to-segment match log
- CSM task assignment with capacity check applied
- Active-save-motion status per account
Works with
Prefer a fully custom build instead of an off-the-shelf integration? We scope both options during your free consultation — most jobs like this one work fine on standard connectors, but higher-volume or non-standard systems sometimes need bespoke API work, reflected in the complex tier.
Where this goes wrong if you get it wrong
- The same playbook applied uniformly to enterprise and SMB at-risk accounts means the enterprise save motion needs exec-to-exec escalation while SMB gets a self-serve win-back offer, and using one process for both fails both segments.
- Save-motion tasks get auto-assigned to a CSM who's already over capacity or on leave, and the tasks sit untouched while the account keeps decaying with no one watching.
- Playbook triggers stack when an account trips multiple risk criteria simultaneously, assigning the CSM five overlapping save tasks instead of one prioritized plan, and the CSM either does all five badly or ignores the queue.
- The automation keeps re-triggering the same playbook every time the risk score re-evaluates, even though a save motion is already in progress, creating duplicate and conflicting outreach to the same customer.
Frequently asked questions
How does this decide which playbook to trigger?
The account's segment and specific risk profile determine the matching playbook — enterprise, mid-market and SMB accounts each get a different save motion rather than one generic process applied to every at-risk account.
What happens if an account trips multiple risk signals at the same time?
The triggers are consolidated into one prioritized plan instead of spawning a separate playbook per signal, so the CSM gets one coherent task rather than a stack of overlapping ones.
Does it check whether the assigned CSM actually has capacity?
Yes, assignment checks current task load before routing a save task to a CSM, rather than assigning purely by account ownership regardless of whether that person can act on it.
Will an account get contacted repeatedly while a save motion is already underway?
No, re-triggering is suppressed while a save motion is active on the account, so the risk score re-evaluating doesn't generate a second parallel outreach to the same customer.