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Customer Renewal & Expansion Review — AI Agent Playbook

Original price was: $1,500.00.Current price is: $349.00.

Bring renewal signals and confirmed expansion interest into one owner-reviewed account brief. Limited-time launch price: $349 through October 31, 2026. Planned future company-license price: $1,500.

SKU: ENC-AP-05 Category: Product ID: 23285

Description

Build a repeatable review of renewal timing, product usage, support issues, and confirmed expansion interest. The playbook applies visible rules, identifies missing evidence, and proposes the next customer conversation while business judgment remains with the account team.

Choose the level of support you need

Option Limited-time launch price What it includes
Digital implementation kit $349 one time
$1,500 planned future price
Editable playbook and PDF for one organization. Launch pricing ends October 31, 2026.
Guided setup +$1,495
$1,844 total during launch
Two 60-minute sessions, scope and field-map review, one sample-output review, and one consolidated revision. ENC effort is capped at six hours.
Custom implementation From $7,500 A scoped configured workflow, testing, human review step, handoff documentation, and training. Request an implementation quote.

Best for

Customer success leaders at recurring-revenue B2B businesses with consistent renewal, usage, support, and owner data.

What this release covers

One recurring product or service, one account per run, equal usage windows, approved thresholds, and internal owner review.

What you receive

Your download includes the editable Word playbook and a PDF version. It defines the workflow, required inputs, business rules, review process, synthetic example, acceptance checks, and pilot design.

License and support

One purchase licenses this release to one named organization, its employees, and contracted implementers. Source materials may not be resold, sublicensed, or redistributed. File-access and documented-defect help is included for 30 days.

Business results depend on your data, configuration, review process, and adoption. Examples use synthetic data; no revenue, savings, or performance result is guaranteed.