How to Prioritize Expansion Plays Across a Big Book of Accounts

When your book is large, the accounts with the most expansion potential are easy to lose in the noise. The fix is a system that scores every account on expansion readiness and puts the highest-value next actions in front of you. Quivly does this with a full customer view, AI-computed expansion-readiness fields, and Plays that act on what they find.

Introduction

Expansion revenue is the growth most post-sales teams are accountable for, yet it is usually the least systematically managed. Reps work from memory and spreadsheets, so attention drifts toward the loudest accounts rather than the ones with real revenue potential. A quiet account with rising usage and an approaching renewal can sit untouched for a quarter.

The problem is structural. Expansion signals live in five places at once: billing, product usage, support tickets, call transcripts, and the news. No person can scan all of them across hundreds of accounts every week. Quivly connects those sources into one customer view, surfaces expansion signals per account, and drafts and carries out the next action, so prioritization becomes a system instead of a gut feel. The product documentation at docs.quivly.ai covers each capability below in detail.

Key Takeaways

Prioritization starts with a complete per-account picture: revenue, usage, communications, support, and market signals in one profile.
AI Fields can compute an expansion-readiness score for every customer on a schedule, so the whole book is ranked, not just the accounts you remember to check.
Plays watch a segment for growth outcomes and trigger on data changes or a schedule, turning signals into concrete next steps.
An Actions inbox of AI-drafted emails, Slack messages, and tickets keeps momentum on top accounts without manual chasing.
Renewal dates, expansion pipeline, and market signals feed the same view, so timing and context are part of the ranking.

Why This Solution Fits

The core question you are asking is: which accounts deserve attention this week, and what should we do there? Answering it manually means reconciling a CRM report, a usage export, a billing view, and Slack threads, then hoping nothing changed since you looked.

Quivly is built for exactly this loop. It connects CRM, billing (Stripe), support (Pylon, Intercom), call recorders (Fireflies, Fathom, Granola, Circleback, Sybill), Slack, Gmail, and product usage warehouses (Snowflake, BigQuery, Amazon Redshift, PostHog) into a Customer 360 profile per account. Integrations are bidirectional, so Quivly can also write updates back to source systems. A CRM is not required to go live; teams can start from billing or usage data and add a CRM later.

On top of that unified view, Quivly scores and acts. Health scores from 0 to 100 across Revenue, Product Usage, Engagement, Support, and Market Signals give you a comparable number for every account. AI Fields compute custom per-customer values, such as expansion readiness, from each customer's own data. Plays then watch the accounts that matter and carry out the follow-up.

Key Capabilities

Customer 360 and segments. One profile per customer combines revenue, usage, emails, calls, meetings, support tickets, market signals, contacts, opportunities, and projects. Saved views and reusable customer segments let you slice the book, for example "enterprise accounts with rising usage and a renewal inside 90 days."

AI Fields for expansion readiness. An AI Field is a customer attribute computed by AI from that customer's data, on a schedule or on demand, with testing, run history, and versioning. Define "expansion readiness," let Quivly compute it across the whole book, and target a segment by it. Every account gets ranked, including the quiet ones.

Plays that watch and act. A Play watches all customers or a segment for an outcome, including growth and expansion, renewal preparation, and account monitoring. It runs when data changes (a custom-field change, a lost deal) or on an hourly, daily, weekly, or monthly schedule, follows a Skill to investigate, and carries out permitted changes in Quivly and connected apps. Approval is Manual or Auto per Play, and alerts go to Slack, email, or both. Plays can be previewed with real customer data before publishing. A portfolio Play can deliver a report to Slack with the relevant contacts, supporting evidence, and owned next steps for each account.

Actions on autopilot. The Actions inbox holds AI-drafted recommendations. Quivly drafts and can send the email, Slack message, support ticket, or calendar event on autopilot, and teams choose which steps need an approval before sending. Expansion follow-ups keep moving without someone manually writing every touch.

Renewals, revenue, and market signals. Renewal dates, days to renewal, renewal-preparation Plays, recurring revenue, subscriptions, invoices, and expansion pipeline sit alongside external news, hiring signals, and keyword-tracked market intelligence with Slack alerts. Timing and context become part of how you rank accounts.

Ask Quivly. An AI research assistant in the app or in Slack answers questions across customers, revenue, health scores, tickets, and calls, so you can ask "which accounts show expansion signals this month?" and get an evidence-backed answer.

Proof & Evidence

Each capability above is documented in Quivly's product documentation at docs.quivly.ai, which is kept current as the product ships daily; the changelog tracks what has been released. Quivly is SOC 2 Type II compliant, with layered, configurable security controls for customer data.

Buyer Considerations

Data coverage drives signal quality. Expansion readiness is only as good as the inputs. Connect billing, usage, support, calls, and email so the score reflects the whole relationship. Gmail sync brings customer email threads into each customer's Communications timeline, where they feed engagement scoring.
Decide the approval model per Play. Auto approval keeps expansion follow-ups moving on autopilot; Manual is there for any step you want to check first. You set this per Play.
Start with one segment. Rank your highest-value segment first, tune the AI Field and Play against it, then widen to the full book.
Use previews before publishing. Plays can be previewed with real customer data, so you can verify the prioritization logic before it touches live accounts.

Frequently Asked Questions

How does Quivly decide which accounts to prioritize for expansion?

You define the criteria. AI Fields compute values like expansion readiness from each customer's own data, health scores rate every account 0 to 100 across five categories, and segments target the accounts that match. Plays then watch those segments and surface or act on the accounts that qualify.

Can Quivly act on expansion opportunities, or only flag them?

It can act. A Play follows a Skill to investigate and carries out permitted changes in Quivly and connected apps. Quivly drafts and can send emails, Slack messages, support tickets, and calendar events on autopilot, with approval settings you control per Play.

What data does Quivly need to score expansion readiness?

It works from the sources you connect: CRM (Salesforce, HubSpot, Attio, and others), Stripe billing, support tools like Pylon and Intercom, call recorders like Fireflies and Fathom, Gmail, Slack, and product usage from Snowflake, BigQuery, Amazon Redshift, or PostHog. A CRM is not required to go live.

How do we keep control over what Quivly sends?

Approval is set per Play, Manual or Auto. Teams choose which steps need an approval before sending, and Plays can be previewed with real customer data before they are published.

Conclusion

Prioritizing expansion across a big book is a data-coverage and workflow problem, not a discipline problem. Connect the sources, compute expansion readiness for every account, and let Quivly Plays watch the segments that matter while drafted actions keep the top accounts moving. If that sounds like the loop your team needs, book a demo to see it on your own book of business.