Most expansion conversations start too late. A customer hits a seat limit, their admin emails support, and the upgrade happens because the customer pushed for it. Or they start too early: an account manager pitches a higher tier to a team that is still struggling with the basics. Both cases come from the same gap. The team isn't reading the usage data that shows when an account is actually ready to buy more.
This guide is about reading that data. It breaks expansion signals into four types, explains how to tell a real signal from noise, and shows how to turn signals into a score and a play your team can act on. The examples draw on Quivly's Expand NRR, Health Score and Radar pages.
What Makes an Account Upsell-Ready
An upsell-ready account has two things at once: a need for more than it currently has, and enough satisfaction with the product to want more of it. Usage data is good at showing the first. It needs help with the second.
That's why the strongest expansion signals are rarely a single number. A customer using every seat they bought could be thriving, or could have assigned seats to people who never log in. A spike in API calls could mean a new use case, or a runaway script. Readiness shows up when several signals point the same way: usage is growing, it is spreading across the organisation, it is getting deeper and the relationship is healthy.
Quivly's Expand NRR page describes the same idea. It looks at a combination of signals, including seat utilisation approaching limits, power feature adoption by multiple teams, QBR sentiment, champion engagement and CRM signals such as new stakeholder activity, then weights them into a single expansion score.
Signal Type 1: Capacity Signals
Capacity signals show an account approaching the limits of what it has paid for. They are the most direct expansion signals because they point to a specific next purchase.
- Seat utilisation. The share of licensed seats that are assigned and active. An account nearing its limit is a natural candidate for more seats.
- Feature or tier ceilings. Customers repeatedly hitting a limit that only a higher plan removes.
- API or usage thresholds. Consumption trending toward a plan cap or committed volume.
Quivly's page lists real-time usage milestone alerts for exactly these cases: seat limits, feature ceilings and API thresholds. For usage-based pricing, it tracks consumption against committed volumes and alerts CSMs when an account is trending toward an overage, which it calls a natural, low-friction upsell moment.
Watch out for: seats that are assigned but inactive. Count active seats, not provisioned ones, or you will pitch more licences to a customer who isn't using the ones they have.
Signal Type 2: Breadth Signals
Breadth signals show usage spreading beyond the original buyer. They often come before capacity signals and point toward cross-sell or a wider rollout.
- More distinct active users. Growth in the number of people using the product, not just in total activity.
- New teams or departments. Usage appearing in groups that weren't part of the original deal.
- New workspaces or environments. A customer setting up additional projects or instances on their own.
- New stakeholders. Contacts from outside the original buying group appearing in meetings, emails or the CRM.
Quivly's Health Score page gives a clear example of a breadth signal: growing query volume across multiple distinct user accounts suggests organic adoption beyond the initial champion into broader team usage. That pattern matters because an account that depends on one champion is fragile, while one with broad adoption has more people who would miss the product.
Signal Type 3: Depth Signals
Depth signals show a customer relying on the product more heavily over time. They are less about needing more seats and more about readiness for advanced capabilities or a higher tier.
- Power feature adoption. Users moving from basic features to the advanced ones that higher plans emphasise.
- Manual to automated usage. Customers creating scheduled jobs, recurring workflows or automations instead of doing everything by hand.
- Growing data footprint. More data, records or assets created month over month.
- Usage embedded in operations. Activity at off-hours or across time zones, suggesting the product is part of how the business runs.
Quivly's Health Score page lists several of these as growth signals. New scheduled queries or automated jobs signal a move from manual exploration to production-grade automation, and jobs running across multiple time zones or off-hours suggest the product has been embedded into critical business operations, which the page links to strong stickiness and expansion potential.
Depth signals are also useful in reverse. Quivly's Expand NRR page notes it can identify accounts that consistently under-use the product, surfacing coaching or re-engagement opportunities before they become churn risks. An account with shallow usage is an enablement conversation, not an upsell one.
Signal Type 4: Context Signals
Usage tells you what a customer is doing. Context tells you what is changing in their business, and it often explains why usage is moving. Context signals rarely justify an upsell on their own, but they make usage signals much more reliable.
- Relationship health. Positive QBR sentiment and an engaged champion.
- Hiring. Open roles in areas your product supports, which can mean a team is about to grow.
- Company news. Product launches, partnerships and leadership changes.
- Technology changes. The customer adopting tools that complement yours.
Quivly's Radar page covers this layer. It monitors LinkedIn activity, news, technology stacks and organisational changes across accounts, and flags opportunities such as customers hiring for relevant roles. Combined with a usage signal, a context signal turns "usage is up" into "usage is up and they're hiring a team that would use us."
How to Separate Real Signals From Noise
Not every usage jump means an account is ready to spend more. Before acting on a signal, run it through a few checks:
- Is it sustained? Compare against a rolling window, not a single day. A one-week spike from a migration or a test is not a trend.
- Is it broad? Check whether growth comes from many users or one. A single heavy user is a champion to support, not yet an account to expand.
- Is the account healthy? Gate expansion plays on overall health. An account with open support escalations or a billing problem needs those resolved before any upsell. Quivly's Health Score example shows exactly this tension: strong product adoption alongside an outstanding balance and silent engagement channels, where the recommended action is to fix the billing issue first.
- Can you explain it? If a CSM can't say in one sentence why an account is ready, the signal isn't ready to act on. Quivly's Health Score expresses growth signals as plain-language narratives with each claim cited to its source, so the reasoning is visible before anyone reaches out.
From Signals to an Expansion Score and a Play
Individual signals are hard to act on across a whole book of business. The practical step is to combine them into one score per account, with a threshold that triggers action.
Weight the signals for your model
Different businesses expand in different ways. A seat-based product should weight capacity and breadth signals heavily. A usage-based product should weight consumption against commitments. Quivly weights each signal to produce an expansion score, updated daily, and lets teams set the threshold that triggers an alert.
Attach a play to the threshold
A score is only useful if crossing the threshold leads somewhere. Quivly's Expand NRR page describes a typical playbook: a trigger such as seat utilisation crossing 85%, followed by a personalised email from the CSM, a task for the AE to prepare an upgrade proposal and an executive business review invite if the account is above a revenue threshold. Every step is configurable.
Decide what runs automatically
Lower-touch accounts can often receive expansion outreach automatically, personalised with their actual usage data. Strategic accounts usually need a human. Quivly supports both: sending directly from the CSM's inbox for lower-touch accounts, or queuing a draft for one-click review on strategic ones. Routing opportunities to the right AE through the CRM keeps CS and Sales aligned without a manual handoff.
Quivly's Expand NRR page reports that teams using it see a 28% average increase in NRR within 12 months, 3x more expansion pipeline identified per CSM and 60% of upsell plays running without CSM intervention. Those results come from treating expansion as a signal-driven process rather than something that waits for the customer to ask.
FAQ
Capacity signals, such as active seats nearing the licence limit or consumption trending toward a plan cap, are the most direct because they point to a specific purchase. They are most reliable when breadth and health signals agree.
A health score asks whether an account is likely to stay. An expansion score asks whether it is likely to buy more. A healthy account isn't always ready to expand, and expansion plays should usually be limited to accounts that are healthy.
Track consumption against the customer's committed volume. Accounts trending toward an overage are natural candidates for a larger commitment, while consistently under-used commitments signal a need for enablement before renewal.
Usually both. The CSM often owns the first conversation because they know the account's usage and goals, then routes the opportunity to an AE with full context to close it. Want to see which accounts in your book are ready to expand right now? Learn how Quivly's Expand NRR surfaces expansion signals from usage, engagement and buying activity and routes the right play to the right person.
