How Bricklay delivered an 85% revenue retention rate across 100,000+ corporate customers by implementing a data-driven retention program that tracked billings health, pricing signals, and churn patterns across 180 branches, automated three previously manual revenue levers, and gave leadership the ability to distinguish pricing-driven churn from volume-driven churn for the first time.
Revenue retention rate achieved across 100,000+ corporate customers by tracking billings health, pricing signals, and churn patterns across 180 branches.
Revenue levers fully automated: annual price revisions, credit issuance, and bundled pricing, keeping pricing aligned with contractual obligations and market conditions.
Branch, market, and corporate-level revenue intelligence delivered live, replacing periodic static reports with real-time decision intelligence across the full operation.
Pricing-driven churn quantified separately from volume-driven churn, giving leadership an evidence-based intervention roadmap rather than undifferentiated retention spend.
A confidential storage company operating 180 branches and serving more than 100,000 B2B corporate customers across storage, destruction, and document service lines. The organization had been experiencing market-share decline among large and medium portfolio accounts. Revenue leadership could see that customers were leaving but could not see why, which accounts were most at risk, whether the loss was pricing-driven or volume-driven, and which of their available revenue levers to deploy and when.
Revenue attrition at scale is not random. It follows patterns: pricing pressure from specific account segments, volume decline in particular service lines, competitive displacement concentrated in certain markets. The ability to act on those patterns depends entirely on the speed and granularity at which they become visible. This organization had five structural gaps that made the patterns invisible until the accounts were already gone.
"At 100,000+ corporate customers across 180 branches, the accounts most at risk of departure are rarely the ones making the most noise. They are the ones quietly reducing engagement while the data sits unanalyzed in the billing system."
Market-share decline among large and medium portfolio accounts was measured retrospectively. Leadership knew accounts had left after the loss was reflected in billing data. There was no predictive signal identifying which accounts were trending toward departure, no early-warning system enabling proactive intervention, and no mechanism for C-suite or regional leadership to engage before revenue was already gone.
When a customer's billings declined, the organization could not determine whether they were paying less for the same volume, purchasing less volume at stable rates, or transitioning to a competitor. Without that distinction, interventions were applied to the wrong root cause, consuming resources without addressing the actual driver of revenue loss.
Annual price revisions, credit issuance, and bundled pricing decisions were managed through manual processes without a coordinated data layer. Price revisions applied without competitive awareness created churn where they could have retained. Credits issued without pattern analysis failed to address the underlying service gaps. Bundled pricing opportunities went undeployed where they would have driven re-engagement.
Revenue performance across 180 branches was reported in periodic aggregates that masked variation at the branch, market, and account level. Corporate leadership could see total revenue direction but not which branches were outperforming, which were losing pricing ground, or which markets had competitive exposure requiring targeted intervention. By the time branch-level problems appeared in aggregate reporting, they had already compounded.
Without year-over-year billing comparison at the individual account level, leadership could not identify accounts with declining billing trajectories before those trajectories reached departure. Accounts that had been steadily reducing engagement over multiple quarters appeared stable in snapshot reporting. The revenue signal that would have enabled re-engagement was present in the data but never surfaced in time to act on it.
Bricklay designed and delivered a data-driven revenue retention platform that tracked billings health, pricing signals, churn patterns, and Year-over-Year revenue trends at corporate account, industry, market, and branch levels across the entire 180-branch operation. Three previously manual revenue levers were automated. Pricing-driven and volume-driven churn were separated for the first time. Re-engagement strategies including bundled pricing and seasonal discounts were deployed with data-driven account-level targeting.
At 100,000+ corporate customers, the difference between 85% revenue retention and market-share decline is not better customer service. It is knowing which accounts are at risk, why they are leaving, and which lever to pull before the departure happens.
The platform tracked billings health at corporate account, industry, market, and branch level, surfacing Year-over-Year revenue trends and churn-indicative patterns in real time. Accounts with declining billing trajectories were identified weeks before departure rather than after. Regional and C-suite leadership received actionable retention intelligence rather than lagging revenue reports.
Annual price revisions, credit issuance, and bundled pricing decisions were automated through a coordinated data layer that ensured pricing decisions remained aligned with contractual obligations and current market conditions. Price revisions were applied with competitive awareness. Credits were issued with pattern visibility. Bundled pricing was deployed where the data indicated re-engagement potential.
The platform quantified the revenue impact of customer departures at branch, market, and corporate level, enabling the CFO to distinguish accounts lost to pricing pressure from accounts lost to volume reduction or competitive displacement. Intervention resources were targeted at the correct root cause rather than applied uniformly across all churning accounts.
Year-over-Year billings growth analytics were delivered at corporate account, industry, market, and branch levels, replacing periodic static reports with live multi-dimensional revenue intelligence. Leadership could see which accounts, markets, and service lines were growing and which were declining before the trend reached a reporting threshold that made intervention too late.
Data-informed bundled pricing and seasonal discount strategies were introduced with account-level targeting based on service history, billing trajectory, and re-engagement signals. The result was measurable B2B re-engagement among inactive accounts and reduced churn in the destruction and onboarding service lines.
Reversing market-share decline required making the invisible visible: which accounts were leaving, why, and which intervention would retain them. Four outcomes measured what that visibility delivered.
Market-share decline among large and medium portfolio accounts reversed. Revenue retention of 85% achieved across 100,000+ B2B corporate customers through proactive, data-driven intervention rather than reactive account recovery after departure.
The revenue impact of customer departures quantified and categorized at branch, market, and corporate level. CFO and CRO leadership able to direct retention resources at the correct root cause, not the visible symptom.
Annual price revisions, credit issuance, and bundled pricing decisions automated through a coordinated platform. All three levers aligned with contractual obligations, market conditions, and account-level data simultaneously.
Year-over-Year billings growth visible at corporate account, industry, market, and branch level in real time. Periodic aggregates replaced with always-current multi-dimensional revenue intelligence across the entire 180-branch operation.
This engagement was built for organizations where revenue attrition at scale is not random, it follows patterns that are only visible with the right data layer, and where the difference between 85% retention and market-share decline is how quickly leadership can see the signals and act on them.
You operate a B2B services business across 50 or more branches with 10,000 or more corporate customers on recurring contracts, and revenue attrition is visible in aggregate but not actionable at the account level.
When a customer's billing declines or they depart, your organization cannot determine in real time whether the cause was pricing pressure, volume reduction, service dissatisfaction, or competitive displacement.
Revenue management levers including price revisions, credit policies, and promotional or bundled pricing are applied through manual processes without a coordinating data layer that aligns decisions with contractual obligations and market conditions.
Branch and market-level revenue performance is reported periodically in aggregates that mask variation at the account, service line, and local competitive level until the performance gap has already compounded.
Re-engagement with declining or inactive B2B accounts is not systematically targeted with data-informed pricing or bundling strategies, meaning re-engagement depends on individual sales relationship activity rather than coordinated retention intelligence.
Let us map your current churn signal visibility against your account base and show you what data-driven retention looks like at your scale.
