Colin Green, Founder, BubbleGum BI
Real-Time Asset Management, Finally
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Guest: Colin Green, Founder, BubbleGum BI
In brief:
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Multifamily asset management is still burdened by fragmented reporting and stale data.
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BubbleGum BI consolidates property management systems, market surveys, and reputation metrics into a daily-updated intelligence layer.
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The immediate value is speed, clarity, and alignment across asset, regional, and property teams.
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Market benchmarking and renewal forecasting are shifting from backward-looking reports to forward-looking operational controls.
The reporting problem no one enjoys admitting
My guest today, founder of BubbleGum BI, Colin Green’s central thesis is that the multifamily industry still spends too much time assembling information and not enough time using it.
As he puts it, “Who likes reporting?!”
The pain point is the daily, weekly, and monthly extraction of data from multiple property management systems, rent rolls, legacy business intelligence (BI) tools, and analyst-built spreadsheets. Even today, many operators still rely on what Green calls “week old data month old, in some cases quarter old” information to make forward-looking decisions.
BubbleGum BI positions itself as a business intelligence layer for multifamily asset managers. Built originally by Green for his own use in asset management, the platform consolidates operational, leasing, market, and financial data into dashboards that refresh daily. The goal is straightforward: eliminate manual reporting friction and align everyone, from property manager to regional to asset manager, around the same numbers.
What changes when daily data replaces the Monday Morning Report (MMR)?
The interface mirrors how asset managers already think: occupancy trends against budget and market, renewal pipelines projected forward, renovation spreads visualized cleanly, and income statements accessible in real time. The difference is that the data is refreshed every day, not once a week.
Green encourages users to ask a simple question when viewing the dashboard: how long would it take to assemble this information manually?
His internal case studies suggest ten or more hours per week saved per role across asset managers, regional managers, and property managers. He admits this may be conservative, noting that manual workflows rarely proceed without friction - broken downloads, mismatched formats, last-minute edits, and the quiet procrastination of dreaded report-building.
The platform reframes the Monday Morning Report from a static document into a live operational control panel.
Can occupancy become a forward indicator?
Occupancy is typically treated as a trailing metric. BubbleGum BI attempts to reposition it as a forward-looking signal by layering budget comparisons, market occupancy benchmarks, and 30- and 60-day projections.
One particularly practical feature is renewal forecasting. Rather than waiting for retention results to hit the income statement, managers can see which renewals have been sent, what percentage increases are embedded, and what portion remains unresolved.
Green frames this as preventative management: solving income statement problems before they materialize.
Does renovation performance actually get measured correctly?
A recurring blind spot in value-add execution is tracking renovation spreads at the unit level. Ownership may underwrite $250 premiums, but realized spreads often differ materially.
BubbleGum BI integrates directly with property management systems to classify renovated versus classic units automatically, track lease timing relative to renovation completion, and visualize in-place spreads. Rather than relying on static renovation trackers, the platform monitors unit-level attributes daily.
The platform answers the question that too often surfaces too late: did the underwriting assumptions hold? If spreads flatten or turn negative, the dashboard makes that visible before capital continues to flow into suboptimal upgrades.
How is the comp set determined?
One of the more interesting integrations is with Hello Data, which provides automated market survey data sourced from property websites and listing services. Properties are ranked using a similarity score that incorporates building size, location, features, and unit characteristics. The top 15 comparables are then surfaced to smooth noise across smaller comp sets.
Executed rents are overlaid against market asking and effective rents, allowing managers to see whether pricing is drifting above market tolerance.
This is where the tool begins to resemble hospitality’s STR reports in the hospitality industry: comparing internal performance with relative positioning against a compset.
For operators managing multiple third-party property management firms, comparative analytics also extend to management company performance.
Expense categories, operational metrics, and even cancellation and denial rates can be stacked across operators and markets. The effect is subtle but powerful: data becomes the arbiter of operational discipline.
Reputation as revenue driver
Ownership groups often lack unified access to online reputation tools, particularly when using multiple management companies. BubbleGum BI pulls Google review data directly and benchmarks properties against their market.
Green notes that two-thirds of prospective renters begin their search on Google. A 3.4 rating versus a 4.5 competitor is not trivial.
The platform even calculates how many additional five-star reviews are required to reach a target score, translating reputation management into measurable operational goals.
The income statement “on wheels”
The income statement dashboard allows asset managers to access general ledger level insights in real time, whether on site or in investor conversations.
NOI trends, bad debt, overtime expense spikes - these can be identified without exporting T12s into yet another spreadsheet. In Green’s words, it becomes a “T12 on wheels.”
Export functionality allows dashboards to be converted to management-ready PDFs. Alerts and subscriptions enable exceptions-based management, pushing signals to users rather than requiring constant logins.
Where does AI fit?
Interestingly, AI currently plays a larger role behind the scenes than in the user interface.
Green states, “AI helps us build this.” Data validation, metric development, and infrastructure design leverage AI extensively. However, visible front-end automation remains measured.
He is cautious about overshooting industry comfort levels. The longer-term vision involves AI surfacing daily portfolio priorities: which assets to focus on, where spreads are mispriced, where renewals lag, where occupancy and pricing risk converge.
Ultimately, he anticipates “agent swarms” that monitor discrete aspects of portfolio performance. That future depends first on structured, clean data - the layer BubbleGum BI is building.
Bottom line
BubbleGum BI eliminates the mechanical drag of multifamily reporting. Its immediate value lies in consolidation, speed, and clarity. Its strategic implication is a gradual migration from reactive reporting to proactive portfolio management.
For asset managers overseeing growing portfolios without institutional-scale analyst teams, the shift from assembling data to interpreting it may be the real competitive advantage.
The software does not change underwriting or management philosophy. It changes how quickly reality becomes visible.
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