Prospect Qualification: 14-Signal Scoring Across Five Tiers

Every brokerage has the same problem: too many leads, not enough qualified ones. A broker with 200 contacts in a CRM and no scoring system spends the same energy on a cold lead as on a prospect who visited three property pages last week, attended a market event, and has a $50M transaction history. That is not a strategy. It is a lottery ticket dressed up as deal flow.

The traditional approach to qualification in CRE is intuition-based. Senior brokers develop a feel for which prospects are real and which are tire-kickers. This works — until the brokerage scales. When you have seventy-eight properties across three markets, intuition cannot process the signal volume. You need a system that reads data the way a senior broker reads a room, except it does so across every prospect simultaneously and never forgets a signal.

The Qualification Agent was built for this problem. It takes enriched prospect data — firmographic profile, behavior, transactions, relationships — and runs each prospect through a fourteen-signal model that produces a composite score from 0 to 100. That score maps to one of five tiers, and each tier has defined outreach rules, channel strategies, and response-time expectations. No guessing. No gut feel. Data-driven prioritization that ensures broker time goes where deals close.

Four categories of signals, each weighted by predictive power for CRE deal conversion. Weights were calibrated against eighteen months of closed transaction data across three properties.

Category 1: Firmographic data (30%)

Company size is measured by employee count and revenue, mapped to the property type’s ideal tenant profile. An industrial warehouse weights companies with 50–500 employees and $10M–$200M revenue most highly. Industry vertical scores alignment with target sectors. Geographic footprint measures existing operations in the target market or adjacent ones. Growth trajectory uses public signals — job postings, funding rounds, SEC filings — to estimate expansion likelihood.

Category 2: Behavioral signals (25%)

Website engagement tracks property page visits, time on page, and repeat visits within 30 days. A prospect who visited the same property page three times in a week scores 9/10. Content downloads — market reports, brochures, investment summaries — indicate active research. Email engagement measures opens and clicks on outreach. Event attendance at market tours and conferences signals active deal intent.

Category 3: Transactional history (30%)

Past deal volume counts CRE transactions in the last 36 months. High-volume transactors score higher because they have proven execution capability. Average transaction size is compared against the subject property’s range — a $5M average looking at a $50M asset scores lower. Time since last transaction measures recency: three months ago beats eighteen months ago.

Category 4: Relationship proximity (15%)

Shared connections counts mutual contacts between the prospect and the brokerage team. Referral source strength evaluates whether the prospect was referred by a high-value relationship. Portfolio overlap identifies prospects who already own or lease properties adjacent to current assets.

Each of the fourteen signals scores differently per tier. The matrix below shows the typical raw score a prospect needs in each signal to qualify for each tier. A prospect does not need maxed-out scores in every signal — the composite is what matters — but the matrix shows which signals carry the most weight at each cutoff.

The composite score maps to five tiers. Each tier has defined response-time SLAs, channel strategies, and escalation rules. This is not a suggestion system — it is an operational framework that dictates broker behavior.

The tier system creates a meritocracy of attention. An On Fire prospect — scoring 85 or above — triggers an immediate alert with a pre-built context brief: who the prospect is, which signals are strongest, which property they are interested in, and a recommended conversation opener. The broker does not have to research. The system already did it.

Hot prospects (70–84) enter a structured 3-touch sequence: personalized email within 24 hours, LinkedIn connection request at 36 hours, phone call at 48 hours. Each touch is pre-drafted by the Content Agent and reviewed by the broker before sending. The copy references the prospect’s specific behavioral signals — “I noticed you downloaded our DFW industrial market report last week.”

Static lists decay. A prospect list exported from a CRM on Monday is stale by Thursday because new engagement data has arrived, a company announced an acquisition, or a competitor signed a lease. The Segment Builder solves this with dynamic segments that update in real time as signals change.

A segment is defined by a composite filter across any combination of the 14 signals plus property-type preference, geographic focus, deal timeline, budget range, and tenant-vs.-buyer classification. The system supports up to 50 active segments per portfolio, each feeding its own outreach cadence.

The segment builder is not just a filter — it is a pipeline management tool. Brokers can see which segments are growing (indicating market demand), shrinking (cooling interest), or have the highest concentration of On Fire and Hot prospects. This segment-level view is how the brokerage decides where to allocate marketing spend.

Commercial real estate is a relationship business. A prospect with a score of 60 who is connected to your top three clients through shared portfolio companies is fundamentally different from a 60-score prospect with zero connections. The Relationship Mapper identifies these connections and adjusts qualification accordingly.

The mapper cross-references four data sources: LinkedIn network overlaps between the prospect and brokerage team members, transaction co-participants who appeared in the same deal as existing clients, shared property interests from viewing the same listings, and event co-attendance at market events.

Each connection type carries a different weight. A direct LinkedIn connection to a senior broker adds 5 points. A transaction co-participant with an existing client adds 8 points. Shared property interest adds 3 points. Event co-attendance adds 2 points. The maximum relationship modifier is 15 points — enough to push a Warm prospect into Hot or a Hot prospect into On Fire.

Qualification is not only about scoring prospects in — it is about flagging them out. Seven negative flags can override even a high composite score. A prospect scoring 88 with a confirmed competitor relationship flag moves to the hold queue regardless of tier.

Flags are not permanent. The system re-evaluates flagged prospects monthly. A competitor relationship flag is automatically cleared if public records show the engagement has ended. The goal is not to permanently reject prospects but to prevent wasted outreach on prospects who cannot convert today.