ELI Call Analysis + Princeton
Princeton used ELI Call Analysis to improve leasing call quality across its portfolio, giving teams clearer visibility into agent performance and opportunities for coaching. As properties adopted call scoring more consistently, Princeton saw stronger call scores and measurable gains in leasing conversion.

Challenge
Princeton wanted a better way to understand leasing call performance across properties and identify where coaching could improve prospect interactions. Without a consistent way to evaluate call handling, it was difficult to connect agent performance on the phone to downstream leasing outcomes.
Solution
With ELI Call Analysis, Princeton introduced structured scoring and review of leasing calls across the portfolio. This gave teams a repeatable way to assess call quality, coach agents on missed opportunities, and reinforce the behaviors most likely to convert prospects into residents.
Impact
9–10 point improvement in average call scores
Princeton’s properties improved from call scores in the mid-80s to the mid-90s on evaluated leasing calls after using ELI Call Analysis.
23% to 62% perfect-score calls
At one property, the share of evaluated calls receiving a perfect score increased from 23% to 62%.
81% to 97% average call score
One property achieved the largest single-property gain in average evaluated call score, improving from 81% to 97%.
52% increase in lead-to-lease conversion
As call scores improved, lead-to-lease conversion rose from 4.2% to 6.4%, while application-to-lease conversion increased from 50% to 72%.
Takeaway
Across Princeton’s portfolio, stronger leasing calls translated into stronger leasing conversion. Properties that actively used call scoring improved average call quality by nearly 10 points, and at one property, those gains carried through to higher conversion deeper in the funnel. The pattern was clear: better call execution helped teams turn more prospects into residents.
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