Call Transcript Analysis Doubled Implant Patient Value

NLP analysis of call transcripts revealed insurance-driven waste and led to a 31% lift in implant starts.

At a Glance

  • Practice: Multi-location dental group

  • Market: Suburban metro

  • Ad spend: $40k/month

  • Timeline: 90 days

  • Stack: Call tracking + NLP analysis + MMM

  • Primary challenge: High lead volume but low implant conversions

Key Insight

Call volume wasn’t the problem — lead intent was. Analytics uncovered wasted spend invisible in traditional reports.

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Increased Implant Case Starts
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Average Patient Revenue

Problem

A dental group ran implant campaigns but felt results were weak despite steady calls. People were inquiring about implant procedures, but the conversion from inquiry to patient was poor.

Approach

QuantiMedia analyzed call transcripts using natural language processing to detect intent. MMM and NLP confirmed most “leads” were insurance-related inquiries – not ideal for implant cases. Campaigns were refocused around cash and financing options.

Results

Within 90 days, implant case starts rose 31%, while wasted spend on insurance calls dropped. Average revenue per lead doubled as campaigns honed in on true implant intent.

Benefits

1

Voice of the Lead via NLP Analysis

Instead of just measuring call volume, we analyzed the content of calls using NLP. This revealed that many “leads” weren’t prospects at all — they were insurance inquiries. By understanding what callers were actually saying, we were able to eliminate unproductive traffic.

2

Waste Reduction That Preserved Budget

Insurance-related traffic accounted for a large chunk of wasted spend. By removing it, we freed up resources to target implant patients, which produced stronger ROI without requiring an increase in ad budget.

3

Revenue Quality That Doubled Case Value

With more of the right patients coming through, the practice doubled average revenue per lead. This created a higher return on the same spend and allowed the business to scale more profitably.

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