Lior Yadin from EntityMed discusses the use of AI technology in the aesthetic space. The technology allows patients to visualize their potential results before undergoing procedures, improving the consultation process and setting realistic expectations. The AI algorithm is trained to understand how tissues will behave post-procedure and generates a spectrum of possible results.

The technology also helps with lead generation and patient acquisition, attracting potential clients and providing a more engaging experience. The future of AI in aesthetics is expected to include simulations as the gold standard and a shift towards online purchases and consultations.

Takeaways

• AI technology in aesthetics allows patients to visualize potential results before undergoing procedures, improving the consultation process and setting realistic expectations.
• The AI algorithm is trained to understand how tissues will behave post-procedure and generates a spectrum of possible results.
• AI technology helps with lead generation and patient acquisition, attracting potential clients and providing a more engaging experience.
• The future of AI in aesthetics is expected to include simulations as the gold standard and a shift toward online purchases and consultations.

Timestamp

(00:00) Introduction and Background

(00:29) The Need for AI in Aesthetics

(01:22) How the Technology Works

(03:44) Pre-Education and Setting Expectations

(04:04) Lead Generation and Patient Acquisition

(06:04) Expanding into Other Industries

(07:28) Comparing Simulation to Actual Results

(08:21) The Future of AI in Aesthetics

(10:59) Choosing Aesthetics as a Niche

(12:09) Global Adoption of AI in Aesthetics

(13:25) Upselling and Cross-Selling

(20:24) Managing Leads and Conversions

(25:24) The Convenience of Online Purchases

(26:08) Reactivating the Patient Database

(28:06) The Shift to Inbound Marketing

(30:12) The Psychology of Buying

(31:02) Upselling and Cross-Selling Success Stories

(32:16) The Marriage of Psychology and Technology

(33:10) Conclusion and Next Steps

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