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AI-Driven Marketing Strategy Optimization for a Real Estate Company

Three real estate analysts connected an AI bot to transcribe and analyze 400 calls: a month of manual work turned into 1 day — 2 hours of report review (−97%). The strategy is now updated every 2 months instead of every 6, demand shifts are caught faster, and advertising is tuned more precisely. Industry case studies confirm 70–80% savings on call reviews.

Monthly savings:

Client

A regional real estate company (buying, selling, renting, transaction support, appraisal), operating in 10 regions of the Volga and Central Russia.

Objectives

  1. Segment the client audience.
  2. Identify the main problems, pains, and needs of each segment.
  3. Optimize the process of analyzing client feedback.

Initial Situation

Deployed AI Solution

  1. Automatic analysis of 400 calls (50 per segment) using AI.
  2. Identification of keywords and semantic core, verification with the client.
  3. Identification of client problems, needs, and complaints based on keywords.
  4. Development of evaluation and ranking criteria for inquiries considering business priorities.
  5. Identification of the top 3 inquiry groups and top 5 specific inquiries within each group.

Results

Conclusions

Deploying AI for client inquiry analysis enabled the company to accelerate target audience research 10×, receive relevant insights 3× more frequently, restructure the marketing strategy, and improve its effectiveness. At the same time, analysis costs dropped by 95%, and employee resources were freed up for more productive work.