Real Estate Case Study

Business Objective

Our client is a realtor company based in a western state of India provide services to all major cities in the state. The realtor company has real estate agents in all the cities they operate. The realtor company uses multiple channels to generate leads for prospective buyers of homes(apartments/ flats/ duplexes). The real estate agents are expected to list the properties made available for sale. The company has been in the business of selling homes for over 8 years. Our client set an ambitious growth plan for the next 24 months to increase revenue by 3% and profitability by 5% by targeting an increase in
– Number of leads by 3%
– Ticket size of the transactions by 5%

Challenges

Disparate data sources, excel sheets, different accounting systems. Reinforcing process to update system daily for all transactions to increase accuracy of information. There were inconsistencies and gaps in recording information about customer background, their choices, contacts met etc…
The time between lead assignment and meetings was not tracked to understand buyer’s interest level.

Solution Methodology

We began by assimilating disparate data source and build a consolidated cohesive account tracking system for agents. Studied as-is way of working and implemented a process for agents to record transactions daily in the tracking system. The assignment of buyers to agents was happening on a round robin basis. With the available data, we found conversion rate of agents by property range and identified agents who were good at showing properties.

Introduced changes like creating buddy system to get all agents trained on showing properties, assignments to be done by property range etc.

Also implemented Customer Relationship Management (CRM) system in the organization. Tracked market data for the number of transactions happening in the area to understand client’s market share.

We analysed data from the consolidated data store (CRM and tracking system) to find pattern and factors that influenced customer behaviour and conversion, some dashboards that we created were:

  • Lead Generation Dashboard – understand sentiment and seriousness of buyer etc.
  • Property Dashboard – property characteristics, time to sell, fondness of property etc.
  • Effectiveness Dashboard – number of meeting, property visit etc.
  • Buyer Dashboard – buyer characteristics, seriousness indicator, response on viewed properties

Business Impact

Using detailed analysis of data resulting in some business decisions, our client was able to increase

  • Lead generation by 2% in first 3 months and 3% in 18 months.
  • The ticket size increased by 4% in first 12 months and 6% after 18 months.

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