• January 23, 2017
  • PropMix Communications
  • 0

PropMix @ Inman Connect NYC 2017
Deciphering the lead from the noise

Richard Bellamy, CTO at Terradatum
Todd Hoover, SVP at Equifax
Umesh Harigopal, CEO at PropMix.io
Scott Petronis, Chief Product Officer at OnBoard Informatics

 

With so many leads being generated through multiple inbound channels, Agents and Brokers are at a loss to understand which is a lead that will lead to a transaction, and which ones are just trying to gauge the market without a real intent to transact. How do we enable Real Estate market participants (agents, lenders, mortgage servicers, etc.) decipher the real intent of their customers and focus attention on the leads that are most qualified?

 

The following major themes emerged from the panel discussion:

  • Inbound marketing via content and research tools are a great way to bring customers to your site, retain them, and then watch their behavior on the site to identify buyers vs. sellers. A typical home purchase takes up to 365 days from intention to transaction and so attracting and retaining a customer and continuing to qualify them is valuable.
  • Chatbots are emerging to engage a consumer, qualify them, and then transition the dialog to a live agent seamlessly. These chatbots are not just talking sentences but offering an immersive experience for the user with video, audio, action prompts, and dialog.
  • Propensity to Sell/Buy/Move predictions are another great way to qualify lead. Machine learning algorithms combine various sources of data – property records, demographics, census, and economic data – to generate such predictions and continue to validate the predictions and learn from real transaction data.

The Propensity to Sell Score combines usage, behaviour, demographic, and economic data to predict how likely a homeowner will be listing their property within a specific time period. The score is a reflection of the confidence in the prediction. With this score, Agents and Brokers can focus on the leads that really matter. This helps them close more transactions faster by dealing with those who are likely to close transactions within a specified period of time.

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