Webinar: Predictive Modeling: Identifying the Prospects Most Likely to Buy

by | Dec 29, 2016

Presented by:
Sue Dolton, Vice President, Sales Services, Love & Company
Kate Phelps, Owner, Taylor Reporting Solutions
Larry Wieskopf, President/CEO, Infinite Analytics
Monica McAfee, Director of Sales & Marketing, John Knox Village

Session Narrative

Being able to identify your hottest prospects through the use of predictive modeling is the next big thing in senior housing. Already this technique has revolutionized marketing in other industries. Variables such as age, distance from community, education, location of children, health, wealth, hobbies, activities completed (attendance at events, phone conversations, appointments, website activity, etc.), existing friends in the community, and involvement of lawyers, financial advisors, and children can all serve as indicators of the likelihood of a sale. Predictive modeling isn’t a euphemism for guessing which factors are most important, but analyzing past senior living data. This analysis has established that some of the key factors are intuitive, but many are not. During this webinar presentation, we will discuss two major CRMs in use in the senior living field – REPS and Retirement Homes Software, powered by Salesforce.com – and describe how each of these platforms addresses this critical functionality. We will also provide examples demonstrating how predictive modeling effectively can increase community sales and reduce marketing costs, including case studies of Life Plan Communities that are successfully doing so.

Key takeaways from this webinar include:

  • Understand predictive modeling that is currently taking place
  • Learn the buying signals and variables that could indicate a higher likelihood of conversion
  • Identify the questions to ask in discovery in order to improve predictive modeling

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