Master the Prospect-to-Resident Journey with Predictive Analytics



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Transcription:

June 24-27, 2015 Mandalay Bay Resort & Convention Center Las Vegas Master the Prospect-to-Resident Journey with Predictive Analytics NAA Education Conference 2015

Agenda Introduction Predictive analytics in Multifamily Housing Customer lifecycle analysis Choosing your tools Metrics for data-driven business decisions Takeaways Q&A

Chris Eckert, G5 INTRODUCTION TO PREDICTIVE ANALYTICS

What are Predictive Analytics?

What are Predictive Analytics? The use of data to answer a question based on the probability of its occurrence

Why Do Predictive Analytics Matter in Modern Marketing? Replace hunches with data Credit scores Insurance premiums

Analytics that used to reduce risk, are used by marketers to decrease the length of the sales cycle

$1.1 Billion

Lisa Trapp, Sequoia Equities PREDICTIVE ANALYTICS IN MULTIFAMILY HOUSING

Are All Leads Created Equally? How are your leads scored today? Is there enough time in the day to effectively follow up on all leads? Are they modeled to advise your associates on how to communicate with prospects?

Set Expectations and Exceed Them

Create a Realistic Vision and Act Guide on-site team s time management Create a scoring system for leads

Most Companies Still Struggle 33% use predictive analytics to make business decisions 66% have appointed Chief Data Offers Source: Accenture

Audience Poll Are you using either scoring or predictive analytics today?

ROI is the Goal 57% are quite satisfied or very satisfied with predictive analytics ability to improve ROI Source: Accenture

Biggest Challenges in Predictive Analytics Erroneous data Capturing data on differing platforms Unreliable tools Understanding the customer and the customer journey

Biggest Opportunities in Predictive Analytics Prioritize the best leads Know their lead source What will their conversion rate be Predict renewal with satisfaction scores

Notify Your Leasing Agents of a Good Lead and a Better Lead

Sequoia Equities Case Study: Leads per Post on Craigslist

Sequoia Equities Case Study: Social Media Referrals Convert

Predict Behaviors Based on Personal History

Customer Journey Mapping Five stages 1. Persona development 2. Map key touch points 3. Validate the hypothesis 4. Ideation 5. Measurement and optimization

Lisa Trapp, Sequoia Equities CUSTOMER LIFECYCLE ANALYSIS

Are the Days of Incentives Over?

Today s Resident Values Relevance and Service

The Path to Revenue Optimization Step 1: Know your customer persona Who are they? What makes them take action? What keeps them engaged?

Jessica 32 years-old Lives alone No children Has a dog College degree Income is $122k

The Path to Revenue Optimization Step 2: Understand the customer journey Screen or Rent Online

The Path to Revenue Optimization Step 3: Benchmark your touch points and track engagement Sites Search Social Advocacy (reviews)

The Path to Revenue Optimization Step 4: Layer measurement on top of trends, on top of analytics Frequency What behaviors precede that decision? Engagement How do they engage with us? Using which channels? Duration How long does that take between interactions? How long does each interaction take?

Audience Poll Do You Know Your Path to Revenue Optimization?

Chris Eckert, G5 TOOLS FOR DEVELOPING PREDICTIVE ANALYTICS

Cheap, Fast, or Free But Not All Three

Completeness of Solution Tools for Developing Predictive Analytics Sites Search Social Google Universal Analytics Call Tracking Packages Reputation.com Moz Pro Reach Local Moz Local Crazy Egg Hootsuite Facebook Insights analytics.pintrest.com Predictive Value

Lisa Trapp, Sequoia Equities METRICS FOR DATA-DRIVEN BUSINESS DECISIONS

Capture Metrics Your CEO Wants to Understand Length of sales cycle Volume of leads by source Cost-per-lead Cost-per-lease Social and anecdotal data

Inform a Variety of Business Decisions Maintenance Leasing office Human resources Hiring

PREDICTIVE ANALYTICS CHECKLIST

Predictive Analytics Checklist Define key digital touch points Know these touch points Measure and engage Monitor the customer lifecycle, for all properties Collect data, measure data, then infer conclusions Check your hypotheses and take corrective action as needed

Chris Eckert: Chris.Eckert@GetG5.com Lisa Trapp: Ltrapp@Sequoia.com THANK YOU