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Data Analytics for Commercial Real Estate

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EDR PRISM
CORPORATE REAL ESTATE: HOW TECHNOLOGY IS RESHAPING PROPERTY RISK MANAGEMENT

This panel taps into new ways that property data is being leveraged more efficiently by corporate owners and for portfolio risk management.

Donna Salvatore, Founder and CEO, Megalytics, Inc.

Published in: Real Estate
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Data Analytics for Commercial Real Estate

  1. 1. Megalytics® Copyright© 2017 Prepared for Data Analytics for Commercial Real Estate May 7, 2018
  2. 2. Megalytics® Copyright© 2017 Megalytics uses machine learning and artificial Intelligence to access, real time, 100’s of disparate and big data sets to aid commercial real estate professionals in their due diligence on tenants, properties, locations, and submarkets. We help them reduce risk and make better decisions and optimize outcomes. What We Do © 2018 Megalytics, Inc. All Rights Reserved. Private and Confidential 2
  3. 3. Megalytics® Copyright© 2017 • Tenant Due Diligence • New, Renewal, Contraction, Expansion • Templates for Law Firms, Non-Profits, Start–ups, Banks, Insurance • Supporting material for Acquisitions & Dispositions • Submarket Analysis • Rent Roll Analysis and Property Score • Site selection for Retail • Retail, Office and MF Analytics based on location • Tenant and Portfolio Monitoring • Portfolio Balancing and Valuations • Commercial Real Estate loan analysis & stress testing Applications in Commercial Real Estate © 2018 Megalytics, Inc. All Rights Reserved. Private and Confidential 3
  4. 4. Megalytics® Copyright© 2017 • Concentric 1, 3, 5 mile rings • Drive Times • Physical site visits • Going home side of the street • Going to work side of the street • Traffic lights for QSR Site Selection for Retailers - The Old Way © 2018 Megalytics, Inc. All Rights Reserved. Private and Confidential 4
  5. 5. • Geofence property and use GPS tracking to determine where shoppers come from • Use credit card spending data to confirm the shopper purchases and trade area • GAP Analysis: consumer spending levels by retail categories outside the trade area • Determine VOIDS based on regional or national retail chains • Social media analysis to determine local search by categories • Credit Wallet and Disposable Income • Sophisticated site selection criteria driven by volume of ecommerce purchases Site Selection: New Data Sources & Approaches © 2018 Megalytics, Inc. All Rights Reserved. Private and Confidential 5
  6. 6. • Geofence property and collect data from 350 MM vehicles and devices 24/7. • Satellite based GPS tracking from cars, fleets, and cell phones • Can Geofence entire malls, or streets, or single retails stores • Can determine Customer Origins and Customer Destinations • Do they come from home or do they come from work? • How far do they drive? • Where do they go after they shop? • Do they go more on weekends or weekdays? • What time of day is the highest traffic ? What is Geofencing ? © 2018 Megalytics, Inc. All Rights Reserved. Private and Confidential 6
  7. 7. Private and Confidential 7 Customer Origins - Weekday This map (on the left) displays percent of visitors traveling to the geofenced area (to the right) on weekdays. 65% of all visitors originate from the primary trade area. Zip Code Town Name Percent of Visitors Trade Area 53207 Milwaukee 23% Primary 53110 Cudahy 23% Primary 53235 Saint Francis 19% Primary 53221 Milwaukee 6% Secondary 53154 Oak Creek 4% Tertiary 53172 South Milwaukee 4% Tertiary 53202 Milwaukee 3% Tertiary 0.2 – 1.2% 1.3 - 3.6% 3.7 – 5.8% 5.9% or more Colors indicate percent of total visitors who start their trip in this zip code. © 2018 Megalytics, Inc.
  8. 8. Private and Confidential 8 Customer Origins – Weekend Day 0.6 - 3.8% 3.9 - 8.2% 8.3 – 21.4% 21.5% or more Zip Code Town Name Percent of Visitors Trade Area 53110 Cudahy 25% Primary 53207 Milwaukee 21% Secondary 53235 Saint Francis 20% Secondary 53172 South Milwaukee 8% Tertiary Colors indicate percent of total visitors who start their trip in this zip code. This map (on the left) displays percent of visitors traveling to the geofenced area (to the right) on weekends. 25% of all visitors originate from the primary trade area. © 2018 Megalytics, Inc.
  9. 9. Private and Confidential 9 Customer Origin Comparison 0 5 10 15 20 25 30 35 40 <1 1-3 3-5 5-10 10-25 25-50 50-100 100+ PercentageofTotalShoppers Miles Traveled Weekday Weekend Day Weekend traffic tends to be destination oriented, coming from up to 25 miles away. Weekday traffic tends to be convenience oriented, traveling less than 3 miles. © 2018 Megalytics, Inc.
  10. 10. Actual Trade Area based on GPS Data Estimated Market Area Actual Market Area 10 minutes 5 minutes 3 minutes 5–8% >10%1–5%<1% Based on Drive Times
  11. 11. Megalytics® Copyright© 2017 Kearny Square Trade Area Comparison © 2018 Megalytics, Inc. All Rights Reserved. Proprietary & Confidential 11 GPS/CC Trade Area 3-Mile Radius Population 216,212 351,720 Daytime population 189,106 382,247 Population Density 9,106/sq. mile 12,442/sq. mile Number of Households 75,360 124,966 Average Household Income $66,947 $59,058 College Degree (2+ years)(%) 27% 26% The table compares demographics of the GPS and credit card based trade area to the 3-mile radius around Kearny Square. The arrow points at a part of the Passaic River. The river travels south through the middle and then down the side of the Tertiary(north) trade area. Then it wraps around the secondary trade area, curving again, separating the primary and tertiary(south) trade area. A river is a natural trade barrier which is evident in our GPS-tracking based trade area of customers traveling to Kearny Square. Although the 3-mile radius will give a good idea of the area, the Trade Area, identified by the red, orange, and yellow colors, are a more realistic view of the customers within the local area, who shop at Kearny Square. The map displays a 3-mile radius compared to the GPS and Credit Card identified trade area of Kearny Square.
  12. 12. Megalytics® Copyright© 2017 © 2018 Megalytics, Inc. All Rights Reserved. Proprietary & Confidential 12 7 Mile 5 Mile Credit card data – Actual purchases from zip codes
  13. 13. Megalytics® Copyright© 2017 Social Media Interest and Search Engine Demand Tenant Category Social Media Likes Ice Cream Parlors 159,146 Beer, Wine and Spirits 157,822 Clothing and Accessories 152,413 Shoes 148,953 Spas 146,877 Yoga and Pilates 141,645 Manicures and Pedicures 134,197 Pizza 131,706 Fast Food 131,146 Beauty Salons and Barbers 125,518 Tenant Category Search Engine Demand Auto Repair and Maintenance 122,741 Movie Theatres 40,829 Pizza 40,736 Clothing and Accessories 39,114 Shoes 39,024 American Food 28,408 Beer, Wine and Spirits 22,540 Burgers 20,553 Full Service Restaurants 15,388 Pets 14,870 The numbers in the tables above are the social media likes and search engine demand within 1 mile of the subject property. The top ‘liked’ category in the area is Ice Cream Parlors with 159,146 likes. The second highest category is Beer, Wine, and Spirits with 157,822 likes. © 2018 Megalytics, Inc. All Rights Reserved. Private and Confidential 13
  14. 14. Megalytics® Copyright© 2017 Aggregated Credit Data Aggregated by Zip code plus 4 for individuals 18 and older $317 Average Current Balance on All Retail Credit Cards 95% Individuals with Auto Loans $1,069 Average Current Balance in Collections $133,015 Average Remaining Mortgage Balance 750 Credit Risk Score (Vantage Score) Credit Information © 2018 Megalytics, Inc. All Rights Reserved. Private and Confidential 14
  15. 15. Megalytics® Copyright© 2017 Mariano’s Ravenswood Trade Area © 2018 Megalytics, Inc. All Rights Reserved. Proprietary & Confidential 15 Identified by Credit Card Purchases The 2 primary zip codes (60640 and 60625) are used for Aggregated Consumer Data Zip Code Neighborhood % of Sales % of Transaction s Trade Area 60640 (A) Ravenswood 34% 35% Primary 60625 (B) Lincoln Square 25% 21% Primary 60613 (C) Lakeview 9% 7% Secondary 60618 (D) Irving Park 5% 4% Tertiary
  16. 16. Megalytics® Copyright© 2017 Credit Wallet – Available to Spend on Credit Cards Ravenswood December 2017 Average available to spend for each zip+4 $18,911 Total $ available to spend: $128,316,799 Population Density 23,756 per sq. mile Average available to spend of individuals 18 and over $1,483 Primary Zip Codes Analyzed 60625, 60640 © 2018 Megalytics, Inc. All Rights Reserved. Proprietary & Confidential 16
  17. 17. Private and Confidential 17 Retail Data Source Categories  Cell-phone movement data for customer journey and anchor tenant  Satellite-based GPS tracking of 350 MM vehicles and phones 24/7  Credit card data on merchant side for sales history, retailer ranking, transaction size, volume, seasonality  Credit card data on consumer side to track e commerce vs. brick-n-mortar spending by retail category and geography  GPS tracking of fleet data for anchor and single tenant analysis  Social media Search for active intent and passive interests  Consumer spending by retail category down to zip code  Demographics and psychographics data over time  Credit card Debt, disposable income, credit wallets at zip plus 4 over time  Pedestrian Traffic down to street segment  Business start ups and cessations by industry to the zip code  News and social media feeds  Third-party business/individual credit reports, international credit reports  Neighborhood Scores based on education, Income, Home ownership, Employment, Spending  Individual income data by SOC code, Zip code, and employment type  New Development and Construction data, permits for residential for Home Centers  Accessibility Scores – Parking, Walking, Biking, Transit  Site history and environmental background from 1600 environmental data bases © 2018 Megalytics, Inc.
  18. 18. Megalytics® Copyright© 2017 Thank You! Get in touch with Megalytics today! Order@Megalytics.net 312-818-1930 4809 N. Ravenswood Ave. Suite 215 Chicago, IL 60640

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