MONTHLY REPORT FOR PHYSICAL RETAIL. Retail Performance Pulse. Year-Over-Year Report January 2015

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1 MONTHLY REPORT FOR PHYSICAL RETAIL Retail Performance Pulse Year-Over-Year Report January 2015 February 4, 2015

2 Average Year-Over-Year Growth/Decline January ended the 2014 retail year with a 7.7% decline in both sales and traffic. Average transaction value and sales per shopper both decreased slightly by 0.1%, and conversion increased by 0.2%. The month started off slow with a relatively steep decline of 8.5% in traffic and 11.4% in sales in the first week. The last week of the month saw relatively stronger performance with upticks in average transaction value and sales per shopper (see page 4). $ Sales Traffic Trans. Conv. %Return ATV SPS (% points) (% points) January -7.7% -7.7% -7.6% 0.2% -0.7% -0.1% -0.1% December -6.5% -7.1% -6.7% 0.3% -1.0% 0.2% 0.5% November -11.0% -11.4% -11.7% 0.1% -0.6% 0.9% 0.4% October -3.1% -4.5% -1.7% 0.8% -1.0% -1.3% 1.8% September -4.1% -5.9% -4.6% 0.3% -1.1% 0.7% -0.4% High & Low Days of January 2015 The Saturday before Martin Luther King Jr. Day (17 th ) experienced the highest levels of traffic and transactions in the month. Sales and average transaction value were highest on the last day of the month (31 st ). The threat of snowfall and wintry conditions during these specific periods drove traffic into stores to purchase seasonal goods across much of the nation. The lowest sales, average transaction value, and sales per shopper occurred on the 6 th. High Low $ Sales Traffic Trans. Conv. %Return ATV SPS Sat Sat Sat Thu Mon Sat Fri Tue Tue Tue Tue Sat Tue Tue January 2015 S M T W T F S RETAIL PERFORMANCE PULSE COPYRIGHT 2014 RETAILNEXT CONFIDENTIAL & PROPRIETARY 1

3 Varied temperatures and weather conditions across the nation allowed for mixed results for brick-and-mortar sales performance. Severe weather and snowfall across the Northeast caused a significant decline in traffic and sales in January. WEST Traffic -6.8% Sales -9.3% Conv. 0.3% ATV -3.3% SPS -2.8% MIDWEST Traffic 0.1% Sales -4.7% Conv. 0.1% ATV -3.3% SPS -4.9% NORTHEAST Traffic -12.8% Sales -10.9% Conv. 0.2% ATV 3.2% SPS 2.0% SOUTH Traffic -9.5% Sales -7.0% Conv. 0.5% ATV 1.5% SPS 3.2% Key Regional Takeaways The Midwest was the only region with a year-over-year traffic increase of 0.1%. Weather in the region was the warmest since 2003, supporting traffic into stores. Sales declined by 4.7%, driven by flat conversion and a reduction in ATV of 3.3%. The South faced traffic and sales reductions of 9.5% and 7.0%, respectively. Relatively strong increases in conversion of 0.5% and ATV of 1.5% helped temper the decline in sales. Traffic in the West declined by 6.8% and sales fell by 9.3%, despite a slight uptick in conversion. ATV fell relatively steeply, by 3.3%. The Northeast saw the steepest decline in traffic and sales of 12.8% and 10.9%, respectively. Severe weather and snowfall for part of the month hindered shoppers traffic into stores. SPS increased by 2%, however, indicating higher consumer confidence once shoppers entered stores. *Regional analysis include only retail chains with presence across all regions **Conversion shown in percentage points Weather highlights provided by RETAIL PERFORMANCE PULSE COPYRIGHT 2014 RETAILNEXT CONFIDENTIAL & PROPRIETARY 2

4 *4-5-4 weeks starting Sunday to Saturday RETAIL PERFORMANCE PULSE COPYRIGHT 2014 RETAILNEXT CONFIDENTIAL & PROPRIETARY 3

5 Glossary Sales: Traffic: Transactions (TRN): Conversion (CVR): %Returns: Average Transaction Value (ATV): Sales Per Shopper (SPS): Customer sales net of returns Total number of shoppers Sales transactions and returns transactions Sales transactions as a percentage of traffic Returns transactions as a percentage of total transactions Sales divided by transactions Sales divided by traffic Methodology 14+ million shopping trips were analyzed in data sets across specialty and larger format retail stores within the continental U.S. Regional analyses include only retail chains with presence across all regions. Note: Regions were reclassified in April Periods defined according to Fiscal Retail Calendar Previous Period: Jan 5 th 2014 Feb 1 st 2014 Current Period: Jan 4 th 2015 Jan 31 st 2015 Disclaimer This report and all information contained herein (collectively, the Report ) constitutes the proprietary information of RetailNext, Inc. ( RetailNext ) and/or its licensors, and is protected by U.S. and international copyright law. All rights reserved. You agree not to reproduce, retransmit, disseminate, sell, distribute, publish, broadcast, circulate or commercially exploit the Report in any manner without the express written consent of RetailNext. The Report is for informational purposes only, is not intended to provide tax, legal or investment advice, and does not constitute a solicitation by RetailNext, its licensors, or others of the purchase or sale of securities. THE REPORT IS PROVIDED AS IS, AND RETAILNEXT EXPRESSLY DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, ACCURACY OF ANY THE CONTENT OR MATERIALS PROVIDED HEREIN, FITNESS FOR A PARTICULAR PURPOSE, AND NONINFRINGEMENT. IN NO EVENT WILL RETAILNEXT OR ITS LICENSORS BE LIABLE TO YOU OR ANYONE ELSE FOR ANY CONSEQUENTIAL, INCIDENTAL, SPECIAL OR INDIRECT DAMAGES (INCLUDING BUT NOT LIMITED TO LOST PROFITS, TRADING LOSSES AND DAMAGES THAT MAY RESULT FROM INCONVENIENCE, DELAY OR LOSS OF THE USE OF THE REPORT) EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

6 About RetailNext RetailNext is the leader in Applied Big Data for brick-and-mortar retail, delivering real-time analytics that enables retailers, shopping centers, and manufacturers to collect, analyze, and visualize in-store data. The company s patented solution uses bestin-class video analytics, Wi-Fi detection, Bluetooth, data from point-of-sale systems, and other sources to automatically inform retailers about how people engage with their stores. The highly scalable RetailNext platform easily integrates with promotional calendars, staffing systems, and even weather services to analyze how internal and external factors impact customer shopping patterns, providing retailers with the ability to identify opportunities for growth, execute changes, and measure success. RetailNext measures the behavior of more than 1 billion shoppers per year by collecting data from more than 65,000 sensors in retail stores and analyzing trillions of data points. Headquartered in San Jose, CA, RetailNext is a growing global brand operating in over 40 countries. linkedin.com/company/retailnext W RetailNext.net H E A D Q U A R T E R S 60 S. Market Street, 10th Floor San Jose, CA p: f: A P A C O F F I C E 435 Orchard Road 11/F Wisma Atria Singapore p: f: E M E A O F F I C E 1 Euston Square 40 Melton Street London NW1 2FD p: