Understand  In-­‐Store  Shopper  Behavior    

with  Precise  Loca7on  Analy7cs    

#CCES14  

Webinar  Sponsored  by  

#CCES14    

Welcome  Webinar  A8endees  

#CCES14    

Follow  This  Webinar  On  Twi8er  

#CCES14

#CCES14    

About  Retail  TouchPoints  

ü  Launched in 2007

ü Over 28,000 subscribers

ü  To provide executives with relevant,

insightful content across a variety of

digital medium

Free subscription to our weekly newsletter: WWW.RETAILTOUCHPOINTS.COM/SIGNUP

#CCES14  

Consistent  Customer  Experience  

Winning  The  Ba8le  Of  Customer  

Service  Vs.  Task:  OpKmizing  The  

Customer-­‐Centric  Payroll  EquaKon    

Growing  Revenue  While  Controlling  

Labor  Cost  

CommunicaKon  Ma8ers:  Solving  

the  Store  ExecuKon  Challenge    

Conquer  the  FiRng  Room  –  

Make  the  Most  of  Your  Most  

Valuable  Real  Estate    

Understand  In-­‐Store  Shopper  Behavior  With  Precise  LocaKon  

AnalyKcs    

#CCES14    

Panelists  

Debbie Hauss Editor-in-Chief

Retail TouchPoints

MODERATOR PANELISTS

Erin Oldershaw Retail Consultant

SMK Workforce Solutions

Patrick Blattner CPO

iinside

#CCES14    

The  leader  in  passive  indoor  analyKcs  with  accuracy  within  1  meter  

7 Patrick  Bla8ner  |  Chief  Product/Data  Officer   October  22,  2014  

PRECISE  INDOOR  ANALYTICS  

#CCES14    

•  Our founders were leaders on the original Apollo Space Mission and Space Shuttle program

•  On the team that launched the first GPS satellite into space

•  We have an extensive patent portfolio with over 30 patents on proximity within indoor location

iinside Steeped History in LBS

iinside is a WirelessWERX company and has been in business for over15 years with 30 global patents around zone technology

FOUNDED  BY  FORMER  NASA  ENGINEERS  

#CCES14    

Observed  Devices  

Basket Cart Employee

Wearables

Mobile Phones

Nodes  

Bluetooth 2.0 & 4.0

We also have small Quarter size tags that can adhere to carts, baskets, and Employee Badges to capture 100% of tagged items.

Tag  

Base  StaKon  

Nodes are Chained off of Base Stations and talk to secure servers

We  see  over  500+  device  types  

HOW  WE  SEE  DEVICES  –  NON  APP  DEPENDENT  Both  Passive  Listening  Nodes  with  Beaconing  Capability  

#CCES14    

Each  sensor  is  about  the  size  of  a  deck  of  cards  

Small  Sensors  are  Easy  to  Deploy  Throughout  the  Store  An  easy-­‐to-­‐install,  low-­‐cost  soluKon,  to  the  most  comprehensive  and  accurate  indoor  analyKcs  using  Bluetooth  technology.    We  simply  place  our  small  nodes  within  locaKons  inside  the  store  and  size  the  zones  and  start  collecKng  data.  

EASY  INSTALLATION  50,000  Sq.  Foot  Store  Setup  in  One  Night  

#CCES14    

Close  Proximity  with  Bluetooth  

ACCURACY  MATTERS  

4b  

iinside  uses  Bluetooth  technology  to  passively  monitor  Bluetooth  enabled  devices  that  appear  within  proximity  of  our  sensors.    

Filtering  Out  Noise  /  Non-­‐Shoppers  

iinside  is  capable  of  filtering  out  employees  and  pass  through  customers  

Employee  TSA  Agent  Front  Staff  

Shopper  Traveler  Visitor  

From  4b.  Across  to  50  b.  Across  

#CCES14    

61%   39%  

12  

67%   33%  EMPLOYEE  AND  PASS  THROUGH  SHOPPERS  

SHOPPER  VISITS  

STORE  1  

WHY  IT  MATTERS–  PROVEN  CLEAN  DATA  SETS  Proven  by  3rd  Party  Audit  

BAD  DATA  Employees  and  Pass  Through  Shoppers  Shoppers  <  10  Seconds  Persons  >  2  Hours  

GOOD  DATA  Shoppers  Dwelling  >  10  Seconds  

STORE  2  

Within  5%  aber  24  hours  |      Within  2.5%  aber  48  hours  

SHOPPER  VISITS  

EMPLOYEE  AND  PASS  THROUGH  SHOPPERS  

#CCES14     13  

CROSS  MARKET  VALUE  &  ROI  Where  We  Leverage  Our  Accuracy  

MASS  TRANSIT  

TSA,  Baggage  Check-­‐in,  Carousel,  and  Concourse  

InstallaKons    

End  to  End  

CITY  FOOT  TRAFFIC  

Embedded  Upstream  in  Signs  

City  Behavior  

BIG  BOX  &  GROCER  

Full  Store,  Store  in  Store,  Cross  Store  

Store  Behavior  

WORLD  TOWERS  

MulK-­‐Floor  Queuing  

Trip  Time  

#CCES14     14  

WEB  ANALYTICS  FOR  THE  PHYSICAL  WORLD  Specifically  Looking  at  Retail    

#CCES14     15  

VISUAL  IMPACTFUL  ANALTYICS  WITH  VALUE  

First  LocaKon  Visited  

Most  Visited  LocaKon  

Average  Dwell  

First  LocaKon  Visited  

Most  Visited  LocaKon  

Cross  Chain  &  Single  Store  Views  

#CCES14     16  

FIRST  LOCATION  VISITED  Awareness  &  Intent  from  Offline  PromoKons  

#CCES14     17  

FIRST  LOCATION  VISITED  Awareness  &  Intent  from  Offline  PromoKons  

#CCES14     18  

FOOTPRINT  /  DENSITY  

70%  

30%  

Brand  and  Category  Interest/Square  Foot  Efficiencies  

EXAMPLE  Typical  Big  Box  Retail  

#CCES14    

70%  

30%  

19  

FOOTPRINT  /  DENSITY  

70%  

30%  

Brand  and  Category  Interest/Square  Foot  Efficiencies  

#CCES14     20  

LABOR  &  FINANCE  Efficiencies  for  Staffing  

#CCES14     21  

SHOPPER  vs  EMPLOYEE  CONCENTRATION  Engagement  Efficiencies  

Shopper Employee

#CCES14     22  

SHOPPER  vs  EMPLOYEE  CONCENTRATION  Engagement  Efficiencies  

Shopper Employee

#CCES14     23  

CROSS  SHOPPING  Referring  Traffic  

•  Format  stores  to  make  cross  shopping  easier  •  Understand  Shopper  Intent  •  Promote  an  Easier  Shopping  Experience  •  Increase  Customer  SaKsfacKon  •  Increase  Likelihood  for  repeat  visits  

#CCES14     24  

RESEARCH  BEHAVIOR  -­‐  IdenKfied  Intercept  Efficiencies  

One  &  Done  We  idenKfied  a  large  number  of  consumers  entering  the  stores,  stopping  at  1  locaKon  for  a  short  period  of  Kme  and  then  leaving  without  touching  POS  

#CCES14     25  

RESEARCH  BEHAVIOR  -­‐  Trending  Intercept  Efficiencies  

Research  vs  Intent  Driven  Shoppers  We  see  research  behavior  increase  leading  up  to  the  holidays  where  consumers  enter  1  locaKon  and  leave  without  going  through  checkout.    As  the  holiday/event  approaches,  consumers  are  intent  driven  and  research  behavior  dramaKcally  decreases  

#CCES14     26  

RESEARCH  BEHAVIOR  -­‐  QuanKfied  Intercept  Efficiencies  

Intercept  to  Convert  •  Are  Products  Stocked?  •  Is  LocaKon  Appropriately  Staffed?  •  Are  The  Products  Priced  CompeKKvely  •  Is  Staff  Trained  EffecKvely?  

#CCES14     27  

SHOPPER  SEGMENTATION  

Grocery  Store  

Informs  Lane  Types  

Basket Cart Shopper

#CCES14     28  

WHY  IT  MATTERS  –  The  Li8le  Things  Add  Up  

Lane  Hopping  Impact  •  18.1%  Lane  Hop  •  9%  Lane  Hop  Twice    

#CCES14     29  

CHECKOUT  LANE  EFFICIENCIES  

Time distribution by checkout lane shows lanes with greatest proportion of low vs high average checkout times

TIME DISTRIBUTION

Grocery  Store        

#CCES14  

Customer  Experience  

OperaKng  Model  

Service  Model  

ExecuKon  Service  

Enhancements    

Measurement  

#CCES14    

Q  &  A  |  Panelists  

Debbie Hauss Editor-in-Chief

Retail TouchPoints

MODERATOR

Patrick Blattner CPO

iInside

PANELISTS

Erin Oldershaw Retail Consultant

SMK Workforce Solutions

#CCES14    

COMING  IN  2015  

ERIN OLDERSHAW

SMK Workforce Solutions

ANNE MACKENZIE KOTRABA

SMK Workforce Solutions

Scott Knaul SMK Workforce Solutions