Location infused insightsfor profitable relationshipsNorbert Herman – Retail Industry Solutions Group

2

You continue to see so many stats about what

consumers say; so what now?

53%

30%

48%

19%

36%

12%

0% 10% 20% 30% 40% 50% 60%

Visit social site

multiple times a

day

Post about items

purchased

2014 - Global

2014 - AUS

2013 - AUS

3

Mobile influenced shopping is enhanced with timely

delivery of messages through the shopping journey

Make data analytics

empowered

decisions with real-

time updates

Amplify your

message with metrics

driven customer

engagement

Increase your reach

with just-in-time

mobile influenced

commerce

4

A couple of 2014 stats that are highly relevant…

Source: http://techcrunch.com/2015/01/06/app-usage-grew-76-in-2014-with-shopping-apps-leading-the-way/

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Customers location sharing is on the rise

One Example: Simon Group Malls

• 200MM Mall network monthly shopper

visits with $20B+/month in

• 3,000+ unique retailers with over 25,000

storefronts

Retail Malls

Airport Malls“The Sixth Continent”

• In 2013 travel retailers sold around $60

billion of goods, according to Generation

Research, a Swedish firm

• Sales at airports alone will grow by 73%

from 2013 to 2019

19%

36%

2011

2013

2013 — Willingness to share

Social handle = 32%

Mobile # = 38%

Willing to share current location (GPS)

IBV Study 2014

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The fundamental challenge “what customers really want”

is simple to state, but difficult to prove

7

Location insights can bring you one step closer to

finding not just the perfect customer, but customer(S)

8

People cannot always explain what they want deep

down, but their location actions provide a strong signal

Life

styl

eD

em

ogr

aph

icP

ers

on

alit

y

• 32 year old • Single female with kids• Lives in Irving, CA• Long NYC stays (3 months/year)

Lilly

• Global Traveler ~200K / year• Travels business class 75%• Most global trips are to London• Prefers Delta • Uses car service in NYC not Taxi• Prefers Hilton in Time Square• Uses Amex for all purchases

• Needs

• Values

• Personality

• Social Behavior

9

Location data combined with other sources increases

the customer intent signal through the shopping journey

• Location Movement Detection•In the mall

•At different malls across US

•In the store

•In specific zones in the mall

Enters the Denver Mall (2:32 pm Sat)

• Analytics Driven Offer

Selection•Next Best Action and /

or Offer analytics based

on insights inferred from

location data

combined with other

sources

• Location Prediction•Predictive analytics for most

profitable location patterns

•Location pattern detection for

optimal timing of engagement

Enters the Mall of GA (12:32 pm 1 week later)

Dwells at

Starbucks

Enters the Denver Mall (5:12 pm 2 weeks later)

Message

based on

presence

event

Recognized

nationwide

pattern

Analytics

based

hangout

pattern

Predictive

traffic pattern

for optimal

engagement

10

Where does one get the data for mall customers?

Current Network

Coming Soon

Current Network

Coming Soon

Provided by an IBM

Partnership with

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The location data driven use cases can make an impact

to all aspects of the retail store

In-Store path enhancements

Merchandizing (shelf-fit) enhancements

Local Marketing Campaign

Enhancements

Email remarketing with BOPIS

Online (.Com) promotion

Point of Sale Based promotions

Opt-In Onboarding

Point of Sale Based Promotions

Beauty Spot promotions

Customer Input and Participation

Associate Guidance in-store

Opt-In

Anonymous

White Glove Opt-In Onboarding

Personalized events and promotions

Mobile based price checker promotions

Word of Mouth Marketing Rewards

In-Zone promotions

Store Focused Associate Driven Digital Promotions

Associate Guidance in-store

Location Insights Use Case Catalog – Traffic to store, Demand Signaling, Marketing Spend, Competition (share of customer attention)

Profitable Customer driven shelf fit

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Hangout detection allows for optimal engagement timing

What is a hangout

– Given uncertain location samples from a moving object, did the

object dwell at a space-time box for at least t time units?

– Useful for classify moving objects (e.g., daily grinder, couch

potato, globe trotter), detecting anomalies (e.g., shifts in

hangout patterns) co-location analysis (e.g., where does entity

e hangout? who did entity e hangout with?) for surveillance

applications

Solution

– Using geo-spatial toolkit in Streams / SPSS.

– Handles uncertainty in location data

– Fexible to work across multiple domains (e.g., ships, cars,

asteroids, person on foot)

Customers– Telco Malaysia, TelcoPhilippines, Telco Thailand, TelcoTurkey, Telco

USA

Spent at least 15 mins in 76m box

in some one hour time window

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Pattern detection and anomaly insights based on

location data reveals key omni-channel opportunities

Leverage Point 5:

Advocate Compensation Use platforms like Pinterest to

complement marketing efforts

through the help of the extreme

loyalist

Leverage Point 6:

Application To Person Use of the mobile platform to

send intelligent, timely & location

focused messages to mobile

users

14

Location insights will identify new profitable clusters

Rank Action Cluster % of Customers % of Spend

1 Extreme Loyalists—Profitable 9% 30%

2 Extreme Loyalists—Unprofitable 8% 18%

3 Family Shopper—Profitable 6% 14%

4 Family Shopper—Unprofitable 8% 8%

5 New Customers 7% 7%

6 Credit Inclined 6% 6%

7 Home Multi-channel 10% 3%

8 Infrequent Modern Seeker 7% 2%

9 Lapsing Occasional Shopper 17% 7%

10 Lapsed Big Basket 4% 2%

11 Lapsed One-and-done 13% 2%

12 Clearance Shopper 5% 1%

15

Lily’s language (social) and interests (location data) with

System-U analytics can enhance the message accuracy

16

A use case driven approach is needed for any data use,

omni-channel options and/or creative store experiences

Business MetricsDetermine the set of measurable

benefits that presence zones can

impact

Customer TargetDetermine the characteristics of the

prototypical customer targeted by

the use

Business ObjectiveWhat opportunity or problem is

going to be addressed by this use

case

CampaignsIdentify existing or propose

promotions needed to expose and

engage customers in the journey

System CapabilitiesDetermine the range of functions,

and analytics (current or

proposed) to support the journey

Available Data & CapabilityIdentify what data and capability is

available / being considered for this

use case

Customer JourneyDraw the customer journey that will

be addressed by this use case with

timing details

Business Case CorrelationMap out the business case logic

that will be proven by the use case

using the defined metrics

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4

1

2

5

6

7

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Use Cases with ROI in

a business objective

context