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BEHAVIOR MAPPING

CONSUMER AND CORPORATE BUYING BEHAVIOR ANNA SHIGWEDHA, HYEHYUN RYU & SOPHIE MUTZE 3RD FEBRUARY 2014

Content

!  General Approach

!  Why Do it?

!  The Evolution of Behavior Mapping

!  Methods

-  Classical

-  Onsite

-  Online

!  Possible Concerns when Tracking Customers

!  Recommendations

!  Conclusion

2

General Approach

!  “A product of observation and a tool for place analysis

and design at the same time” (GOLICNIK/MARUŠIC, 2012)

!  Systematic documentation of location-based observations

of human activity

!  Developed by Ittelson et al. (1970) to record behavior as

it occurs in a designed setting

! spatial features and behavior

are linked in both time and space

3

Five Elements of Behavior Mapping 4

Graphic rendering of the area

Definition of behaviors observed

Schedule of times during which to

observe

Systematic procedure

Coding/counting system to minimize effort in recording

observations

Why Do it? 5

Re-design and optimization

•  Increase usability • Better staff allocation •  Increase revenues • Save costs

Tailor marketing activities to customers‘ preferences and wants

• Place communication at high-traffic areas

Gain a better understanding of customers

Predict future behavior

The Evolution of Behavior Mapping

Behavior mapping „by hand“

Use of technology

Smart technology

Behavioral matrix

Drawn behavioral map

Individual-centered map

GPS

Wi-Fi Video

Big Data

Clickstream analysis

6

LED lighting

Predictive analytics

Classical Behavior Mapping

7

Individual-centered Mapping

!  Tracking the individual's movement over time and space

8

Limited information

Social mapping: more information about perspective, attitude, and valuable places

Source: GOLICNIK MARUŠIC, B. and MARUŠIC, D. (2012). Behavioural Maps and GIS in Place Evaluation and Design.

Place-centered Mapping

!  Documenting behavior of individuals within a specified place and time

9


Behavioral matrix Drawn behavioral map

Place-centered Mapping Using GIS

!  “An electronic map used to display data based on its geographic location” (NYS GIS COORDINATION PROGRAM, 2007)

!  Analytical tool with millions of geographically related pieces of data

!  Enables organization, visualization and analysis of data

10

- Easy to update

- Represent spatial

data of behavior

patterns

- Quality of data

depends on

quality of

observation and

data entered

*GIS (Geographic Information System) Source: GOLICNIK MARUŠIC, B. and MARUŠIC, D. (2012). Behavioural Maps and GIS in Place Evaluation and Design.

GPS as a Data Source 11

Data usefulness

• Large amount • High level of

accuracy • Compatible

with GIS

• Awareness of tracking may influence behavior

*GPS(Geographic Positioning System)

Data objectivity


Observation by Video

!  Use of camera surveillance in-store

12

Source: UNIVERSITY OF CALIFORNIA (n.d.). Place-centered map.

Onsite Behavior Mapping

13

Changes of Onsite Tracking

Environ- mental change

New Methods

Enriched data

!  Average spending time

!  Revisit rate

!  Bottleneck

!  Engagement & bounce rate

!  Smartphone technology

!  Desire of retail stores

!  Increase of intermediaries

14

Advanced Video Technology

- Surveillance camera - Smartphone(MEMS)*

Drawing a heat map based on traffic

Adjusting store layouts

*MEMS(Micro-Electro-Mechanical Systems)

15

LED Lighting

Smart- phone

camera

Smart-phone

application

① Frequency

Decode the signal, determine location

Microchip is implemented Read the light

Retail store

④ Personalized marketing

Analyze location, develop campaign

② Location information

③ Consumer data

16

LED lighting

Wi-Fi

Searching Wi-Fi signal in the store

Detecting Wi-Fi signal, analyzing consumers

Consumers Intermediaries Retail stores

MAC address*

Changing layouts, developing marketing strategy

Consumer data

Service fee Wi-Fi service

Improve consumers’ experience

17

*MAC address (Media Access Control address)

Analysis of Onsite Tracking Methods

Source: GUARDIAN NEWS AND MEDIA LIMITED (2013). What information can retailers see when they track customer movement?

18

CASE: Copenhagen Airport

Source: CISCO (2012). Increasing Airport Efficiencies with Cisco Wi-Fi.

19

CASE: Copenhagen Airport

Situation

• One of the oldest and busiest airports • Need to improve capacity

management

Solution

• Passengers’ behavior mapping by Wi-Fi signal and Augmented Reality

Result

• Increased customer satisfaction • Monitored and prevented bottleneck

20

Online Behavior Mapping

21

Behavior Mapping in Online Environments

22

Factors influencing customers’ decisions

•  Product information

•  Navigation

•  Time pressure

•  Perceived risk

•  Know your customer

•  Predict behavior

•  Achieve real-time

personalization

Gathering Big Data

„Big Data is high-volume,

high-velocity and high-variety information assets

that demand cost-effective, innovative forms

of information processing for enhanced insight

and decision making.“

23

Source: GARTNER, INC. (n.d.). Definition ‚Big Data‘.

Gathering Big Data

„Big Data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.“

24

Use analytics

Decreasing storage

costs

Determine relevance

Create value

Gathering Big Data


25

Keep it fast and simple

RFID tags

Sensors

Smart metering

Gathering Big Data


26

Gathering Big Data

Internet of Things Location Intelligence Smart Data

27

Trends in 2014

Clickstream Analysis

!  How did the users arrive on the website?

!  How long did they stay?

!  What did they do during the visit?

!  When did they return?

28


Source: ONLINE BEHAVIOR (2010). How to optimize web design for conversions.

29

1.  Google Analytics

Clickstream Analysis 30

Source: CLICKTALE (n.d.). Mouse move heatmap.

2. Mouse Move Heatmap

Clickstream Analysis 31

Source: CLICKTALE (n.d.). Mouse click heatmap.

3. Mouse Click Heatmap


Source: NECTAR ONLINE MEDIA (n.d.). Products – Nectar Connect.

32

4. Behavior on Social Media


Source: NECTAR ONLINE MEDIA (n.d.). Products – Nectar Essence.

33

5. Hyper Personalized Communication

Real-Time Predictive Intelligence 34

Source: IBMSMARTERPLANETUK (2012). Smarter Analytics – Businesses Use Analytics To Find Hidden Opportunities.

Real-Time Predictive Analytics

By 2014

30 % of analytical

tools will include

real-time predictions!

!  Walmart

o  Acquired ‚Inkiru‘ in June 2013

!  SAP

o  Acquired ‚KXEN‘ in September 2013

35

Concerns & Recommendations

36

Possible Concerns When Tracking Customers

37

•  “Security camera” • Nordstrom

Lack of awareness

• Data being sold to third parties

Limited control

•  Target: pregnant teenager

Unethical targeting

Ranking of Quality

High quality Low quality

GPS + GIS Classical

approach

Video

Wi-Fi

LED lighting

Big Data


38

Evaluation of Methods

Set-up costs Follow-up costs

Quantity of data

Effectiveness Customer control

Classical approach

GPS + GIS

Video

Wi-Fi

LED lighting

Big Data


Not favourable Medium Favourable

39

Criteria

Methods

Conclusion 40

Rather than place- vs. individual-centered, categorize mapping into online vs. ofline

Methods depend on objectives/targets

Bear in mind customers’ increasing awareness and concerns regarding privacy

Advanced technology empowers behavior mapping to predict future behavior

Thanks for your attention!

41

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Sources II

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Sources III

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GOLICNIK MARUŠIC, B. and MARUŠIC, D. (2012). Behavioural Maps and GIS in Place Evaluation and Design. In: ALAM, B.M. (ed.) Application of Geographic Information Systems. InTech, pp. 113-138.

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