channels, operations and marketing m@ kuperholz brisbane, 10 may 2012 connecting to drive customer...

Channels, operations and marketing

M@ Kuperholz Brisbane, 10 May 2012

Connecting to drive customer experience

In God we trust…

In God we trust……everyone else bring data

The sexiest job in the next decade will be…

The sexiest job in the next decade will be…… statistician

© 2012 Deloitte Touche Tohmatsu6

The Customer Experience

Disruptive Forces Impacting Customer

Needs and Power

Channel / access device proliferation

Blurring of global boundaries

Higher customer product feature

knowledge

Increased sales & service

expectations

Ubiquitous access to

information

Social network influence

Price transparency

Data ExplosionTechnologyInnovation

EnvironmentalChange

Regulatory Reform

Reduced switching costs

Between the dawn of civilisation and 2003, we only created five exabytes of information…

Between the dawn of civilisation and 2003, we only created five exabytes of information……now we create that amount in less than two days

Between the dawn of civilisation and 2003, we only created five exabytes of information……now we create that amount in less than two days

…by 2020 every hour

Data is an asset

BIG DATA

big data

Data is an asset

Huge amounts ofData is an asset

Data is an asset

Win : Win


Data is an asset which can improve customer experience

Acquire

Store and access

Prepare and structure

Analyse

Validate and interpret

Report and implement

What?

When?

Where?

How?

Who?

Why?

What next?


Channels

Physical presence

Live events

Mail

Telephone

Web

Email

Social

Online chat

Mobile


Operations

Human resources

Customer care / contact centre

Production

Supply chain / logistics

Store placement / layout

Delivery


Marketing

Word of mouth

In store promotions

Sponsorship

Billboards / print

Mail

Cinema

Radio

Television

Web

Email

Web 2.0

Social

Mobile


Enriching with external data

Census / ABS

Property details

Household expenditure / net worth

Geodemographics / Segmentation

Loyalty Programs

Data aggregators

Market research

2012 : GaSoLoMo


Socialytics

“The Big Shift” and increasing social capital

Social network analytics

Unstructured and structured data



Acquire

Store and access


Analyse



What?

When?

Where?

How?

Who?

Why?

What next?


Text analytics


Social Network Analysis


Reporting, statistical analysis and geospacial


Artificial Intelligence and other advanced techniques

11 Suncorp © 2011 Deloitte Touche Tohmatsu

Indicative insights –S6, 7 Highest penetration: seek to “own”S5 Underpenetrated; immediate focus

S1 Emerging value; next best offerS4 Savings to Term; up-sell “lock-in”

S2, 3 Optimise margin: selective growth


MAKES PURCHASE


MAKES PURCHASE ACTIVE CUSTOMER


MAKES PURCHASE ACTIVE CUSTOMER IS MALE


CATEGORY SPEND BRAND PERCEPTION HOURS USED


Segmentation

Holistic and simultaneous consideration of all attributes

Assumption free

Hierarchical clustering : GRANULARITY aligned with capacity to act


Self Organising Map (Artificial Intelligence) videos

Technical

http://bit.ly/saxaHK

Business

http://bit.ly/Kla4Z5

http://bit.ly/saxaHK






Acquire

Store and access


Analyse



What?

When?

Where?

How?

Who?

Why?

What next?

Test and Learn



Acquire

Store and access


Analyse



What?

When?

Where?

How?

Who?

Why?

What next?


Large Financial Institution : target marketing customer case study

Profile, Segment, Target : 10,000,000 customers based on 17,000 metrics derived from data assets relating to Channels, Operations and Marketing

• Deliver 17 targeted lists and models for Bank

• Retention

• Upsell

• Cross-sell

• Each model consisted of a marketing objective, primarily a targeted cross-sell product or service

Offer Group Segment

E TDCT customers with shallow money-in product portfolio with us

4 Offers

D TDCT chequing customers who are likely to attrite

4 Offers

4 Offers

B TDCT customers who currently have a chequing account

1 Offer

CTDCT customers who have short tenure 9-24 months and have a

chequing account

Sub-Segments / Offers

A TDCT customers who currently have an unsecured credit product

4 Offers


Granular segmentation assigned customers into 40 segments

C22

C4

C40

C37

C1

C33

C27

C31

C32

C26

C3

C39

C9

C2C8

C24

C11

C34C25

C6

C30

C35C10

C20

C13

C5 C14 C19

C16

C17

C15

C18

C12

C28

C38

C21

C29

C7

C36

C23


Tenure, gender, age

• Two main typologies of TD WaterHouse customers

• New and young customers are predominantly found in the bottom right hand side of the SOM model.

• Less affluent customers tend to be found along the bottom part of the SOM model.


Product holdings

44

Mortgages Line of Credit Visa

• Generally the customers with investments are high value, older and have a longer tenure – but there are pockets of younger/newer customers who also have investment products.

• Visa product held by both high and low profit customers as well customers with both deep and very shallow banking relationships.

Investments Demand Loans


Risk and value

45

Other FI Utilization

Total average chequing balance- 6 month average

NSF FeesBeacon Score

Total Money In Total Money Out

• Highly utilized, high NSF fees, high risk customers

• Older and long tenure customers tend to have higher than average chequing account balances

• Investment customers with high total money-in balances


Changes over time

46

Future log increase in product holdings Future log increase in investment balance Ezyweb transactions as a percentage oftotal channel usage (Historical 6 months)

Future log increase in chequing balance Future log increase in Visa balanceEzyweb transactions as a percentage oftotal channel usage (Future 6 months)

• These are a cluster of older customers who are taking money out of their investment accounts probably to spend during retirement.

• There are strong clusters of customers whose visa balance has increased over the year.

• New customers tend to increase their chequing balance the most, the customers who reduce their balance tend to attrite

• This cluster of customers have the number of product holdings increase over the one year period. They are also younger customers who have some investments.

• • The usage of Ezyweb as a percentage of total channel usage increase over the year for this cluster. This top cluster is majority TDWH customers. There are several smaller clusters as well.


All Offers

A1, A3, E1, E3 – Cluster 1

A3, B1, E2 - Cluster 1

A1,A2,A4,Z3,E1,E2,E3,E4 –Cluster 1

A2, A3, E2, E3 – Cluster 1

A1, A4, Z3, E2 – Cluster 1 A1, A4, Z3 – Cluster 1

A1, E1, E2 Cluster 1 A1 – Cluster 1 A1, Z3 - Cluster 1

B1, Z1, Z2 – Cluster 2

A1, A2, Z3, E3 - Cluster 1

A1, A3, E1, E3 –- Cluster 2

A1, A4 – Cluster 1 E1 – Cluster 3

A1, A3 –- Cluster 2

A1, D1 – Cluster 1

A1 – Cluster 4

D1 – Cluster 1

Z1, Z2, E1, E3, E4 – Cluster 1 B1, D1 – Cluster 1

A1, A3 - Cluster 1

A2, Z3, E1, E3 –Cluster 1

A1, A3, E1 –

Cluster 1

B1 –Cluster 2

A1, E1, E3 –

Cluster 1

A1 –Cluster 2

A4 – Cluster 2

B1 – Cluster 1

B1, Z1, Z2 -

Cluster 1

Z1, Z2 – Cluster 1

Z1 – Cluster 2

D1 – Cluster 2

Z1, Z2 –Cluster 2

Z3, E1, E4 –

Cluster 1

Z3, E1, E4 –

Cluster 2

A2, Z3, E1, E4 - Cluster 1

E1 –Cluster1

E4, E1 –Cluster 1

E3 – Cluster 1 A1 –

Cluster 3

E4 –Cluster 2

A2, Z3, E2, E4 – - Cluster 1

A3, Z3, E1, E4 – Cluster 1

A1, Z3, E1, E2, E3 - Cluster 3

A1, D1, E1, E3 - Cluster 1

Z1, Z2, E1 –Cluster 1

B1, Z1, Z2, E1 -Cluster 1

B1, Z1, Z2 -

Cluster 2

3. We identified segments of opportunity

• Segments identified based on sales, response to marketing, product, pricing and brand performance

• We then characterised the segments defining their distinguishing attributes, example:

Large Global FMCG Organisation – Promotional, marketing and pricing

• Lower sales

• Year on year decline

• Categories 1, 2, 3 over represented

• Low volume per household

• High advertising activity (TV and radio) with lower incremental return

• Weak competitor brand positioning

• Higher income earners

• Above average membership of Segment Y

1. Problem Statement

Situation Pricing / marketing strategy to maximise return on promotion spend

Goal Make decisive marketing, promotion and pricing choices in order to grow

Challenge What drives customer purchases? Where are we over-investing? Where should we invest? How?

4. We helped embed the model into their marketing and sponsorship plan

We have embedded the model with the marketing and strategy teams who refresh the model on a regular basis to measure performance.

2. Granular customer insights

We modelled the purchase patterns of 10,000 stores with ~ 700 attributes simultaneously to identify 46 granular segments, with a focus on return on promotional spend.

We also overlayed promotions, marketing, pricing, TV, radio, online, social media, weather data and more to identify and predict effects of marketing

5. Interventions were Identified to reallocate marketing spend, channel mix and pricing adjustments

- Withdraw promotional spend from X segments with, low market share and no clear intervention strategy to rectify

- Pricing adjustments in areas with low price elasticity

- Channel and promotional brand and sponsorship mix tuned based on granular segment insights

Segment 4

• Reasonable sized sales

• Year on year growth in value and volume

• Generic split of categories

• High volume per household

• Low advertising activity on television with high return

• Competitor brand positioning growing

• Lower income earners

• Above average membership of Segment X

An unforeseen opportunity– how should we engage the distribution channel and end consumer to capitalise on the growth?

Segment 5

A market of no excuses – how do we negotiate and drive improved distribution? How best to improve Marketing ROI?

Analyse & Interpret Design Interventions Execute Campaign


Airline targeted marketing

Granular Insight


Situation: Incumbent under threat

Goal: Increased share of wallet

Challenge: Who is the true customer? What is their travel behaviour? How can we improve loyalty?

3. Setting Growth Priorities

We aligned market growth priorities to the organisation’s overall strategic objectives

Prioritising which segments to target for maximum growth

Quantifying growth goals against segment priorities

4. We Defined the Intervention Program

We defined a program of personalised campaigns for customer acquisition over a 12 month program


2.7m customers, 30 months of history to trace customer behaviour:

Domestic, international, leisure business; corporate, SME, retail

Product (fare, route, Valet, QC) Value (revenue, price sensitivity)Booking (ltime, channel, checkin) Points usage Campaign response

5. We refresh, test & refineWe refresh the segmentation to measure

program effectiveness, respond to shifts in behaviour & re-align for sustained growth

Strategic Alignment Agile Execution & Measurement

© 2012 Deloitte Touche Tohmatsu

Granular Insight


Situation: Increased competition

Goal: Improve service whilst lowering cost to serve

Challenge: How do we best meed the needs of customers to drive online adoption?

3. Defining adoption strategy

We prioritised key segments & defined relevant strategies for online adoption:

• We articulated the value proposition that best aligned with customer needs & behaviour;

• We tied this to quantified benefits for lowering cost to serve.

4. We designed the Interventions

We improved specific business processes and online user experience flows to support key market interventions for adoption


We developed a granular segmentation model to understand the long-tail of cross-channel customer behaviour: across all aspects – transaction, product, channel, attitudinal & demographic

5. We designed targeted campaigns for execution

We drove into the segmentation model to select customer lists and execute targeted cross-channel campaigns for adoption

Agile Strategy Targeted Execution & Measurement

Telcommunications company marketing strategy for digital adoption

Questions?

Channels, operations and marketing

M@ Kuperholz Brisbane, 10 May 2012

Connecting to drive customer experience

channels, operations and marketing m@ kuperholz brisbane, 10 may 2012 connecting to drive customer...

Documents

asset slide

purchase slide

deloitte touche tohmatsu

male slide

days slide

geospacial slide

gasolomo slide

statistician slide