Pizza and Great Customer Experience - SAS · 400Mb data snack for €2.99 to see you through....

Copyright © SAS Inst i tute Inc. A l l r ights reserved.

Pizza and Great Customer Experience…Increasingly Digital!

David Williams SAS Global Customer Intelligence Practice


Great News!


But our lives have become WAY MORE COMPLEX!


So we have new needs!


Company Confidential - For Internal Use OnlyCopyright © 2016, SAS Institute Inc. Al l r ights reserved.

CUSTOMER JOURNEY 2017: Digitalization Everywhere

But, 73% of consumers also want access to actual

people, even when digital channels work perfectly.

Source: Steven van Belleghem


Itsounds

simple…

Customer Experience Expectations?

at the right time in the right place

the right thing for the right customer

Do EXACTLY


Delivering Effective Contextual Engagement

Combine the context of each interaction with the bigger picture: their full profile and history

2: Understand1: Listen

In real-time to interactions, transactions, events and sentiments. Identify needs

Just do it! Engage the customer in a timely, convenient and consistent way. Real-time or right-time. Omni-channel

4: Act

Use analytics to balance objectives, costs, risks, benefits and constraints to identify the optimal action to take

3: Decide


Delivering Effective Contextual Engagement

one central brain driving

continous improvement

multi-focus omni-channel

real-time right-time

KPIs

CX

TCO

analytics driven

contextual customer

decisioning

modular delivery

of increasing

value


Delivering Contextual EngagementMaking SMART Contextual Engagement Happen

Act

Listen

Understand

Decide


Making Contextual Engagement HappenEnabling Capabilities


Context: Defined by 360 Customer View

15

Who They Are

What They Buy & How They Use It

How They Interact with Your Brand

What They Feel & Say

Their Common Locations

Satisfaction and Loyalty

Potential to Buy and Consume

More

Current & Future

Value


Core Capabilities Required

16

Descriptive

Diagnostic

Predictive

Listen: Detect Events

Understand: Integrate Data

Decide: Apply Analytics

Act: Take Action

Online, Offline

Structured, Unstructured

Match, Merge, Purge

First Party, Third Party

Outbound

Inbound / Real-Time

Orchestrated Omni-Channel

Transactions

Channel Interactions

Opinions / Sentiments

Location

Listen / Filter / Trigger


Effective Contextual EngagementSome Examples


* 21M Active Customers, 50K TPS

Take ActionUnderstand

S1

S2

Listen

Real-time triggerLimited contextual data

Rules-driven next best offer

Real-time deliveryPoorly-defined offer

Delayed trigger Broad contextual data

Analytics-driven next best offer

Delayed deliverySophisticated offer

Real-time trigger Broad contextual data

Personalized offer driven by real-time analytics

Real-time deliverySophisticated offer

18

Real-Time Contextual Campaigning (RTCC)Data Throttle Campaign



Take ActionUnderstand

S1

S2

Listen

19

5% Relevance Convenience Max. Take Rate

5%Relevance Convenience Max. Take Rate

24% Relevance Convenience Max. Take Rate




20


Incremental Revenue Increase €10sM

Payback MONTHS

Take Rate 5x Business As Usual 24%


21

Context:

• O2 Blue All-in M

• High Value Customer

• Data usage in the last 48 hours above average

• 5 remaining days until de-throttling

Intelligent Decision:

• Analytically optimised offer

• Individualised price, volume and validity

Action:

• SMS

• App Push

Refinement:

• Based on customer response

• Analytical Model learns continuously

Event:

• Customer exhausted data pack and is throttled

Hi David, we can see you might be frustrated right now, so how about a 400Mb data snack for €2.99 to see you through. Regards


Hi David, we can see you might be frustrated right now, so how about a 400Mb data snack for €2.99 to see you through. Regards

New BI RTCCInfrastructure

Based on events, RTCC takes the individual customer context into account in real-time:

Contact customers in real-time after an event (e.g. throttle)

Create individual offers through real-time analytics

Enrich customer data with real-time network information


Banking Use Case - Xmas Shopping

22

Track customer behaviour and look for specific patterns

(i.e. 3 transactions within 30 minutesresulting in low balance)

John is shopping, hisbalance is close to

zero and he is eligible for contact

Apply business logic to

determinebest action

Deliver assistance,

encouragementor offer

3:57 pm

Offer

<1 second3:29 pm

Dress3:46 pm

Jeans3:57 pm

Scarf

Hey John! Your current balance is now €67, but we have good news. Text “Y” to activate a €200 credit extension on your account

Calculate personalized

offer parameters

Shopping =• 3 txns in <30 mins• same debit card

*

t


Xmas Shopping: Behind the Scenes Decisioning

23

Check for Card w/Headroom

Y: Encourage Card Use

N: Check for Deposit Account

Y: Recommend Transfer

N: Pre-approved O/D available?

Y: Offer O/DN: Run Credit

Risk Check

Overdraft

M,L: Evaluate Potential Offers

H: Warning

Personal Loan

Credit Card

Advise: Mobile App / Branch


Case Study –Commerzbank


Digital CRM - Project Objectives

25

An innovative marketing architecture enables Commerzbank to run a cost efficient, scalable and fully complete „state of the art“ user experience across multiple touch points. Delivering effective 1:1 dialogs:

the right message, at the right time, in the right structure, on the customer preferred device.

Technology View• Single technology - all channels • Platform drives innovation and

faster time to market• Machine & rule based learning

drives effectiveness

Execution Excellence• Efficient marketing operations • Avoid integration complexity • Avoid redundancy • Process scalability • Centralized workflows and

content de-coupling Integrated Marketing

• The RIGHT data and analytics• Intelligent 1-1 marketing via co-

ordinated multi-channel campaigns

• Seamless & relevant user experience across all channels


Real-Time Creative Marketing: An Example

Customer: British AirwaysAgency: OgilvyCustomer Analytics: SAS


Real-Time Creative Marketing: An Example

https://www.youtube.com/watch?v=ftyl4JBCPd0

https://www.youtube.com/watch?v=ftyl4JBCPd0


And Really Taken to Extremes… Guerilla Marketing!

https://www.youtube.com/watch?v=SkGaFRwIs7c&t=4s

https://www.youtube.com/watch?v=SkGaFRwIs7c&t=4s


Making Contextual Enablement HappenNew Capabilities


Core Capabilities Required

30

Descriptive

Diagnostic

Predictive

Listen: Detect Events

Understand: Integrate Data

Decide: Apply Analytics

Act: Take Action

Online, Offline

Structured, Unstructured

Match, Merge, Purge

First Party, Third Party

Outbound

Inbound / Real-Time

Orchestrated Omni-Channel

Transactions

Channel Interactions

Opinions / Sentiments

Location

Listen / Filter / Trigger


CUSTOMER INTELLIGENCE

360Managing Personalized Digital Interactions

for Customers and Visitors


Orchestrate Digital Customer Journeys

Contextual Analytical Helpers

Cloud Based SaaS


360

Digital Data Hub



360Dynamic Data

Capture

Digital Data Model

Visual Exploration & Reporting

Digital Orchestration & Execution

Standalone or Hybrid Deployment

Analytical Decision Helpers

Discover Engage


Collect All Behavioural Interactions

TransformJourneys Into

Insights

See The Full Customer

Picture

Take The Right Action For Every

Customer

CI360 Discover


Collect Digital Behavioral Interactions From Websites

Collection at the browser by just adding one single-line code insert, that never changes, to each page of your site:

<script id="ob-script-async" type="text/javascript" src="/js/ot_async.js" a=" [account-id]">

Default Event Collection (mobile and desktop browser)


Examples of Collected Web Behavioral Interactions

Page TitleFull URL

Meta Data Tags

Client Information

Referrer

Page Content


Field Interaction

Link Clicked

Form Submit

Captured when focus is moved away from form field

• Value• Form ID and Name• Field ID and Name• Number of changes

• HREF (link location)• Alt Text / Inner Text• Link location in page

(DOM PATH and CSS Selector Path)

• Value• Form ID and Name• Field ID and Name

Examples of Collected Web Behavioral Interactions


Controlling Data Capture and Collection

System Administrator controls which elements are collected

Individual fields can be excluded from selection


Collected Mobile Behavioral Interactions

•Mobile Browser•Visitor User behavior

• Users, Sessions, …

•Event detection• Page views, Shopping Cart

•Mobile App (iOS; Android)•Usage (Online & Offline)•App Experience & Engagement

• Sessions, Page Views, Product Views, Shopping Cart

•Events• Login / Identity events• Location events (beacon discovered, geofence entry, exit)

The SDK for SAS Digital Intelligence is a supporting library that enables you to add support for event collection and ad displays to native mobile applications.




Insights


Picture

CI360 Discover


Customer


Transformation

Maps events to online data mart

Easy-to-use wizards to navigate the

website

Page Loads

Clicks

Form Submits

Text Changes

Media Interactions

Page Elements

Content Changes

Collection

Online Data Mart

Out of the box VA

Reporting

Real-time Session

State

Outputs

Digital Data Transformation


Digital Data Transformation User Interface

Select Goal Configuration from Configuration Menu

Business Goal Created on URL for Online Tracking


CI360 Discover



Insights


Picture


Customer


Interactions

Sessions

Visitors

Customers

Digital Customer View


Demonstrating The Enhanced Customer View

Activity added to ECV record 1689 under cookie ABC

• Consolidated customer behavior across multiple cookies and devices• Creates and merges customer records retrospectively based on current understanding• Provides customer online activities and behaviors for all sessions


Online Data Model


CI360 Discover



Insights


Picture


Customer


CI360 Discover - Take Action


CI360 Engage


Enable marketers to benefit

from approachable and

actionable advanced

analytics to make more powerful

decisions within today’s complex

and interconnected business

environments.

CI360 Analytics Vision


PersonalizationCustomer Journey Analytics

Content Optimization

Anatomy of SAS Decisions At Scale

Key Analytical Pillars

Company Conf ident ia l - For Internal Use OnlyCopyr ight © 2017, SAS Inst itute Inc. Al l r ights reser ved.

Personalization

A/B Testing, Self-Learning Optimized Tests (MAB), Multi-Variate Testing

+

Product & Customer Recommendations

+

Testing-

Recommendations-

Segmentation-

Prediction- Personalization driven by individual prediction (e.g., Shopping Cart Abandonment prediction, Goal Achievement prediction)

+

Building out a fuller picture of the user or customer group

+


Engage: Blue Box Analytics

Automatically discovered, most distinguishing segment criteria, but also supports marketer-defined criteria

Compare members of the selected focus segment against the comparative group to identify key segment characteristics

Company Conf ident ia l - For Internal Use OnlyCopyr ight © 2017, SAS Inst itute Inc. Al l r ights reser ved.

Customer Journey Analytics

Understand cross channel customer interactions+Digital Intelligence & Customer Analytics

-

Given the choice of 2 or more company/marketer defined journeys which one is better?

+Customer Path Testing

-

Customer Journey Analysis

- Discover (bottom up) and analyze paths to conversion (at touchpoint level)

+

Marketing Attribution

- Understand important touchpoints, prediction and scenario analysis

+

Customer Journey Optimization

- Self-learning approach discovers levers that influence goal achievement

+


Customer Journey Analytics

A handy by-product of algorithmic attribution is a means to automatically discover conversion and non-conversion paths.


Customer Journey Optimization2018: The Machines Take Over

The best (and already optimized) ‘play’ or plays is determined for every interaction


Prospects to Customers. Remarket.

tim

e

Susp

ect

Pro

spe

ctC

ust

om

er

Incentivize!

Track!

Build Profile

Interest. Personalize / Test

Engagement by Source. Re-evaluate Spend.

Track!

Link!

Site Engagement. Redesign.

Site Issues. Remarket.

Track!

Target X-Sales. Omni-Channel.

Early Churn Indicators. Predict & Act.

Engagement Issues. Proactive Service Action.

CI360 Use Cases


Capabilities Extension


Enabling Effective Contextual Engagement

60

Important Considerations

Contextual Data & Analytics

End-to-End Journey Management

Multi-Focus Decisioning

Real / Right-Time Execution

Land and Expand

Omni-Channel


Any Questions?

sas.com


Thank You!

http://www.sas.com/

Pizza and Great Customer Experience - SAS · 400Mb data snack for €2.99 to see you through....

Documents

Transcript of Pizza and Great Customer Experience - SAS · 400Mb data snack for €2.99 to see you through....