Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Data Analytics driven Customer Experience Programs
1. 1
Data Analytics driven Customer Experience Programs :
Measurable Impact across the Customer Lifecycle
Dr. Vinod Vasudevan, CEO
@Flytxt. All rights reserved.
2. 2
The ‘Customer Experience’
It is about what the customer feels/perceives
Not just rational elements but emotions play a significant role
It is not just about transactions but the whole journey
“How customers perceive their interactions with your company.” – Forrester
“Customer experience (CX) is the sum of all experiences a customer has with a
supplier of goods and/or services, over the duration of their relationship with
that supplier” -- Wikipedia
Cannot fully control customer experience
Can influence it significantly. - Pays rich dividends
3. 3
Customer Experience Management: Influencing each
Individual Journey
Consistent
Customer experience
Persona-driven
Across Lifecycle
Contextual
Pro-active care
Who is the customer?
Young, female, migrant, HVC, Malay speaking, Dubai
Which stage of lifecycle?
New, handholding, data-growth, hold
What is the current context?
Time, location, channel, power on, first call,
LTE handset, web page
What are the customers expectations?
Personal affinity, segment affinity, propensity,
cross affinity
1
2
3
4
Each individual’s journey is unique.
Same events would evoke different emotions in different individuals
Same events would evoke different emotions in different contexts
4. 4
MAN
1. Integrate & process all and any data
2. Full-Spectrum of analytics
3. Real-time decisioning and online experimentation
4. Man-Machine Collaborative Decisioning
Patent pending Decisioning Logic Units (DLUs)
technology framework
Proprietary Global Propensity Associations
(GPAs) consulting framework
1. Action oriented Analytics & Telecom Expertise
2. Faster & Smarter end-to-end program
Flytxt CEM Solution: Technology + Consulting + Execution
FASTER, MORE EFFICIENT, EASIER
5. 5
Persona driven Customer Engagement
Personas of
same person
360 degree persona driven engagement
Touch point personalization
Personalized Service/content recommendation
Lost intent revival
1
6. 6
Pro-active Customer Experience Management
Churn – breach of
expectation
Churn – absence of
expected experience
Churn -
dissatisfaction
Churn – carried away by
market forces
Increased
usage
Increased
uses
2
Acquisition Handholding Usage phase 2 Usage phase 3 Migration phase Revival phaseUsage phase 1
Carefully follow the customer journey to create customer
experience at every stage
7. 7
Customer Experience Programs across Life
Cycle stages
2
Prepaid
Postpaid
Etc..
Hold
Cross-Sell
Up-Sell
Retain
Arrest, Etc.
Voice
VAS
Data
Roaming
OTT, Etc.
HVC
MVC
LVC
Custom, Etc.
Recharge
Usage
Subscription
Handset
Location
Cust.Care
Network,
Etc.
IVR
Push Channel
VAS Insert
WAP
WEB
In-bill
In-Store
In-App, Etc.
Type Objective Services Profiling Context Touch Points
Category Construct
Advocacy Phase
Delighted customer
brings in more
customers
1
Value
Time
2
3
4
5
6
7
Whom to
acquire
Customer
Joins
Acquisition
Phase
Handholding
Phase
Usage Phase-1
How good is the
Service Experience?
Usage Phase-2
retain the right
customers
Migration Phase
Prepay Post-pay
Post-pay Prepay
Neglect Phase
Predict churn & retain
the right customer
Customer
Churns
Baby care/ kindergarten campaigns, data pack,
friends and family campaigns
Elite Campaigns, Free minute, Happy hour
campaigns, pack upsell, CRBT, new service
promo campaigns
Upsell/ cross-sell offers, rate-cutter
packs, happy hour calling, RMGM
Renewal campaigns, talk more
offers, happy hour, loyalty offers ,
free minutes ZMU revival, recharge
offers, retention offers
Campaign Library across Life cycle
8. 8
Real-time Contextual Actions
Location, channel, time, device,…
Ability to convert events to triggers and act on them in real-time by
heuristic analysis, soft clustering, affinity analysis,…
3
9. 9
Example of Contextual Customer Engagement
Objective:
Up-Sell special Internet Recharge pack through recommending next best
action/offer based on the trigger obtained by the subscriber action.
Target:
Subscribers
using Facebook
Pack
Low data usage
Data enabled
Handset
Subscriber trying
to check the new
game which is
outside Facebook
Auto App
Launched
Gets Instant
recommendation of
various special offers
Redirected to
offer Page
Recharge
Instantly
Single App for recharge,
offer recommendation
and balance check
3
11. 11
Prescriptive Recommendations and Actions
Few Prescriptive analytics use cases
Best fit spot offers - segment affinity, individual affinity, product group
affinity
Auto discovery of apps/services for customers
Proactive churn mitigation
Customers of Same
Segment Group Products
Offer
A
Offer
B
Recommend Offer B to the other subscriber of the
same segment because of segment behavior
Customers of Same
Segment Group Products
Offer
A
Offer
B
Other Subscriber of same segment group now
purchased offer A
4
12. 12
Persona + Expectation + Context + Prescriptive = Better Fit!
0
5
10
15
20
25
ConversionRatein
Jul-2012(in%)
Circles
Rule-based campaign Best-fit recommendation (fair)
Offers:
Data Plan, 3G plan, VAS usage,
International Calling packs, Bundle
offers, Recharge stimulation, Seeding,
ebill subscription etc……
Channels:
IVR, SMS insert, In store, Retailer, WAP
portal, Customer care portal, ODP
Personas created:
CLV (HVC, MVC, LVC), Volatile,
Early Adopter, Frequent Handset Changer, Heavy
Data user, Social Media Fan, Bollywood Fan,
Music Fan, Sports Fan, potential ipad buyer,
International Caller Etc…
Objectives:
Cross sell, Upsell, Stimulate
recharge/usage/Service adoption Etc…
13. 13
Example Case Study: Touch Point Personalization
Subscriber Profile – 60+ Million base
Data volume/Day -175 billion ‘rows’ at a data integration
frequency of 5 Minutes to 24 Hrs.
Peak Throughput – 1533 Recommendations per second
Total 8 Touch Points Personalized – IVR, webPayment, Retailer,
USSD, SOMA (prepaid system), ASCC, MBR, ODP
System Specifications
Impact Generated
1185 MN Recommendations
8 touch-points personalized
12 MN Unique conversions (~20% subs)
1.4% incremental revenue
14. 14
Measurable Impact: 2 to 7% Economic Value Delivered
Consistent touch point personalization: 1.4% incremental revenue
Customer experience programs across lifecycle stages: 12% subscribers
converted from floaters to stable users over a 6 month period
Real-time contextual customer engagement: 105% increase in conversions
AON increased from 2 to 3.5 months through baby care campaigns
0
1
2
3
4
5
Control
Group
Target
Group
Conversion%
Random
assignment
through
customer
targeting
Target group
Control group
Exposed to actions
& offers
Not exposed to
actions & offers
Target
customers
15. 15
Flytxt Overview – About Us
Our vision is to create >10% measurable economic value for CSPs through Big Data Analytics
Flytxt solutions increase revenues, margins and customer experience for CSPs
Serving many large CSPs across continents totaling 500M+ subscribers, via a mature CTE model
Proven: 2% to 7% economic benefit to customers
Headquartered in Netherlands, Corporate office in Dubai, Global Delivery Centre's at Trivandrum and
Mumbai; and presence in London, Kuala lampur, Lagos, Nairobi, Dhaka & New Delhi
Vision, Mission & Impact
Customers (50+ Customers, 32 Countries)
Brands
16. 16
500+
Million
Subscribers
Flytxt in Action
440 Million Prepaid
Customers
60 million Postpaid
customers
25 Million data
products sold in
2012-13
0.3 Million mobile
money transactions
for a leading CSP
2 multi-national
group level
framework
agreements
3 out of global top
15 CSPs based on
revenue (Q1 2013)
50+ CSPs
across 32
countries
300+
Million
products
sold in
2013
$350
Million
Incremental
Revenue till
now
750K+
Segments
served
33% usage
enhancement for
Kenyan CSP
Churn reduced by 25%
for South Asian CSP
>300% ROI on mobile
Ad campaign for
handset upsell
1 Billion segment-of-
one personalized
recommendations
served in one CSP
300K opportunity
segments served in a
year at single CSP
Sample text
Awards & Achievements
IEEE Cloud
Computing
Challenge
B.I.D International
Quality