Get closer to your customers
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Get Closer to your Customers Turn your data into valuable interactions that your customers expect!
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Learn how you can leverage your data to know your customers better, in real time, to better engage them. Presenter: Steven Noels, CTO of NGDATA
Transcript of Get closer to your customers
Get Closer to your Customers Turn your data into valuable interactions that your customers expect!
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Connec/ng with the Customer
Preferences
Affini4es
Context
Behavior
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Customer Experience Customer spamming is doing more damage than good
Company & Customer Ac1vity
Customer CRM
Systems
Customer Web & Mobile
Customer Channel Campaigns
Customer Service Desk
Social Data
Website & online apps
Mobile App Server
Mail SMS
Broadcast
Offers
direct mail
ATM
web
Agent, IVR
mobile
chat
Relevance? Awareness?
Value? Timing? Clarity?
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direct mail
ATM
web
Agent, IVR
mobile
chat
The Personaliza/on Customer Experience “I have a customer – what does that customer value most?”
Customer Service Desk
Customer Web & Mobile
Customer Channel Campaigns
Social Data
Company & Customer Ac4vity
Customer CRM Systems
Mail SMS
Broadcast
Mobile App Server
Customer website & online apps
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I have a customer -‐ what are the top 3 products he is likely to buy?
Answering the Tough Ques/ons…
Which top hundred customers are likely to buy my product X today?
What is the best channel to connect with my customer, and when?
Can I turn around my most valuable poten1al churners?
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Overcome “Analysis Paralysis”
Proac4vely Engage with
Customers
Cope with plethora of data
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GeIng to Know Your Customer From siloed channel interac4ons into ONE customer “DNA”
Listen Learn
Customer DNA
Standardized, Ac/onable Metrics Single View of the
Customer
Channel all sources of customer interac/ons into
one data model
CRM and Demographic
Debit & Credit Card Transac4ons
Online Data
Loca4on
Wallet Informa4on
IVR data
Call Data
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“Listen” is about Interac/ons
• Interac4ons are behavior
• Connect data silos • Unify & augment
interac4ons
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Augmented
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“Learn” is about Metrics & DNA
• Iden4fied, standard, comparable Metrics
• Based on Interac4ons
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“Learn” is about Preferences & Affini/es
• Interac4on-‐based Preference Learning on Products & Categories
• Affinity Scores for longer-‐term profiling
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Empower End-‐Users to work with Customer DNA
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Organize Metrics along ac4vity-‐based
categories
Common, industry & custom DNA
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Beyond metrics: trend & accelera4on
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Execute
Event marke4ng with ac4onable
customer-‐level data
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Dynamic, metric-‐based segmenta4on & tracking
Build Target Groups
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Alerts for keeping track of key opportuni4es (or impediments)
Go from campaign-‐based to event marke4ng
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Website Real Time Offer Personaliza/on
Determine offer eligibility from: • Joe’s product preferences • Joe’s DNA (Interests, lifecycle, ac4vity,...)
Calls to Lilly with content: • Customer info. • Context info. • Session data
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Website Real Time Offer Personaliza/on
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Lily Enterprise -‐ Value
Analy/cs Transac/ons Strategic
Machine Learning
Bigger is Beher
Current BI Solu4ons
Prescrip4ve
Customer DNA Results-‐Driven
Genius of “AND”
Maximize Architecture
Objec4vity
Governance
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Experience the Difference with Lily
Listen Bigger.
VOLU
ME
Learn Faster.
SPEE
D
Execute Smarter.
ANSW
ERS
Volumes of Data Availability Questions Answered
Start working with Lily to discover results from Day 1
Zettabytes
Exabytes
Petabytes
Terabytes
Gigabytes
Seconds
Minutes
Hours
Days
Weeks
Unknown Unknowns
Known Unknowns
Known Knowns
DW/BI DW/BI DW/BI
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