1. Questions you ask of your customer data – if you could
Are all your customers alike? Do they all
behave the same way?
Do you know what your customers will
buy and when?
Is your communication relevant to your
customer?
Are you influencing your customers to buy what
they want from you?
2. Understanding and engaging customers in a meaningful dialogue
Who is the
customer
Optimize and
Improve
What does the
customer want
What to offer. How.
How the customer
engages
3. How – by embedding analytics thru your marketing decisions
Behavioral Segmentation
How
Post Event
Cataloguing
When
Where
Optimize and
Improve
Compare
Campaigns
Post Event Couponing
& Circulation
Analyze Campaign
Who is the
customer
Recency,
Frequency
& Monetary
Who responded
Customer
Activity History
Loyalty Lifetime
Demographic
Profile
value of purchase
Geographic Profile
What does she buy
only occasionally
Growth
Pricing
Switching
What products he
buys regularly
Product
What does the
customer want
as per Customer
Promotion
Acquisition & Retention
Channel Preference
Execute
Personalized
Campaign
When did he
last buy & what
Send Promotion
Define
What to offer. How.
Set Triggers
Conceptualize Associate
Affinity
Purchase
Behavior
Is he likely to move away
Coupons
Value
Optimize
Channel
Creative
Which offers
did she respond to
in past?
Cross Sell
How the customer
engages
What is his Preferred Channel
of Communication?
Up-Sell
Scenarios for
Customized Offers
Loyalty
Performance
4. Jenny Lee shops
once a month for
staples like
milk, bread and
eggs
Multi-dimensional
segmentation
predicts the her
lifetime value and
loyalty
Affinity Analysis
identifies new
cross-sell and upsell opportunities
You reward Jenny
with timely &
personalized Offers
Jenny joins Loyalty
Program & starts
accumulating
points
Jenny feels
rewarded with the
discount and
engages with your
brand.
Her transaction
history helps build
a unique behavioral
portrait
She starts
shopping more
regularly
5. Significant financial reward of understanding
and meeting customers’ expectations
$2Bn food grocer
Customer churn of est. ~12% of
member base
Understand unique media
preference
Potential Churn customers demonstrate
distinct purchase behavior and Comm.
preference
Retention and win backs create
a revenue lift of >$120Mn
6. With ARC Customer Analytics
ARC TargetOne
ARC Customer360
Understand your customers
Predict their behavior
Drive marketing outcomes
Execute personalized
promotions
Optimized Marketing
Analytics consulting to drive
marketing effectiveness
SALE
ARC Loyalty247
1-1 communication through
a mobile platform
The deck needs to have broader Manthan branding. Should not feel like a slideshow, can have good animationIdeally darker background to contract against Linkedin screen
One slide to present Manthan’s broader framework for customer analytics.
One slide to present Manthan’s broader framework for customer analytics.
Bottom up opportunity identification and actionAdd a few images here.