The Paradigm: From Sales to Profits Using Optimization Analytics

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Transcript of The Paradigm: From Sales to Profits Using Optimization Analytics

What to Expect from This Session

Explore the fundamentals and benefits of Lift Modeling and Constraint-Based Optimization Analytics

Learn how CVS Caremark has utilized their POS channel to deliver relevant offers and improve ROI

- Behind-the-scenes analytic engine that drives differentiated offers to unique types of customers

- Program evolution- Lessons learned

Introductions

Who We Are

Consulting firm specializing in information-based marketing and customer intelligence

Founded in 1999, with headquarters in Burlington, MA

Business problem solvers, skilled in analytics

Broad, practical experience across multiple industries

Outcomes driven - strive to deliver work that produces significant bottom line impact

ANALYTIC VISION. BUSINESS IMPACT.ANALYTIC VISION. BUSINESS IMPACT.

What We Do

Multi-media Marketing

Effectiveness

Customer Intelligence

and Reporting

Campaign Planning and Measurement

Predictive Analytics and

Scoring

Customer Acquisition and Development

Loyalty Program Strategy

Support Business Decision Making / Processes

Increase Business Growth and Profitability

Optimize Marketing Spending

ANALYTIC VISION. BUSINESS IMPACT.ANALYTIC VISION. BUSINESS IMPACT.

CVS

What does CVS stand for?

a. Consumer Value Stores

b. Caroline, Vanessa, Sophie

c. Convenience, Value, Service

d. Computer Vision Syndrome

CVS

Nation’s largest retail pharmacy chain

Recently opened 7,300th store

CVS fills more than 1 out of every 7 prescriptions in America

ExtraCare is the largest and most successful retail loyalty program in the country

ExtraCare Loyalty Program

(brief video)

Do you have your ExtraCare Card?

68 MM active ExtraCare cardholders

70% of CVS transactions are on the card

ExtraCare customers visit the store every month, which is twice as often as the typical non-ExtraCare shopper

Every second, 32 ExtraCare cards are scanned in the US

The very next day, these transactions can be transformed into customer insights

Lift Modeling and Optimization

Incremental Sales Potential“Best” customers are not always the same ones who drive campaign profitability

Best Customers - Top Sales Promotion Sensitive, High Incremental Sales

Response Model Lift Model

Limit or Exclude from Discounting Strategy

New Population - Test Offer Levels

Best Offers

Lift ModelingFocus directly on the consumer behavior that drives ROI

Predicts incremental response rather than total response

Model score provides a mechanism to target customer with the highest likelihood to deliver incremental sales

The challenge: incremental sales is an aggregate measure, while modeling and targeting must be done at the individual level

Offer Optimization Engine

Objective:

Determine the optimal offer assignment for each customer given certain goals and constraints

Automated approach to offer assignment; allows quick evaluation of numerous scenarios

Optimization targets: maximum lift sales, program revenue, units, ROI, margin impact; minimum incentive cost

Optimization Constraints: budget, incentive cost, ROI hurdle, total sales

Flexibility is a key benefit

Optimization in Action

How do you do it?Start by asking: are you leveraging everything you know about your customer?

Shopping Behavior

Demographics

Tenure

Employees /Non-Employees

Basket Profiles

Payment Type

Category BreadthPromotion History / Channel

Preference

Digital Behavior

POS Marketing at CVS

POS Coupons - Overview

Printed at Bottom of Cash Register Receipt

Primary Objective: Drive return visits

Customer data (what they buy, who they are) drives offer assignment

Offers: Product-Specific or “Open-Ended”

Open-Ended Offers

- Discount on any non-Rx item in the store- Automated trigger program- Redeemable on next visit - Broader offers drive most sales lift and ROI- Largest CVS-funded incentive program

Sophisticated targeting engine drives delivery of POS Coupons

CVS Approach – Trigger Offers

ExtraCare/coupon

John Smith

Save $4 on any $20 purchase. (UP TO $4.00 VALUE)

EXPIRES 11/4/2011

ExtraCare® Card #*******8047

*EXTRACARE CARD MUST BE PRESENTED TO GET THESE SAVINGS.  EXCLUDES TOBACCO, ALCOHOL, AND PRESCRIPTIONS.  NO CASH BACK. 

TAX CHARGED ON PRE-COUPON PRICE WHERE REQUIRED.LIMIT ONE PER CUSTOMER.

3363805547

Customized and Dynamic Targeted Offers

Offer Configuration and Cadence determinedquarterly by mining millions of data Points:

CategoryShopped Demos Past

OffersProfitLevel

Customer 1:Spends $12.50 per trip, visits

3x Qtr

Customer 2:Spends $22 per

trip and, visits 4x Month

Customer 3:Spend $15 per

trip and, visits 5x Qtr

Illustrative

PromosRx

Freq

Customer 1Matched up to $3 off $15 offer

Customer 2:Matched up to

$10 off $50 offer

Customer 3:Matched up to $4 off $20 offer

Evolution of POS Program Ongoing innovation and refinement has ensured lasting program success

Build Fact Base

Test and Learn

Optimize

Optimization System

Refine

Response, Modeling,

Differentiation

Innovate

Lift Modeling

This could not be achieved without a commitment to test and learn

We were here

Step 1 Target and Execute

R, F, M

Step 2

Step 3

Step 4

Step 5

-15%

-10%

-5%

0%

5%

10%

15%

20%

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

Campaign ROI

The Catalyst: Declining ROIResponse model targeting was beginning to be unprofitable – need for

investigating drivers and potential solutions

2009 2010Key Question: Who drives incremental sales?

CampaignSales

IncrementalSales (Lift)

Discount /Coupons

NetIncremental

Sales

NetIncremental

Margin

Profit tInvestment = ROI

Modeling Approach Explore a wide range of variables to capture key customer

behaviors

- Promotion sensitivity and history, brand preferences, loyalty, demos

Print

visit, purchase

Redeem

visit, purchase

Spend

basket size

Create multiple predictive models for each step in the coupon redemption process

Estimate a wide range of success metrics

Optimize offer assignment, unique to each customer, given predicted behavior in response to each offer scenario

Program StructureThe final solution involves multiple models that capture the profit dynamics

Shopping Behavior /

Loyalty

Price & Promotional Sensitivity

Coupon Usage

Category Patterns

Predictive Models

(14)

SalesSales

Sales LiftSales Lift

CostCost

Margin Lift

Margin Lift

ROIROI

No OfferNo Offer

$3 off $10$3 off $10

$4 off $20$4 off $20

$5 off $25$5 off $25

$10 off $50$10 off $50Customer Demographics

Qualifier (1) Redemption (8) Sales (5)

Old Target New Target

Don’t Target

Recommended Target ChangesSignificant changes to targeting and offer assignment were recommended

Add Drop Keep

Higher incremental sales

Stronger ROI

The TestA test was implemented to compare the new approach to the old

Eligible Customers

Control Group

New Strategy - Lift Modeling and

Optimization Based

Existing Strategy - Response Model Based

Control Group

Test ResultsIt didn’t work!

Existing Model New Model

Incremental Sales and Profit Per Customer

Incremental Sales Incremental Profit

$3 and $10 coupon worked well

$4 coupon drove negative results

Identified disconnect in success metrics

If At First You Don’t Succeed…

Granted another opportunity to “split” the eligible population in a head-to-head test

Refined and implemented models using more recent data

Tested alternative approaches

- Model Based Targeting and Offer Assignment

- “Strategy-Based” approach – art plus science

Art + Science Wins!

Existing Model New - Model Based New - Strategy Based

Incremental Sales and Profit Per Customer

Incremental Sales Incremental Profit

ROI 4% 15% 16%

Lessons Learned

Lift Modeling is not straight forward – be open to testing

- Most challenging: predicting incremental sales dollars and ROI

- There are several alternative modeling approaches

Focus on the right metrics, and be consistent with corporate KPIs

Optimization is likely to require human intervention – solid business understanding and good intuition

In Conclusion

Leverage as much data and customer insight as you can to maximize

The next generation of marketing analytics is moving beyond traditional response modeling

- Understand your success metrics and use analytic tools that focus directly on those metrics

- Be aware of the challenges

The best solution requires a balance of technique and business knowledge

Getting Started

Set up randomized testing with appropriate treated / control quantities

Capture historical campaign data

- Customer characteristics at time of execution

- Response results

Ensure operational system infrastructure is in place

Identify resource to develop solution

Marcy Riordan Michael Parduhn

ANALYTIC VISION. BUSINESS IMPACT.

Thank You!

For more information contact: mriordan@iknowtion.com (781) 494-9989