Cross Channel StrategyHow Market Mix Modeling Can Impact Cross-Channel

Budget and Business Planning

Speakers:Dhiraj Rajaram, Mu Sigma

Craig Kronzer, UnitedHealth Group

Session Objectives

• Learn approaches to Market Mix modeling – how it enables measurement of multi-channel activities

• Discover the advanced framework to quantify ‘true’ cost of acquisition, netting out cross channel effects and cannibalization

• Evaluate tools and platforms for budget scenario planning and optimize marketing budget allocation

BACKGROUND

Organization Overview

• Established in 1998 as a AARP/UHG relationship

• Nation's largest supplemental insurance program focusing on people age 50 and over

• Distribution: DTC, Employer, Agent, Web

• Largest provider of pure-play decision sciences and analytics services

• 30 Fortune 500 Clients in 10 Industry Verticals

• Headquartered in Chicago IL with presence all over the US

Insurance Solutions

Business Problem

Background• Insurance Solutions uses

multiple marketing channels to attract members

• Operational constraints result in less than complete attribution of sales to marketing efforts

• Several sales are not attributable to any of the marketing channels

Business Hypotheses• The business wanted to

test the hypothesis that unattributed sales are driven by marketing

• In particular, there was a need to understand the impact of DRTV on sales

• The solution framework required to measure cross-channel impacts

The Challenge of Measurement

Attribution by Channel

Sales

DRTVOther ChannelsUnattributed

• A major portion of sales is unattributed to any advertising channel

• Sales attributed to DRTV are low compared to proportion of investment

• Business wants to measure the true effect of TV advertising by understanding the “halo effect”

The Need for Measurement

Channel 4

DRTV

Channel 2

Channel 1

Cost per Sale

• Due to relatively low attribution of sales to DRTV, the apparent cost of acquisition for the channel is high

• There is a need for improved measurement to calculate the ‘true’ cost of acquisition

• Cost of acquisition is a key component in marketing planning

Cost of Acquisition

SOLUTION APPROACH

Problem Solving Framework# Strand The Why?

The What & How?

1 SCQInitial

XXX YYY ZZZ

XXX YYY ZZZ

2 Factor Network

XXX YYY ZZZ

XXX YYY ZZZ

3 Hypothesis Matrix

XXX YYY ZZZ

XXX YYY ZZZ

4 SCQFinal

XXX YYY ZZZ

XXX YYY ZZZ

SCQInitial SCQFinal

SCQFinal SCQInitial

FactorNetworkFactorNetwork

HypothesisMatrixHypothesisMatrix

The Mu Sigma Problem DNA ensures appropriate emphasis on design and hypothesis leading to right representation

Solution ApproachThe ms Factor Network

Factor 2

Factor 3

Factor 4

Problem

Factor 1

Factor N

Mapping the exhaustive set of factors enables testing of all relevant hypotheses

Sales

Direct Marketing

DRTV

Other DTC

Agent

Seasonal Index

TrendExternal

Economic

Product price changes

Competitor data

Demographic data *

The Market Mix Framework

• The Market Mix Framework decomposes total sales into contributions by advertising vehicles and external factors

• Contributions from different channels enable calculation of ROI

MMX Modeling ApproachesDirect Marketing

Print

Agent

Direct Response TV

Marketing Mix Model

Sales = f(DM, DRTV, Print, Web, Events…)

Contribution

Percentage of enrollments due to each promotional program

Total and Marginal ROI for each program

Cost per Sale

Lifetime Value

Optimization

Promotional spend allocation at aggregate program level taking into account diminishing marginal

Portfolio level optimization for all products

WebPro

mo

tio

nal

Act

ivit

y

Measurement of diminishing returns

Multiplicative

Unattributed Sales

Measurement of individual contributions

AdditiveMeasurement of

cross channel effects

Multi Target

Ad stock – Lagged effectsDM enrollments Effort adstock 0.2 adstock 0.7

Weeks

Enro

llmen

ts

xx

Adstock transformation methodology

At = Tt + λ At-1

Where:• Tt is the value of the marketing variable at time t

• λ is the decay or lag weight parameter• At-1 is the carryover of Advertising at time t-1

“HALO” EFFECTS AND REATTRIBUTION

Multi-target Model

Total Sales

DRTV Sales

Channel 1 Sales

…

Unattributed Phone Sales

Other unattributed

sales

Each of the target sales modeled on all advertising inputs as well as external factor

Reattributed Sales Original Attribution

Post Modeling Reattribution

Sales

DRTVOther ChannelsUnattributed

Sales

DRTVOther ChannelsUnattributed

The Market Mix models are able to measure the contribution of advertising to previously unattributed sales

Improved measurement

Channel 4

DRTV

Channel 2

Channel 1

Cost per Sale

Original CPS

Channel 4

Channel 2

DRTV

Channel 1

Cost per Sale

Reattributed CPS

Due to higher level of attribution in sales, the effective cost per sale reduces significantly

Halo EffectContribution of Media Activities

DRTV Channel 1 Channel 2 Channel 3 Channel 4 Channel 5

Enrollments from channel

DRTV

Channel 1

Channel 2

Channel 3

Channel 4

Channel 5

Unattributed

Halo Effect

Self ContributionThe ‘halo’ effect of advertising channels enables

quantification of cross-channel contribution

Impact of the initiative

• Cost of sale calculated based on direct attribution used in budget planning

• Member lifetime value calculations biased by high cost of acquisition in some channels

• “Dark Test” conducted to verify impact of TV on unattributed sales

• The optimization process for allocating budget across channels refined by using ‘true’ cost of acquisition

• Budget allocation across marketing channels changed significantly

• “Bright Test” conducted to test additional advertising opportunities

Pre-MMX Modeling Post MMX Modeling

SPEAKER BIOS

Speaker Bios

Dhiraj Rajaram

• Founder and CEO of Mu Sigma, an analytics services company that helps clients such as Microsoft and Dell institutionalize data-driven decision making.  Prior to founding Mu Sigma, he advised senior executives across a variety of verticals as a strategy and operations consultant at Booz Allen Hamilton and PricewaterhouseCoopers.

Craig Kronzer

• Leads a Data Analytics team for UnitedHealthcare. Team is responsible for enterprise-wide analytics including building predictive models, designing and analyzing marketing tests, and claim data analytics. Previously, was with Carlson Marketing Group and Lands' End.  Craig holds an MS in Statistics from the University of Minnesota and BS in Computer Science from the University of Wisconsin.