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Maritz Capabilities & Areas of Expertise

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William Ortman

on 1 October 2013

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Transcript of Maritz Capabilities & Areas of Expertise

In Depth Interviews (Virtual & Traditional)
New Taxonomy
Categorization
Clustering
Prediction
Link Analysis
Pattern discovery
Anomaly detection
Keyword and entity extraction

Thank You
Why Are We Here?
I Mean Why Are We In This Room Together?
Why Did Maritz Ask For This Meeting?
Maritz Can Do So Much More!
We Work With Many Companies...
And We Collect Information Many Ways
How We Might Help You
Product Quality Competitive Study
Features/Options Conjoint Study
John Zepp
Director, Marketing Science
Maritz
This & That
Retail Cultural Alignment Study
Maritz CONNECT
& Insight Communities
Infotainment
Research
Chris Travell
VP, Marketing
Doris Ehlers
VP, Business Management
Chris Travell
VP, Marketing
Deb Davis-Lenane
Director, Custom Research
Deb Davis-Lenane
Director, Custom Research
Making Surveys Enagaging
Comments- Leveraging Auto Coding
What Categories Do My Comments Fall Into?
How Are They Trending And What Is The Sentiment?

What Are Individual Customers Saying?
Or User Can Play Their Own “What If” Games
Word Clouds Used To Deliver Insight
What Are the Emerging Trends Customers Are Telling Us?
Enhanced Sophistication Uncovers Important Relationships
Retail Cultural Alignment Study
The Retail Culture Study is a powerful diagnostic tool to help Dealer
Principals/General Managers determine how closely their perceptions of how
the dealership operates match the perceptions of their employees and customers.
Results Are Analyzed 2 Ways
Performance ratings
Alignment between stakeholder ratings
Dealership Results Reveal:
Dealership’s performance on 6 key dimensions
Comparison to other dealerships
Comparison over time
Alignment within Dealership
DP/GM, Dept Managers, Front-Line Employees
Sales vs. Service
Alignment between Customers and Dealership
Analysis Reveals That Dealerships With Both High Performance And High Alignment Have Better Business Results
A 25-question survey is used – one version for Customers, a second for Dealership employees.
Customer version:
“The employees at this dealership are always willing to help customers.”

Dealer version:

“The people at this dealership are always willing to help our customers.”

Automotive
Financial
Hospitality
Retail/Restauraunt
Telecom/IT
*300,000 mystery shops annually is more than competitors who specialize in mystery shopping

But What If You Want A More Pure Research Approach?

Why Are We Talking About This?
Gain research insights
‘In our research and consulting on customer journeys, we’ve found that
organizations able to skillfully manage the entire experience reap enormous rewards:
enhanced customer satisfaction, reduced churn, increased revenue, and greater employee satisfaction. They also discover more-effective ways to collaborate across functions and levels, a process that delivers gains throughout the company.’
So What?
There’s a benefit to tracking the customer over time. MARITZ CONNECT makes this happen.
Harvard Business Review
Alex Rawson, Ewan Duncan, and Conor Jones
September 2013

The Truth About Customer Experience
Building Mutual Value
Is A Basic Pillar Of CONNECT
What Does Maritz CONNECT Look Like To Chrysler?

Have more satisfied customers
Increase loyalty
Increase retention
Sell more cars
Quantitative Research
Qualitative Research
Focus Groups (Virtual & Traditional)
Insight Communities
Continuous Dialogue
Intercepts
Blogs
Ethnographic Interviews
Bulletin Boards
Survey Methodology
This study can be a great catalyst for in-dealership coaching.
Insight Communities Are A Viable Option
Three Taxonomies Already Developed For Chrysler
Categories Linked To Important Quality Buckets
PolyAnalyst Can Then Be Used With Other Data Sets For:
Online Reporting Tools
Unlock Insights from
Customer Comments
Let’s Have Some Fun With This
Maritz’ SmartProbe™ Technology Makes The Web Survey Feel Like A Conversation (And We Get Better Data)

If We Engage Them, They’ll Want To Talk To Us
Creating Engaging Surveys Addresses These Issues
http://you2.us/bigkahuna/
“This isn’t exactly fun.”
“Do they do anything with what I tell them?”
“Why should I fill this out. It’s a waste of time.”
“It’s too long. I don’t have time for this.”
“These surveys are ugly.”
How Do ICs Differ From Other Offerings?
What Can We Do With It?
Mind-mapping
Mobile surveys
Online surveys
Card sorting
Virtual focus groups
Diary project

Live chat
Photo sharing
Reporting
Analysis
Questionnaire/Design
Conjoint Is About Understanding And Predicting Choices
Most marketing related choices involve tradeoffs ($)
Dan McFadden 2000 Nobel prize in economics
One of the leading market research methods used for:
-Product optimization
-Pricing
-Product line optimization
Maritz Experience
Maritz conducts conjoint studies frequently – for more than 50 different clients in the past few years

These studies have been done in Technology, Hospitality, Financial, Pharmaceutical, Automotive, Retail, Travel, Meetings, and Incentives.

They have employed a variety of methodologies in design, analysis, and reporting.
Maritz Is A Leader In All 3 Conjoint Components
1. Questionnaire/Design
Maritz is a leader in conjoint and other tradeoff methods
2. Analysis
3. Reporting
Simple Generic Conjoint With Constraints
Constraints often need to be applied in design.
Optional Dual Response Question May Be Added
Choice Task May Involve Structure
In this case respondents not only choose a brand, but a type of car within that brand.
Maritz Leads In Frontiers Of Conjoint Estimation
Hierarchical Bayes (HB) analysis is most common in market research and is what we typically use.
-Sawtooth Software CBC HB, R Bayes M
In 2007 Maritz developed Expectation-Maximization (EM) method of conjoint analysis.
In 2012 Maritz also developed Latent Class Ensembles
-Latent Class Ensembles significantly improves simple Latent Class
-Typically better aggregate predictions than HB
-Sometimes better hit rates at individual level
-Provides a benchmark for HB model
Specific Analytic Advantages In Conjoint Modeling
Non-Compensatory Modeling

Respondent Level Constraints
-Stepwise selection of attributes



Nested Logit to Handle Correlated Alternatives

Diminishing Return Utility Function to Handle Correlated Attributes
-Other custom functions
-Sometimes U = ∑βx is not enough
Nested Logit At Respondent Level Is A Maritz Advantage
Common Areas of Correlated Alternatives
-Product Line Optimization
-None vs Some
-Real World (Brands, Types)
In simulators it can be disastrous
-Add 30 versions of a product and it can dominate the market
Partial Solutions
-Individual level utilities like HB (helps but still occurs at respondent level)
-Randomized First Choice (Better but other problems)
Better Solutions
-Respondent level probit (structured covariance matrix)
-Nested Logit – Maritz advantage
EM and Latent Class Ensembles enable more complex modeling than HB
Non-Compensatory Requires Typical Conjoint Scenarios And Additional Questions For Non-Compensatory Attributes
"Thinking about <ATTRIBUTE>, what do you think of the following options?”
Most modelers simply ignore this
Simulator Screen Shot Basic Conjoint
Insights From Non-Compensatory Conjoint
Easy to use drop-down interface
Combined appeal of multiple packages for portfolio optimization.
Custom segments can be defined on the fly using an interactive form
Sensitivity Analysis shows optimal, near optimal, and poor configurations at a glance.
Simulator Screen Shot Brand-Price
Easy to use scroll-bars or type in price
Brand premium calculation shows how much Test Brand is worth vs. competitive brands.

Revenue or Profit Curve showing optimal price point and loss of revenue/profit at different prices.
Price elasticity curve for one or more brands can be shown, along with current price and demand.
Additional information about how respondents make choices
-What are the cutoff points we have to watch out for?
-How many customers do these cutoff points affect?
Improved Predictions

Infotainment
Qualitative Research For In-Depth Intelligence
Are Your Customers Getting The Bang For Their Buck With Their Infotainment & Connectivity Systems?
Learn More. Bring Your Customers' Experience To Life And Improve Your Diagnostic Insight For Next Generation Product Refinements
Soft Cutoff or Potential Screening Rules
Potential Must Have Screening Rules
Potential
Irrelevant
How Would They Be Used For Chrysler?
“Quality” Is Still Important To Purchasers, But The Definition Has Changed.
Three Dimensions Of Quality Still Among Top Reasons For Vehicle Purchase –
Reliability, Overall Quality, Durability
However, “Quality” As Defined By Number Of Problems Is changing, As Fewer New Buyers Report Problems.
67% of buyers report no problems with their vehicles, with less than 10% reporting multiple problems
So What Is Contributing To Buyer Evaluation Of A Vehicle’s “Overall Quality”?
Established
Dimensions of Quality
Highlight Need For A Different Automotive Quality Metric
Maritz Has Created A
Perceived Quality Index
That Closely Correlates And Diagnoses “Overall Quality”
Maritz “Perceived Quality Index” Components
Grouped By Quality Dimensions
“Perceived Quality Index”
Brand Ranking Non-Premium
“Perceived Quality Index”
Mid SUV Ranking
“Perceived Quality Index”
Mid SUV Scales
“Perceived Quality Index”
Mid SUV Features Scale
Full transcript