How Conjoint and Max Diff Can Help CX Leaders Make Better Decisions With Craig Lutz

Experience strategists are navigating increasingly complex decisions. Customer journeys are increasingly complex, channels are proliferating, expectations continue to rise, and data is abundant. How do we help our companies make the best decisions about how and where to spend money? 

Craig Lutz is uniquely well positioned to help us answer this question. Craig has been a data scientist and researcher at Qualtrics since 2007 where he has conducted thousands of conjoint analysis projects with Qualtrics. He is also the designer of Qualtrics' conjoint analysis DIY technology, the author of Exploring Conjoint Analysis and a prominent thought leader on innovative quantitative research methods. We are thrilled to announce that he also recently joined our team at Stone Mantel as Conjoint Advisor!

In this episode, Dave and Aransas talk to Craig about how he helps teams like Google, Goldman Sachs, Uber and others make the decisions that really matter for customers, based on powerful analytics and what shifts when companies understand that time really is money.

You'll hear:

How Conjoint analysis can be used to get underneath what customers really care about and how it can be used to predict and change behavior

How Uber used these tools to design a radical new rider loyalty program

How Google: uses Max Diff to predict how customers will spend money

How Goldman Sachs used it to inform their employees experience by optimizing their benefit packages - and tailoring them to each individual office in ways that saved money while increasing real and perceived value

How conjoint could be a really groundbreaking understanding how and where customers spend their precious time 
How Max Diff relates to Clayton Christensen's  Jobs to Be Done Theory 

Check out the Experience Strategy Trend Report for more information on how to bring the power of context to your customer insight portfolio https://www.stonemantel.co/trendsreport

BIO:

Craig Lutz has been a data scientist and researcher at Qualtrics since 2007.  He has been a frequent presenter at conferences on the subject of quantitative research methods and has conducted thousands of conjoint analysis projects Qualtrics/ customer over his time there.  He also designed and developed Qualtrics' conjoint analysis DIY technology.
Craig graduated from BYU with a degree in Actuarial Science with a minor in Mathematics.  Craig and his wife Karrie have 5 kids and reside in Orem, Utah.