A Statistically Driven Solution to Understanding Customer Needs

A Statistically Driven Solution to Understanding Customer Needs

Asiri Silva • June 2, 2025
Asiri Silva • June 2, 2025

Share

A Common Problem: Understanding Customer Needs 

Investors and management teams often struggle to discern what customers say they want versus what they actually want. Traditional innovation frameworks and customer needs assessments (e.g., Clayton Christensen’s “Jobs to be Done” approach) rely on in-depth market conversations or rudimentary web survey analysis (e.g., ranking criteria on a scale from 1-7) to inform strategic decisions. While these approaches may often be sufficient, there remain many instances when a market’s purchasing dynamics are too complicated or nuanced for customers to clearly express their purchasing rationale. 


In these cases, there are meaningful risks, particularly for management teams seeking to refine product/market fit. The most effective way to mitigate such risk is to observe customers’ actions instead of trusting their stated intent (e.g., Eric Reiss’ “Build, Measure, and Learn” approach); though this requires a disciplined commitment to resourcing and iteration. 

A Statistically Driven Solution

At Grant Thornton Stax, we employ an alternative analytical approach to solve this issue. Our approach measures customers’ derived needs (as opposed to stated) without requiring lengthy product/market fit testing. The approach is rooted in a MaxDiff analysis, which begins with collecting data using best-worst scale web survey questioning. This questioning format presents respondents with a subset of criteria and asks them to select the most and least important on each screen. The answer options adapt based on respondents’ prior selections, thereby forcing tradeoffs while reducing survey fatigue. 


Using this data, we run a statistical analysis to quantify the relative magnitude of purchase criteria importance. The outputs from this analysis are meant to represent the “derived importance” of a customer’s purchasing criteria (i.e., what is truly meaningful versus stated as meaningful). 

Image of carious charts displaying examples of Derived Importance Analysis (Web Survey/Data Collection, Statistical Analysis, Data Synthesis)

This analysis can serve multiple purposes. In one case, on behalf of a B2B software client, we used these derived purchasing criteria and firmographic attributes, in combination with a statistical clustering analysis, to create a sophisticated market segmentation—versus segmenting based solely on firmographic attributes, like size or region. Ultimately, this enabled us to move beyond surface-level segmentation and deliver actionable strategic recommendations that changed the company’s product roadmap and commercial motion, in line with core customer needs. 

This analysis can serve multiple purposes. In one case, on behalf of a B2B software client, we used these derived purchasing criteria and firmographic attributes, in combination with a statistical clustering analysis, to create a sophisticated market segmentation—versus segmenting based solely on firmographic attributes, like size or region. Ultimately, this enabled us to move beyond surface-level segmentation and deliver actionable strategic recommendations that changed the company’s product roadmap and commercial motion, in line with core customer needs. 

Image of Asiri Silva
Image of Will Barden

Asiri Silva

Head of Data Science

Market Segmentation Based Behavioral and Firmographic Attributes

In a different case, a transportation service provider needed to pinpoint what marketing messaging would have highest resonance with school district customers. By running a similar MaxDiff analysis testing the relative importance of student outcomes, Grant Thornton Stax enabled the client to craft more targeted and effective sales and marketing materials, while also informing product development to strengthen its competitive differentiation. 

Chart of Messaging Reach: All Outcomes Resonance, TURF Analysis

Conclusion: A False Trade-Off 

Sophisticated customer insights can be achieved using a lean customer research approach. Using Grant Thornton Stax's web surveying and statistical techniques, customer needs be can more precisely assessed and implications can be incorporated into actionable sales, marketing, and product strategy. Visit www.stax.com or click here directly to learn how we can help develop strategy using deeper customer insights.

Read More

The Investment Case for Experiential Marketing Agencies: Growing Mission Criticality of Live Events
By David Lindsay • October 15, 2026
Experiential marketing agencies are transforming into strategic partners, and enterprise clients are valuing agencies that create relationships built on trust and operational excellence. Read more.
Featured by Bezinga: Health Care PE Is ‘No Longer An Easy Source Of Returns'
October 8, 2026
Rob Larson was featured by Bezinga, offering his expert insights on the current state of healthcare within PE and why investments continue to be made in the industry, Read more.
What Local Governments Need from GovTech Right Now: Lessons from CivStart
By Chen Liu • October 1, 2026
Partner Chen Liu attended CivStart's GovTech conference, sharing his insights and key takeaways on what GovTech providers and investors should know. Read more.
Grant Thornton Stax Top 20 2025
By Florent Jarry & David Lindsay • September 17, 2026
Grant Thornton Stax has released its annual Top 20 Ranking of Exhibition Organizers. Click here to explore the full list.
Feat. by Pitchbook: The future of diligence is not integration. It is conviction.
By Paul Edwards • September 15, 2026
Global Practice Leader Paul Edwards explains how diligence is changing and how confidence and conviction are adding exit value. Read the full article here.
Featured by Carta: PE is trying to figure out where AI fits into the future of healthcare
By Rob Larson • September 8, 2026
Rob Larson met with Carta to discuss the growing problem of supply and demand in the US healthcare system, and how a technological revamp could be necessary. Read the full feature here.
Show More